November 2, 2023

Episode 015:

Unlock Your AI Potential with Data

In this episode, Fred explores the current data & AI reality in the banking sector with Zennify's Manvir Sandhu. The discussion dives into the evolution of data analytics in banking, the potential of AI in financial services, and the benefits of CRM systems like Salesforce. They also discuss data strategies, such as data lake houses, and the role of platforms like Databricks and Salesforce's Data Cloud in maximizing efficiency and enhancing marketing and customer strategy. The episode also tackles the potential of AI in automating and improving customer service and loan processing, as well as the necessary data security considerations.

Episode 015: Unlock Your AI Potential with Data

by Banking On Disruption Podcast

Show Notes

💡 Join us for this episode to dive deep into how banks can move through their journey from foundational data work to leverage practical AI use cases. 🚀 🏦

We sit down with Manvir Sandhu, Co-Founder and Chief Innovation Officer at Zennify, to discuss how banks have made the journey from focusing on traditional reporting needs to using data, analytics, and AI as a competitive differentiator. 🔍

We discuss advantages of open vs closed environments in data management, and the implications of each for data security protocols. We also explore how platforms including Salesforce Data Cloud, Databricks, and Snowflake can contribute to an institution’s data landscape. 🛡️ 🌐

Our episode concludes with a look at the potential of automation in reshaping the banking sector, particularly in back-office operations; and Manvir shares practical use cases from underwriting to chatbot interactions in call centers. 🤖 🏢

After the interview in our Quick Takes Roundtable Josh, Eric, and I discuss whether or not boomeranging is a good idea if you were a worker affected by the layoffs earlier this year, how pending open banking regulations will impact consumer choice and what pressure that may put on community banks, and with all the excitement in AI – What is standing in the way of banks actually using it.

Links & Mentions


Manvir Sandhu

Manvir Sandhu

Founder & Chief Innovation Officer, Zennify

Founder and Chief Innovation Officer at Zennify Leading Zennify’s Gen AI and Innovation Strategy and GTM Plans

Full Transcript

00:03 – Manvir (Guest)
Yeah, absolutely. It’s an exciting time and the beauty of what happened with ChatGPT and just that whole phenomena is you can have a very practical, real-life conversation with the institution leader like, hey, are you using, how are you using, chatgpt, how are you using OpenAI, how is your kids using it, how are people at the bank using it? And that way you initially remove that barrier of demystifying this Uber high-tech thing and also it naturally starts to bring in the comfort level and some of the security conversations.

00:53 – Fred (Host)
Hello and welcome to Banking on Disruption. I’m Fred Cadena. In this episode. I am so excited to be bringing you my friend, Manvir Sandhu. For those of you who don’t know him, Manvir is the founder and chief innovation officer at Zennify, where he uses his more than 25 years of enterprise IT and CRM experience to deliver transformational sales force and data solutions to banks and other financial institutions. Manvir is the proud father of three, living in beautiful Northern California. He graduated from Cal Poly, San Luis Oblispo, where he was a four-year letterman in football. That probably explains why he’s such a fierce competitor.

Over the years, Manvir and his team has kept me on my toes, as we have both worked in and with some of the most innovative banks in the US. I’ve been excited and grateful to have developed a respect and friendship with Manvir over the years, and I’m super excited for our conversation today where we’ll be digging into practical AI applications for banks, whether just getting started or a bit down their journey, and I hope you’ll stick around after the interview for a quick takes roundtable. Josh, Eric and I will discuss whether or not boomeranging is a good idea. If you were a worker affected by the layoffs earlier this year, how pending open banking regulations will impact consumer choice and what pressure it may put on community banks. And, with all the excitement in AI, what’s standing in the way of banks actually using it?

While you’re listening to this podcast, why not take a moment to follow us on LinkedIn at the Banking on Disruption podcast and on Instagram at at bankingondisruption?

Now sit back and strap in, because our show is coming to you, and welcome back. I am super excited this week to bring you my friend, manvir Sandu, who’s the founder and chief innovation officer at Zennify. If you’re not familiar with Zennify, you should definitely check them out. They do a lot of really exciting work with banks and other financial institutions in Salesforce and expanding increasingly into data and artificial intelligence roles, and that’s why I’ve asked Manvir to join us on the podcast today. I’ve been following what he and his team at Zennify have been doing around AI for the last several months and was really excited to spend some time with him and his team during Dreamforce, seeing some of the presentations and how they’re really at the forefront of the AI frontier and rolling out this functionality in real time out to clients actually using it in banks to get real results. And so, manvir, thank you, and I appreciate you making time to join us on the podcast.

03:39 – Manvir (Guest)
Great to be here. Fred and I know we’ve been working together and talking for a long time, so this is a great opportunity for us to brainstorm and exchange notes.

03:48 – Fred (Host)
Sounds fantastic. Well, I’m really excited. I just want to maybe start a couple of steps back. You’ve been in the game for quite some time. You’ve seen how data analytics has picked up over the last 10 years or longer to really become crucial, even ahead of the last nine months, and like all the excitement around generative AI. So do you want to talk a little bit about how you’ve seen data analytics evolve in banks over the last decade, and what challenges do you think banks are still struggling with over that period of time?

04:20 – Manvir (Guest)
Yeah, fred, it’s a great question. I think when I meet with banking leaders, what I see more and more often is what really was a catalyst for them to even embark on the initial data strategy was reporting. Really like executives, business leaders needed certain information, so they started in this BI world and you have BI people at these banks pulling together information across all these different systems. There’s some of the busiest people at banks actually is the BI folks. One leader the other day referred to as deaf by reporting, because they literally generate one report and then there’s questions and that leads to more reports, and so eventually they arrived at this idea of like, oh man, we need an operational data store or a data warehouse right where we can take information across all these different systems, pour it into this storage space here and now it’s easier for me to run my BI, my reporting, from there, and I feel like I’ve solved the problem because I’ve got 80% of the bank’s data in this system. Sure, there’s latency, but I can give my stakeholders what they need, and so I think that worked for a while. It got the job done.

But then, as those institutions started to get more serious about CRM and really understanding their business better understanding their customers right and not just needing insights but then taking action on those insights. All of a sudden it introduced the concept of a CRM system like Salesforce where, lo and behold, if you were able to successfully set up, you know, like financial services, cloud or sales or service at least around the customer domain, a lot of your reporting didn’t even have to be reporting anymore. You could just go into the system and, assuming that people have adopted the system and are using it the right way, then you can get the information you need out of this system. That is like cloud-based, and so I think that was an awesome evolution for the institutions. They’re not all there, but we know a lot. We’ve worked with a lot that have gotten to that phase. But then they want to know a cross-line of business. They want to know, they want even more information around information that’s in the banking core, for example. And so all of a sudden it called for more data and more integrations, and so you’ve got amazing tools like Milsoft that can help with some of that and connect some of that information. And then it just started to introduce another problem. It’s like well, now my CRM is getting loaded up with a bunch of data, and so now there’s like questions around what the traditional questions they ask is what is the system of record? What is that one golden record? What is that one unified source of the truth? And that’s what we hear nowadays and it’s like it’s asking the wrong questions because they’re not necessarily thinking about the architecture and the strategy the right way, because people are so inclined to point at one system as a system of truth or whatever. And so I think there’s been some evolution.

I’d say about half the institutions we work with are still in that death by reporting mode.

They might have moved to a data warehouse that’s on-prem, and then some have progressed to this next level of like. Well, we at least have advanced beyond that and we’re using a CRM and we’re getting information we need and we’re starting to act upon customer data, we’re responding to customers. But now, with AI, what it’s done is it’s been an even a bigger catalyst to be like oh man, I’ve got data all over the place and I’ve got unstructured data. So you still have people that are in phase one, that are dealing with those old problems. So I would say, generally in financial institutions probably not the larger, larger, big ones that have a lot of IT people and have built out a lot of their own systems. In most of the regional banking world the mid-market that you and I know really, really well they’re still very much in those early phases and they’re just starting to look up for air. And here we are throwing AI at them and they’re still like man, I’m still back here.

08:53 – Fred (Host)
We’re still catching up for the last five years.

08:55 – Manvir (Guest)
Exactly, exactly. So I know that’s a lot, but that’s the world and the landscape as I see it.

09:01 – Fred (Host)
No, I think that makes a lot of sense, that kind of moving from that. You know a bunch of one-off reports and latency and you know questions about data quality to the CRM a little bit more near real time, but still some occasional questions of latency and whatnot. And I know again, this is going to be a very dangerous question because the answer is a consultant. As always, it depends. But if you were talking to a bank today and they’re like what is the architecture I should be thinking about for the future, like what are the tools and platforms that should be in place, what would you point to a bank to say this is, you know, kind of the hockey analogy, right, you go to where the puck’s going to be. You don’t go to where the puck is now. Where’s the puck going to be on this in a couple of years?

09:47 – Manvir (Guest)
Yeah, it’s a great question and I, you know we, when we address this topic, we first like to step back and, you know, understand the business and their strategy. Ultimately, what you want is you want business leaders at the institution that are, in fact, data driven. Right, they run their business that way. They want to understand the data. There’s a genuine, you know, strategic value around that data. So you’re not still having the CRM conversation like. They’re well beyond that and you know they obviously understand the value of CRM. They understand the value of data.

You have to, kind of, because that’s what’s going to get the executive stakeholders aligned. Else, what you’re going to have is siloed conversations. You’re going to have an enterprise data architect or chief data officer that might have this vision right, or it could be a line of business leader or the CEO that has the vision and they’re trying to catch everyone up. Ideally, they all get on the same page and playing and they realize like, okay, wow, we’ve got to think about this holistically, strategically. We need to assign an owner, right, you need an executive sponsor and an owner, because sometimes that’s like half the battle is who owns the data strategy, right, if it’s born out of the CRM effort, and then you just kind of throw that on top of the CRM leader, who’s not really versed, you know, on how to do enterprise data management, strategic data management.

11:17 – Fred (Host)
I imagine it also has to be somebody that has some juice of the organization right, Because they’re going to have to broker a lot of conversations. They’re going to have to really work hard to build consensus across the different stakeholders, both on the IT side and across the lines of business.

11:32 – Manvir (Guest)
Absolutely, and there has to be value assigned to it. Because I know your question was about like infrastructure and kind of solutions, and we’ll get to that in just a second. But you know there is a lift and there isn’t necessarily an immediate impact of that lift because there is some infrastructure components. And so to ask, you know somebody that’s paying the bills to invest in infrastructure? You know they’re going to want to know what am I going to get in return, which goes back to why the entire enterprise has got to be unified on the strategy and have a unified vision around the value of data and what it can do for the business.

And once you’re there, then you can start to architect things and say, okay, let’s look at how you’re using you know these various systems and using the data, right. What are some of the key KPIs and metrics? Where is that information stored today? The good news is, no matter what state they’re in today, I do believe you know, because you’re talking future, I’m talking like right now we believe that the technology has made incredible advancements, especially with the concept of a data lake house, for example, which is a, you know, cloud based piece of infrastructure. That’s very dynamic, right, and we prefer more open infrastructure there versus lockdown. You know kind of proprietary.

12:57 – Fred (Host)
Do you mind if this is going to be a little bit basic, but I think a lot of our listeners may not know a data lake house and how that differs from a data lake and some of the more traditional data warehouse structures. Can you just give a 50,000 foot view on that?

13:12 – Manvir (Guest)
Yeah, absolutely so it’s. You know, the concept is so, obviously you have the store side of it, right, like you can, you can pour data into this thing, but it kind of gives you the dynamic capability of you know, consumption and using only the information that you need when you need it, right. Whereas, like, if you’re filling this tub full of data right now, I’m paying for that whole thing and it’s got all that stuff loaded in there, right? I can’t necessarily get to what I need when I need it and I’m also paying for that whole thing, like paying, you know, rent for the whole house when I only just needed like one room, right, and so data lake house is just a lot more dynamic in that I can structure that data differently, and it’s not just structured data, is unstructured content as well. I think it’s a really another important differentiator between you know, your, your classic data warehouse and your, your data lake house is that I can take conversations that are happening, I can take content, I can take pictures, I can take video and I can index all those things in this like sophisticated way so that it’s easier to organize, manage, get to it and I can again pay for consumption, meaning I’m not using all that stuff, utilizing it all at one time. I need to utilize certain aspects of that data at certain key times. That’s what I should pay for, not not for for just storing all that stuff into this place. You know what I mean.

So it’s like a combination of API’s and integrations that are involved with it too, because that’s what’s allowing you to do, that is, it’s allowing you to pull information as you need it right From core systems like core bank existence, like Jack Henry and Symmetar and some of these. You know I don’t want to take everything that’s in there and pour it all into here. I just want, like, key pieces of information, key times. You know what I mean. So it’s a lot more efficient, ultimately, right. And then, because it’s more efficient and because I have, you know, all this different type of information there’s advanced tools with some of these lake houses like Databricks. That allows you to now sort of get to information as you need it. It lets you complete information that’s incomplete, right, which is really cool. It allows you to have lineage to see where did that information come from and how has it changed over time, Because all these things are really important in compliance in audit environments for, like banks.

15:43 – Fred (Host)
And, quite frankly, even for users to have trust in the, in the data and the accuracy right. You want your users to feel confident that what they’re looking at is the right information.

15:54 – Manvir (Guest)
Absolutely. And so what you know, I don’t have a diagram to show you, but it’s almost like see, I have this dynamic environment. Now I don’t just have this like one system, this one storage space. I have this dynamic environment where I’m pulling key information as I need it, right, and so I’m not hard coding these integrations from system to system to system to system, right, I’m just kind of pulling key information from key areas, bringing it together.

And the reason the data strategy is important because now I do, now I can start to align around data standards and governance, I can start to say, okay, this is how we’re going to define the customer for this use case, right, and so this is how I’m going to define the customer for this use case. It can be very different, and I want actually I need some read back capability. I need to be able to write back capabilities. I need to be able to take this information now that actually is the most up to date, and send it back to the core, because that is, in fact, now the updated address. To do those things in the older environments requires a lot more intensive development, software integrations, whereas in this new environment it’s a lot more dynamic and it’s just a lot more powerful, flexible, and this is without even getting into AI, right this?

17:13 – Fred (Host)
is all the precursor. This is just getting the data right.

17:16 – Manvir (Guest)
This is just getting the data right.

It’s great for, like ML, like machine learning, because all of that data and being able to kind of churn through a lot of that data again very efficient way is why a platform like Databricks has been so strong is because it was designed for machine learning at the end of the day.

So they have to make it efficient and open and sophisticated, and it was probably ahead of its time even initially, because go back to the original examples I talked about the death by reporting they just need a operational data store reporting. Well, the industry went from that to AI very fast this time last year we weren’t talking about AI the way we are now. Right, and so talk about a catalyst. That sped up all these conversations. And now you go back to this data strategy and you go wait a second, did I architect this stuff the right way for this next massive trend and dynamic of AI? Chances are you have it, but the same data lake house that I’m talking about is an awesome piece of the infrastructure to support artificial intelligence, right? So I don’t know if that makes sense of it all, but that’s yeah.

18:34 – Fred (Host)
Yeah, it definitely did and I think it was really helpful, I think also giving that explanation of how that data lake house is different and I wouldn’t necessarily say better, but potentially provide significant advantages in efficiency and it’s just a much more modern approach to putting that together. You mentioned Databricks and I think at one point you were saying something. I cut you off with a question but you said you prefer a more open source or maybe I misheard that kind of an architecture. Do you want to talk a little bit about Databricks and kind of some of their players and where you see that those key decision points in what platform a bank should consider?

19:19 – Manvir (Guest)
Yeah, I think, because it’s interesting. The banks usually they’re in the early phases and they’re concerned about security and customer data and PII and breaches and they’re still trying to understand moving to cloud and those are all legitimate concerns, whereas when you get to this conversation or openness, why have an open platform at the end of the day, versus something that’s more locked down or proprietary? Sometimes people have a misconception. Well, that means it’s more secure. It means it’s more locked down. I actually like that. I prefer that because it’s in this controlled environment. That’s not necessarily true. The security protocols that go into some of the open infrastructure are just as robust and rigorous as the closed environment. The difference with the open environment is it allows, like a Databricks for example, to utilize the innovation that’s happening and the infrastructure that’s happening in some of the surrounding complementary pieces, and it allows you to do that more efficiently, because, ultimately, databricks was created with the idea that you’re going to get all this power, but it’s going to be yours, it’s going to be your data, your strategy, and we’re reducing your dependency upon third parties Because, if you think about, like Jack Henry, in some of these on-prem mainframe based systems, there’s literally third parties, like service providers that have made a killing in a living off of just helping banks manage all that infrastructure and all that information, and they essentially locked down that bank into their five-year contract agreements. I’m literally talking to like three or four banks about this today and they’re trying to figure out how do I get out of this old world I’m actually and so there was a dependency that was created, and this whole industry to some extent has created this dependency upon certain software vendors, certain third parties, and the idea initially was well, this is to stop breaches and security and we’ll help you protect all this stuff. But in reality, it created a dependency that involves monetization. You know what I mean. It’s like you don’t really have access to your data, which is crazy. It’s your data, but you can’t even really get to it the way that you want. You don’t control and own it.

So when you enter into a Databricks environment, it’s very empowering. Like this is your data and we’re going to charge you to use your own data. We’re going to charge you to utilize it effectively and strategically and then you’re going to be able to choose what third parties, what applications, what other surrounding pieces of infrastructure make sense for your bank. We’re not going to lock you into this or this or this. So I see it as a very liberating platform in that sense and it’s efficient in that sense. But it can also be scary because it is very technical.

And somebody that understands SQL, for example, that’s been doing on-prem and VI and these things forever, is going to be uncomfortable initially with this new platform and this environment. And something like a Snowflake is a little bit more term key. It is a little bit more plug and play where they’ve configured more of that for you and you don’t have to be necessarily as advanced. So those are some of the pros and cons from a trade-off perspective.

If you want to be empowered, you want to be liberated, you want to be efficient, you want to be set up with the best engine to set you up for AI, or I don’t want all that headache and I want to make it as easy as possible. I don’t want to be committed to this third party but at the same time, I only have this one person and I just need them to be able to manage this one environment. So it’s not that it’s a bad strategy to go that route, but it’s not going to give you the scale and the efficiency Because your question was around the future and it’s not going to set you up for success in the future is kind of our perspective to folks.

23:49 – Fred (Host)
No, I think that makes a lot of sense and I think that looking at that trade-off between maybe a simpler lift, a simpler path to getting your resources skilled up, is one trade-off versus the if you want to make the longer-term investment and maybe a little bit more upfront, a little bit more pain to start with, for the bigger payoff down the road, and I think I’m sure that’s something you and your team help bank sort through in that conversation all the time. So, definitely, if you have more questions, listeners please I’m sure Andrea would love it if you’d reach out and dig into that Because, like I said, as a consultant, the answer is always it depends. One other thing I want to throw yeah, absolutely one thing I want to throw in the mix that I’m sure our listeners having a big sales force focus in the audience are curious is how does Data Cloud fit into all of this?

24:43 – Manvir (Guest)
It’s a great question and full transparency. We are still in the process of understanding that and figuring that out. Quite frankly, I think there’s a lot of potential there and the idea of having something more native to your CRM, to your sales force environment and we could talk about this in the context of AI too at some point in this conversation it does give people some comfort. It gives people that makes sense, logically, right. Like, yeah, historically we know, salesforce has not been a great platform to store and manage data, right, and we, how many times have we advised clients you and I own like no, no, no, don’t borrow that stuff in a sales force because it gets expensive and all that? So it’s a paradigm shift.

But logically, people were organically moving in this direction, you know, and it’s just a platform wasn’t necessarily architected or designed for that, right, so, like, practically it makes sense. We just haven’t seen enough of what it can do to, you know, fully rationalize, not just the capabilities, but how is it going to fit into the strategy? Because they’re also inking partnerships with Snowflake and with Databricks, right, and so they are realizing that there’s going to be some limitations of like, if you’re just sort of living within that CRM world, well, there’s other enterprise systems that are have really key pieces of data as well, right, and so, going back to that data lake house concept, is this the data lake house for your CRM environment? And then you still need the broader lake house for your enterprise environment and then this particular lake house is just more optimized and more configured for your CRM type use cases like marketing, you know, is where a lot of you know what we’ve seen to date, a lot of the examples that are shown around marketing and segmentation.

So you’re going deeper into that. You know kind of CRM marketing domain. So maybe that makes more sense to you know. Have that be a part of this ecosystem? Or is it duplicate, duplicative, I don’t, you know. That’s where it’s. It’s interesting, you know, to see where it goes.

26:58 – Fred (Host)
Yeah, it is. It is interesting. It’s something I’ve been in a question of as well, and I’m not nearly the Databricks and Snowflake expert that you are kind of. Where I’ve gotten to as my, you know, default position, or where I sit on it right now, is that they’re they’re very complimentary in that I would want to use something like a Databricks or Snowflake to bring together a lot of data and potentially do and maybe this isn’t the right term, but you know some level of like pre-processing in it and you know, getting into something that’s a little bit more ingestible to something like a data cloud.

And then the data cloud’s power to me is is twofold. It’s in that execution engine where you could write those rules. You know very easily, you know to your point, not the kind of lift that you need for a Databricks. You know marketing, user, business analyst and customer strategy. You can write those rules for those activations. And then the seamless integration into all of those channels. You know if you’re a marketing cloud shop, and that’s where you’re doing your. You know your mobile studio, your email studio, you’re launching all those things like that just seems, you know, super straightforward to me and that’s again that’s you know. That’s at least where I sit with it today. But we all know right and everybody is expanding their product roadmap all the time. I’m sure Salesforce is going to be growing data cloud into some more stuff that probably sits more natively in Snowflake and Databricks today. I’m sure Databricks and Snowflake are no slashes on their product roadmap either, so it’s one of those things I think is going to keep evolving.

28:28 – Manvir (Guest)
Yeah, but I think you touched on something really important, right, it’s like it goes back to that user experience, you know, and the user you know, a lot of what goes behind Salesforce and the CRM is that it’s not for IT professionals only, right, it’s for everyday users that can go in and, you know, generate their own reports, they can create their own campaigns, they can do their own segmentation right, their own analysis, and so it does intuitively make sense that you know you would utilize data cloud as an extension of that, except, you know, a more powerful data engine at the end of the day, which, again, salesforce has an historically had. So I can definitely see how it all comes together. I think we’re just all really anxious to just see more of it out in the market and to see the next iterations of it. Right, you know, I think the announcement at Dreamforce those are exciting. I saw some good demos.

You know you get the 10,000 profiles, I think, initially now free, so they’re trying to get people out there trying it, and I think that’s another important part of this thing is, you know, earlier we were talking about how a data enterprise shift can be a big lift, right, and part of what we’re preaching and consulting on, as is Salesforce, is well, before you go do this enterprise wide and do this massive thing, why don’t we pick a use case, you know, or a specific line of business or a specific group of users, to prove how this all can work and prove the value? So I think that’s what some of the logic that went into, like well, let’s give you the first 10,000 profiles and let’s start to do some modeling. They start to utilize it. Let’s start to have a proof of value right, so that you can see how it works in this sort of controlled environment and then have more backing on the ROI because you can see how you could extrapolate that value to the rest of the enterprise. So I do like how they did that.

30:27 – Fred (Host)
Yeah, no, I like it a lot too. I was really I know I use the word lucky previous SI was that got to be involved with a couple of data cloud implementations. You know really kind of saw it from the beginning, but it was a little, you know I don’t want to say necessarily cost-prohibitive, because I actually think Salesforce made the pricing pretty attractive out of the gate, but it was a little bit kind of a prohibitive barrier to entry with you know the lift and the skills not having a lot of people that knew what data cloud was, how to use it. For a long time there was only the professional accreditation that partners could get, but if you were not in the partner environment there’s really no way that you could have gotten learning on it. Now there’s the data cloud certification, which is out in the wild and live. I love the pilot. I’m sure you’ve been having a lot of great conversations I have as well with institutions that are like, hey, let’s kick the tires on this and, to your point, let’s stand up a use case and see how this works in our broader you know kind of data and activation strategy. So I think all of that was the right move.

I’d like to transition a little bit over to AI, and one of the things I really like and sparked this, you know you coming on the episode now was I really like how you and your team are taking the approach of meeting banks where they are, because I think that and this is my opinion and you can tell me what you think executives, whether it’s, you know, c level at the board and then it rolls down are getting pressure from investors and others to say, hey, how are you answering the AI question? What do you do it? You know, show me how you’re going to pull AI in, and for a lot of banks, especially the ones that are, you know, potentially not even you know up to today, with CRM and some of the data structures we’ve talked about, it can be difficult, and what I really like is that you guys have come up with a lot of strategies to help banks answer that question. So how are you talk a little bit about how you’re meeting banks where they are on this AI question?

32:31 – Manvir (Guest)
Yeah, absolutely. It’s an exciting time and the beauty of what happened with chat, GVT and just that whole phenomena is you can have a very practical, real life conversation with the institution leader like, hey, are you using, how are you using, chat, GPT, how are you using open AI? How is your kids using it? You know how are people at the bank using it. And that way you initially remove that barrier of like, you know, demystifying. You know this Uber, you know high tech thing, and also it naturally starts to bring in the comfort level and some of the security conversations. But you know it’s such a practical thing to if you’ve used it, you know if you, the person you’re talking to, has used it, and you go well, let’s extrapolate that, because that’s what we’re doing.

All we did at Zennify is we said, hey, let’s not use it in these individual ways under wraps, let’s bring it into the fold, let’s bring it to the forefront, let’s, you know, all use it and let’s see what we can do with it. Because we see how powerful it is and so you know, we’re gaining productivity every day from it. Every day there’s some new innovation or breakthrough that we have, just as a firm utilizing, you know, the technology, and so we talk openly and practically about that with banking leaders, because it’s like you guys are having meetings with customers, right, you have to summarize those meetings and those calls and you have to then generate documents and you know you’ve got to transform those documents. You’ve got to, you know, have five different hands look at that document, and so it’s a very practical conversation and it’s a very practical way to encourage them to get started. You know, because now they’re open to like well, okay, what are the possibilities, what are the different tech options? Because that’s the other challenge is that innovation is happening so rapidly and all the big players are just announcing stuff, right and left, be it Google, be it Microsoft, you know.

Open AI, you know, and so it’s hard for them to make sense of all these things and Salesforce, right, and so part of the value we can bring folks like you and me and you know, system integrators, consultants is well, how do I make sense of all these different options, so it’s not so overwhelming, and how do we make sense of them in the context of your enterprise strategy? So if you were, for example, a very locked down, sort of Microsoft based, Azure based shop, that we have to keep that in mind as we think about our AI. And guess what? There’s options for you that will fit that your compliance officers, that your chief security officer is going to be comfortable with, right. Conversely, if you know someone is not, as let’s say, bound by that, and then there’s other things that they want to do. So I’m perfectly fine with open AI and my data like sort of going out. You know, I want the full power of the engine, right, and that’s not as frequent in financial services.

35:37 – Fred (Host)
I was going to say probably not.

35:40 – Manvir (Guest)
Yeah, but you do have those snars and you have others that are like, no, totally locked down, like I, you know, I would prefer to utilize my own information. We have a wealth of data inside this bank. We’ve been in banking for a hundred years, right, we’re a $20 billion bank. Look at how many customers we have. Like, how do we, you know, take, monetize and all that. And then so I was like you know, well, you could build your own model, and so we can. We can play in any one of these scenarios and you can make progress fast.

Going back to that POC, you know that proof of value without having to do a massive, massive infrastructure move, right, because you do it at a very small scale in a very practical way. Yeah, you might choose one or two use cases or maybe just a few users, right, and then again, you prove how this technology can be used and then eventually, you want to open it up, you know, to to the rest of the institution. But we’re in that early phase right now. And the other thing they’re worried about is like, well, the technology is changing so fast If we buy something now and it’s going to go obsolete, it’s like, well, remember, what you’re doing now is you’re just getting yourself ready, you’re getting yourself comfortable with this new powerful technology that’s out there, right, and we will make sure that we set you up in a way where you know you’re not buying some crazy proprietary thing from us or going too far down this path of building something proprietary yourself.

You know what I mean. Like like where you’re leveraging the power of some of these Googles and Microsoft’s, like would you do it in a very like cost effective way, you know where, where you can pilot something and you can get a sense of how much is that going to cost? You know what I mean, like okay, how do I scale and ramp that? So that’s kind of the the mode that we’re in with institutions. There are, you know, some more sophisticated use cases that are popping up, like people that want underwriting engines. You know, like I, I I want to reduce the time it takes to approve this small business from X number of days to this number of days. It’s a lot more complex, and so I think there’s we have to be careful, because I think there’s going to be companies out there that develop that, build that, and Sino might even build that out.

38:00 – Fred (Host)
Right, I would be. I would be very surprised if they queue to a number of other load origination systems are not already thinking along those lines.

38:09 – Manvir (Guest)
Absolutely so. So even we have to be careful with like this is innovation that we’re driving and I’ve got incredible technical people that love to build, that can build these amazing things. But we have to be careful with how far we go. We were almost about to build co-pilot for Salesforce before Salesforce announced it.

And my guys are brilliant, you know, like, like they just go and they want to go, like, oh yeah, this could sit on, sit here inside of Salesforce and it would, you know, do all these amazing things inside of Salesforce. And I was like, wait, just wait, wait a little bit, let’s see what happens. And then you know, lo and behold, you see the Dreamforce announcement. So you got to be, you know, you got to be a little careful with how far you go with it, because I think a lot of that automation is going to come with Salesforce. I think they’re going to do really well in this space because it just goes back to that logical progression. Like today it takes five, six, seven steps and I’m in my CRM in Salesforce and a while you just automated it so that it can happen behind the scene and I just have to hit, approve.

All that innovation is all that productivity is coming Like next year is going to be bananas, right With what people are going to be able to do. In fact, they’re going to be like wait. Why did we just spend all this time working with this SI on developing all this configuration? You know, all these flows or even code, when all of a sudden it can be automated right? Those are going to be interesting conversations when the time comes.

39:39 – Fred (Host)
No, I agree, and I think that there’s definitely a real.

Well, I’ll say this I think the value I mean the way that I would answer that question as somebody that anticipates being asked that at some point in the future is you know you still need the help in asking the right question, right? I think a lot of the time is you know, where the real value is in consulting is not in, you know, building the and I’m not taking you to think away from the technical aspects of it, right, but it’s in making sure you’re building the flow you need, right. It’s in making sure you’re automating it the right way, and I still think there’s a ton of value in that. But to go back, like you’ve alluded to a couple you mentioned, you know, kind of meeting notes and summaries and that’s. I think that’s a great basic use case. You mentioned some more advanced things around underwriting, but what are like, what are you, what are you talking to banks Like? What are the use cases that you’re pushing? What are the use cases that they’re excited about? That maybe some of our listeners haven’t considered.

40:40 – Manvir (Guest)
Yeah, I think a big one is just around. It’s in the more complex engagements that financial institutions have to do, where, you know, there’s a lot more thought and qualification and profiling that have to go into the approval or to the final plan. In the wealth world, the final plan that gets created for your customer from an advisory standpoint or for a commercial lending customer, the all the information that’s gotta come together, that you know it’s gotta go past underwriting, right. So even though you might have an AI approval engine that approved it based on X, y, z, there’s still some documentation that you need from a compliance standpoint. There’s just a lot of document, doc gen. That happens in the financial world, right, and so that’s where a lot of exciting conversations are happening is like how do I automate that process? Because there’s so much back office involved, there’s so many handoffs and reviewers and manual things happening. Yet the use case, that profile, that type of customer we’ve lended to that type of customer like 16,000 times. Why are we treating this as if we’re doing it for the first time? You know what I mean. So that’s really exciting in that space.

The other thing is just the idea of you know, we haven’t talked about Slack right. But you know the idea within the collaboration world. You know you think about conversations that are happening on teams. A lot of our institutions use teams and there’s just you know you step out of the office for a couple of days and you come back and you’ve got this whole chain of a thread that’s going around a really important topic or a really important client or whatever it is, and I’ve gotta like go back through and sift through all that. I mean that is a powerful innovation that Salesforce will be delivering with their next generation of Slack. It’s gonna be able to summarize those things and even take action. You know from Slack right. So all of a sudden, when I’m talking to Microsoft Teams users, you know I’m actually getting them to seriously consider Slack, because it’s hard to get them off Teams, because you know there’s pricing there and Microsoft it’s it’s hard to beat free.

42:55 – Fred (Host)
It’s hard to beat free. Slack is way better. I mean, I just and I’m a I have you know this or that I’m a Slack community group leader, so I’m obviously a big Slack fan. But if you try to compete as just a Teams alternative, it’s hard to beat free.

43:11 – Manvir (Guest)
It’s hard to beat free, so you have to bring value. All of a sudden there’s some incredible value that you can generate out of Slack because of the AI engine is gonna be working. You know, even in our world today, like you know, I’m sure you get this all the time with all the SIs you know somebody asks the question like, hey, has anybody ever integrated such and such within Compass? Right? And then you got to like there’s all these people that are chiming in and then you’re gonna go to information storage. You know whether you’re using Google or SharePoint, whatever it is, you go sit through documents and it’s like well, with Slack, you ask that question and if you’ve set it all up properly, it brings you the answer Right, it sits through all that stuff for you, brings you the answer, summarizes it, brings you to the channel, summarizes the answer.

So there’s some examples like that that people are like really, really excited about the call center environment. The obvious one is like some of the chatbots, and you know we heard from PenFed at TrainForce. You know a lot of the innovation they’re doing. But even you know just the back office management of all of those interactions that come in an inbound motion, whether it’s on the phone, whether it’s on the web, right? Whether it’s in chats, like that’s great that the bot listened to that but then the summarization of it and then what do I do next?

Right, like that was specifically an inquiry about a, you know, retail lending product, right? So like I’ve got like 36 of these I have to sit through you know what I mean by the end of the day and I’m not gonna get to them until the end of the week. So all of a sudden, I had a hot inquiry coming in that I you know I couldn’t even discern between that hot one and this one. That was kind of mediocre. I’m like sitting here one by one responding to. So there’s a lot about a nation.

45:02 – Fred (Host)
And how much time does it take to make that sort versus? You know, sending it through AI totally.

45:08 – Manvir (Guest)
That’s right.

45:09 – Fred (Host)
And I think that’s it’s also one of those like low it’s a low risk, right? Like if you’ve got 30 things to sort through and prioritize and you know you’re gonna get to all of them but which one’s more important, you know that’s a low risk versus I’m just gonna hand my underwriting decision over to an engine and let it go. So I like the idea of helping a bank that is maybe a little bit more risk averse. Pick some of those. You know lower risk, that if there is a hallucination it’s not necessarily that big of a loss.

45:39 – Manvir (Guest)
Yeah, it’s not necessarily customer facing yet, like it’s still kind of back office behind the scene and there’s still a reviewer and a prover, ultimately, of what the AI engine deemed the conclusion to be right, and so you’re kind of doing this very iteratively and then you might build confidence over time. So you know what the AI is pretty darn good. It should just auto generate the case from here on out. Like I don’t even wanna approve the creation of the case, I just want it to go, because we have enough history here that’s showing that it really knows what it’s doing. And for the ones that it doesn’t know, it’s putting them in this other queue that need triaging right. So, but I’ve taken that queue from like 50,000 a week to like 500 a week. You know what I mean. So that’s all really interesting, exciting.

Another use case that’s interesting too is think of turnover that happens Like. Think of the mortgage industry, you know, and loan officers, and the turnover that happens where you’ve got a lot of applications in flight or you’ve got leads, you’ve got prospects, and you’re turning over that territory to a new LO, right, and it’s like man sure, my manager told me like these ones were hot, but like how do I, you know, prioritize and you know figure out where to start. And it’d be sweet if these could just be summarized for me so that I can. How do I get right in Exactly? So I think there’s a lot of productivity that you know. We could go on and on. If you and I sat on this call for another like two hours, we’d probably come up with like 50 more use cases, you know.

47:18 – Fred (Host)
Absolutely. I think those were all fantastic, though One of the things and I think you’re primarily a G Suite user around email, as am I. Most of my boxes are G Suite, but I do have one Microsoft 365 box and I this morning this is the first time I saw it. I hadn’t looked at the thing since, you know, sometime yesterday afternoon. I put it up this morning trying to, you know, just want to kind of go through. I had about 25 or 30 emails in there and there’s a little notice at the bottom of my Outlook app on my iPhone. That said, do you want us to read you a summary of your email so you can get caught up? I was like wow, I was. I was kind of first time I saw it. I don’t know if that’s been out there for a while and I’ve just missed it, but it’s like everybody’s doing these innovations kind of all the time. So it is a lot. It is a lot to keep up with.

48:12 – Manvir (Guest)
Think about the Microsoft suite of apps. You know Excel, you know PowerPoint, you know all those applications. They’re introducing their own co-pilot right. That will sit across a lot of those things and, like, the automation that’s going to be able to drive for people is going to be incredible, and Google’s going to do the same. Everyone’s going to do the same thing within their application environment, which is why you got to be careful with how far you go with something proprietary. You got to really draw the line Like where do you, where do you, you know, where do we, as system integrators and consultants, draw the line like, as you’re going deep within an app, our value should be across, maybe all those different solutions, you know where those things intersect or how you use what when, and be able to advise on that. I think and it’s changing, like to your point, it’s changing very fast because there’s new innovations coming out. That’s what’s going to make our industry incredibly exciting for the next several years.

49:13 – Fred (Host)
It is. It’s funny. I had talked to a lot of people I mean, you and I have been in the ecosystem for a while over the last couple of years that were like, oh you know, kind of tired of Salesforce. I want to do something different, I want to change. You know, it’s not, it’s not a challenge anymore, and I think this is that wake up where you know, hey, there, things are about to get. You know, really fast, really fast, you know, and to me, it’s one of the most exciting times to be to be working on this kind of stuff.

I’m curious and we’ve alluded to it a couple of times one of the things that I think Salesforce has done really, really well and it’s kind of two things in one with how they’ve done generative AI is number one. They are focused on not necessarily being the engine, not necessarily being the model, but just putting the you know, access points inside Salesforce where you can bring your own model, whatever you pick. And the other thing is that whole trust and safety layer around it. Right, you know so when you but I’m curious, you’re having a lot of these conversations In some cases you’re using Salesforce stuff, in some cases you’re using, you know, other technologies. How are you navigating those conversations, whether it’s with the business or with info security or with compliance around you know? How are we sure that this data is safe? How are we sure nobody’s going to steal our secret sauce as we’re using these AI tools?

50:40 – Manvir (Guest)
Yeah, it’s a great question and you know it’s going to be an ongoing dynamic conversation, but I think for us and we touched on this earlier it’s like at the bare minimum. You know, the general feedback is like hey, you know, customer information can’t go out, you need the masking right and I don’t want others to monetize off of my data, right? So the good news is that doesn’t mean that you have to build your own model then and not get the true power of open AI and all the data that’s out there, right? Because now you do have this trust layer that Salesforce has developed. And CIOs you know they’re not there yet, but Salesforce has kept them in mind as the key persona they need to convince, you know, as part of these discussions.

And then Microsoft with their solution, their Azure GPT you know they just carry this inherent security with CIOs in our financial institution world, right, it’s like oh, it’s Microsoft, I’m good, I feel great. You know what I mean, and so I think it’s you have to be able to understand the different options that are available and how the financial institution historically operates and what their comfort levels are going to be. I mean, look, you and I have worked on clients where it’s like you can only use our laptop, right, and you got to go through our VPN, and so guess what? They’re going to be very uncomfortable with you know, just loading, you know, open AI on, like all these machines, like it’s going to have to go through a whole different protocol. But the good news is that technology is there, it’s available Now.

Is it going to get hacked and is this going to happen? Is that going to happen? I can’t insure against that, because you know there’s, unfortunately, there is a evil and dark market people out there that will see this as an opportunity to innovate themselves, right, like, how do I hack into that now? How do I get into this? And so it’s good. I don’t think it’s. I think it were early is what it is, you know, and so it’s going to be interesting to see how that conversation evolves. Another reason why it’s starting small is is maybe a good way to go right now, right, you know, starting with few use cases, seeing how it goes, and then think about what it means to the enterprise, right?

53:04 – Fred (Host)
Yeah, no, I think I think you’re absolutely spot on there. It’s early days. I think that you know a lot of institutions at least some of the ones I’ve talked to are kind of punting on it or, you know, doing something small, but you know, kind of holding off and making big decisions. But for those ones that are that are, you know, really wanted to push the envelope and start to adopt AI in greater ways, to your point, there are tools out there, there are ways to make sure that you’re, you know, doing everything you can and I’ll say this at the very, at the very least, like with tools like masking and and other kind of preprocessing stuff, you can do a pretty good job of making sure nothing sensitive leaves your firewall. Now to your point. You know, is there stuff that’s not sensitive that maybe you wouldn’t want open AI to bake into their model or whatever? Right, you mean? So that there’s, there’s things like that that are that are always going to be a potential risk? Right, that’s, right, that’s right, absolutely.

So, yeah, this has been a great conversation. I know we’re almost out of time. I’ll ask a question that you probably can’t answer very quickly, but I’ll ask for kind of your quick take on it. If you’re a bank that is just starting on on AI, what would you be thinking about, like what’s your top three things that you tell them? You know to get right out of the gate.

54:18 – Manvir (Guest)
Yeah, I think the the first thing I’d I’d want to do is again make sure I understand the different options and what the implications are as far as the capabilities that particular option provides and the security. I think that’s a. That is a starter conversation that has to happen right, and everyone’s got to feel aligned around that right, including the chief security officer, all those folks. Now I think the next step that’s really important is, again, it’s starting to inventory use cases and pain points and challenges where you know something is taking way too long or way too much manual labor, and so you, we uncover a lot of those as part of our you know discoveries. When we do a Salesforce rollout, for example, right, and that’s a. That’s another great way to do. It is well, rather than it be its own thing over here. You know that’s separate from everything else.

Let’s go back and look at those user stories and some of the pain points that we had already uncovered, and so picking the right use cases is a really important step, because if you pick something that’s too grandiose or has way too many data dependencies, right, that that and you don’t have your data strategy right Going back to our earlier conversation then my concern is that your proof of value for that initial project you do is not gonna come into fruition or it’s not gonna be able to scale. So you wanna pick use cases that you, we think are pretty solvable, they’re valuable but they’re solvable. And there is line of sight to like how it could scale. And right, we didn’t, we didn’t just do it in this like project environment, and then there’s no way we can scale it because I’d have to have an integration between that system, this system, and I need my data lake house. You know what I mean. But conversely, conversely, it does create a catalyst to have that data lake house conversation too, right?

56:16 – Fred (Host)
Some of those bigger changes. It can definitely light a fire.

56:20 – Manvir (Guest)
That’s right. That’s right. That’s my, that’s my take on it is you want to be able to go back to the CEO, you know, or the line of business leaders and say, look, this is how much time it was taking before and how much in resources and this is what we can do with it, you know now. And so there’s productivity, there’s real value that the business leaders sees. And financial, look, it’s going to be a tough market, we know it. It’s not getting really better. In banking, you know interest rates, you know.

There, I saw announcements of layoffs today or yesterday from several institutions. I think we’re going to see more of that. Right, I think we’re going to see profits are shrinking. I think revenues be shrinking, so people are going to be looking for opportunities to either find more business right or cut costs, and AI can play in both of those worlds, you know, and it can accelerate your realization to that value. It can actually help with adoption too, by the way, you know, like when Salesforce launches the stuff they’re about to launch in February. Talk about like, because you know how it is. The product owner or the executive stakeholder over the CRM is always looking for how do I win people over? Because I have to get them into the system now and they’ve got to log all their opportunities and all these things. If you can do that in a way where, all of a sudden, they see some incredible productivity, that’s going to be really amazing Any time you can give them a what’s in it.

57:52 – Fred (Host)
for me, this is not just a big brother or just not a reporting tool, but I’m getting something to make my life easier. That’s the easiest way to get adoption.

58:04 – Manvir (Guest)
It is. I think that’s what we’re going to get to do, absolutely. We’re going to get to be a part of that, which is why I think the next two years is going to be incredible in this space.

58:14 – Fred (Host)
It is going to be incredible in this space. Well, I thank you. This has been a phenomenal conversation and I look forward to continuing to work in the ecosystem closely together with you and your team over the next couple of years. Like you said, there’s a lot of exciting stuff coming up. We’ll put your LinkedIn and stuff in the show notes Anything else, any other way that our listeners can reach out and find you if they’re interested in connecting or learning more.

58:39 – Manvir (Guest)
LinkedIn’s great Genifycom. We’re pretty easy to find and I love this stuff, so I encourage people to reach out and just have conversations. So thank you for having me. It was a pleasure.

58:52 – Fred (Host)
Pleasure was all mine. Thank you, have a great rest of your day.

58:55 – Manvir (Guest)
OK, my friend, Take care you too, and welcome back.

59:05 – Fred (Host)
Really excited to be joined by Eric and Josh again this week for our Quick Takes Roundtable. So the first thing I wanted to bring up and it’s a topic that I was hoping to get to last time around, but I think it’s still in the news is that after earlier this year, all the layoffs we heard from, obviously, salesforce, meta, some of the other big ones now they’re ramping hiring back up again and I’ve definitely had some people in my network reach out. I’m sure you guys have as well. What should you do if you’re being asked to boomerang? Should you go back? Josh thoughts.

59:40 – Josh (Co-host)
Yeah, look, I mean, that’s an individual, independent decision based on each person’s situation. I read the article and it sounds like there’s a lot of sentiment out there about people feeling like, well, they say they’re Hanai, didn’t feel like I was treated like family, or they’re frustrated or disappointed or hurt. Where’s the security? It’s like where’s the security? What are you talking about? What are you talking about? Security in a tech company during a down market? What are you talking about? I just think it’s so, I’m going to say it. I think it’s just ridiculous.

Some of the things that I read about and I’ve heard it from individuals too it’s like listen, did Salesforce hit all the marks? I’m just using Salesforce as an example. Did they do everything right? Well, no, but is there any perfect, right way to do it? Ever Not really. You know, when, compared to all of these other big tech companies they were among, for a huge company with that much market presence, they’re not efficient. Their margins weren’t good, and I don’t know about you, but I don’t want my family, my ohana, to die because I made some bad decisions. And guess what they did? They overhired 27,000 people that year and I believe most of the people that were let go were first year people.

01:01:08 – Fred (Host)
I’m not sure. I know that I heard a lot of big mix of people. But at the end of the day, to your point you look at your employee count you’ve got to make the best decision for the whole company. Yeah, some people get left out of the cold and I get the sentiment around not feeling like a ohana. At the same time, I’ve never been the person that thinks that like business is really family doesn’t mean that you don’t treat your employees fairly, right, but when the going gets tough, I’m not putting my kid out on the street, but when the going gets tough, sometimes you have to make those kinds of decisions when it comes to employers and that’s why I think those two things are very different.

01:01:48 – Josh (Co-host)
Yeah, I’ll tell you. I talked to a guy yesterday who’s in the enterprise success management for Salesforce and we were chatting a little bit about how the people in his department were let go and it was literally like region number. It’s not like the people that they were actually reporting to you had a say in it. So maybe there were some mistakes, but what I can say is that they’re thriving right now. So should you go back? Yeah, if they offer you a good job back and you liked working there, you should have definitely go back. That’s my short answer.

Okay, if you had problems with your manager, if you’re onto better pastors, then stick with that. If you like your company more where you are right now, if you did land a job and it’s a good culture but it doesn’t pay as well, I would keep the job that you have because you’re going to have a better life. But if you’re not working, go back. If you want to try and renegotiate something, go back for more money. Feel free to do that. Just understand. A lot of the people who had been there for 15 years or 10 years and were making over 300 grand were the ones who were let go because they were on this graph making too much per their region. So that’s just the more money you make, the more risk you have at losing that job. That’s just a fact.

01:03:04 – Fred (Host)
That’s what Biggie said no money will pros.

01:03:07 – Josh (Co-host)
Yeah, exactly, right. So anyway, those are my thoughts. Go back if you want to, but don’t feel butthurt that you got laid off. That’s just a business thing.

01:03:14 – Eric (Co-host)
Right, right. The other side of this, on the community bank side, where they typically like to have that family Ohana type environment, when they had everybody coming back into the office after COVID was over, there were certain areas that maybe didn’t feel and probably didn’t need to come back. They weren’t customer facing jobs that needed to be in the office. They could work remotely. And I know of a couple of community banks in small rural areas that had talented people in the marketing or maybe even on the data side that got used to working from home. Or maybe they decided they wanted to live in a more exciting area and I don’t want to live in rural Michigan, a po-dong town, but it’s a good career, but I’d like to maybe move up to Grand Rapids or I’d like to move to Chicago or someplace and some of these community banks said, no, you got to be here. And they said, all right, fine. And then they left and they realized that they’re not getting people of the caliber to be digitally innovative and what they needed on the marketing side or the digital side or the IT side and they’re having I don’t know if it’s technically a boomerang because maybe they weren’t laid off, they just chose to disappear and say I’m going to go someplace else. Then If I can’t work for you, I’m going to go someplace else find a job.

They’ve actually reached back out to some of these individuals and said hey, arvad, would you reconsider? I think we are open to this work from home work, remote work, from wherever approach. It’s different than the culture we’re used to. So we’re going to need you to work with us and maybe you can come in maybe once or twice a month to see us, as opposed to being here three or four times a week.

And they’re starting to bring some of those people back because they did like working in the community bank environment. They did like the benefit that they are a part of in helping the community prosper and businesses grow and people achieve their dreams and reach their financial goals. But they just didn’t want to have to still live in Podunk, usa or wherever that’s at, and realize that you didn’t have to be there. So it’s a little different take on this, but when I read the article it made me think of that that you may need to, especially as you’re looking to and I know it’s on one of our agenda items that we can get to it but leveraging and understanding AI and digital transformation. Those aren’t people that are going to likely be interested in living in a smaller community, because there’s not the other stuff that attracts that typical type of demographic.

01:05:56 – Fred (Host)
So yeah, yeah, no, totally I know, I think, yeah, I think all good at all great points. I mean, if you are really thinking about going back, right, like you have an advantage that you’ve worked there before, so you kind of know what you’re signing up for, right, in the instance of, like Meta and Salesforce, I still I mean, I’m on LinkedIn every day. I see a lot of people in their headlines that say X, meta, x, salesforce. I mean, they’re still good names to have on your resume. I wouldn’t hesitate to go back. If that’s something that I enjoyed the first time I was around On the community bank side. I couldn’t agree more.

And I think employers of all sizes are going to have to think about like national hiring pools. Right, the days of being able to hire people that are just in your backyard, especially if you’re in a rural community you’re just not going to find the talent you want. You’re going to have to look. You’re going to have to look everywhere. And something that wasn’t really on the agenda, but something I feel pretty passionate about I wonder how much longer and I’ve never thought they were particularly good idea until, like, regional pay bans are gone, the whole idea that I’m doing a job but I’m sitting in Manhattan and I should get 50% more than somebody is doing the same job sitting in Nashville. We’re sitting in Podunk, michigan. I think those days are numbered as well.

01:07:18 – Josh (Co-host)
Yeah, well, it’s happening through choice is what’s happening right now? Right, I mean, the people just decide we can get someone else who’s better for less. We just don’t get to like stand next to them at the water cooler, right, that’s it, and I’m not. I’m running a search right now in Toledo for several Salesforce positions. We’ve got a bunch of people. Ideally, the company wants people, they want people. Yeah, they want people there at the company. I totally get it Like if I was them, I would want that too. They’re in the trades. It makes sense. But how many people are advanced admins with field service in Toledo? None, the answer is none. The answer like that’s the answer.

01:08:01 – Fred (Host)
Or if they are, they already have something. It’s a hard enough role to find anyway.

01:08:06 – Josh (Co-host)
Well, if they do, it’s because they’re working remote for another company, so it’s not like they’re going to want to give up that remote job that they have so that they can drive to work. So yeah, that’s a real issue.

01:08:17 – Fred (Host)
Cool. Well, when we jump forward, since Eric teased it a little bit in his last response, I read an article over the weekend I thought it was really interesting from an American banker. Not surprising that, with all the excitement around AI that banks have, many banks aren’t actually using it. And again, I say I think the article talks a lot about some of the more newer generative AI use cases. I mean banks are using if you think about AI more broadly, like machine learning and that kind of stuff been using it for years, but I think banks are being a little more cautious. You know, eric, what are you saying? I know you talk to banks every day about this stuff.

01:08:56 – Eric (Co-host)
Yeah, I was on the road last week for some marketing forums and one of the forums when I do those for the state associations I asked the marketing directors what are you interested in? What do you want to talk about? And one of the first things that came back from one of the folks was AI. So we had a lot of conversation about that. Of course, pi from our last Quick Takes came up and reintroduced her and everybody looked at each other like that’s really cool, that’s really creepy, and told the story of mental wellness and counseling and they thought that was pretty cool. But the other group that I had of bankers didn’t mention it at all and I brought even in the agenda from the prior day and showed them what was there and nobody really said anything. And so I brought it up because I think that it’s something, at least from a marketers perspective, because that was the audience that they need to be cognizant of and aware of because of the ways that it can change the business.

Imagine if you’re we’re not going to use email when email came around because it had risks of viruses and downloadable stuff that you could use to infect your computer or reputational risk. But there were still a handful of banks represented that said we can’t use it, it’s blocked. They just shut the door and said, no, we’re not going to use it. And now I don’t know if that’s a temporary. We blocked it until we do a risk based approach. Should we figure out how we can mitigate against that? Or if they’re just putting their heads in the sand and saying, nope, we’re not going to use it, it’s not us, we’re not going to use it? Yeah, just one way when Microsoft rolls out co-pilot and that is available through Office 365. I think that’s going to be a big game changer because they’ll be able to play with AI in a Microsoft environment that they feel comfortable with. But until that happens, getting into cloud or pie or open AI, chat, gpt, it’s going to be, I think, hard for some banks that have an embrace technology.

01:11:00 – Josh (Co-host)
Yeah, they need some sort of a closed system. I would think, to begin with, just letting employees drop stuff from their computers that might potentially have some sort of information in it is definitely a risk. I don’t have a lot of experience, of course, in banking, but I have seen this before where companies are like nope, no GPT, no AI, no generative this, no chat box. And fair enough, because even Microsoft has screwed up with some of their AI stuff. They got their wrist slapped about 10 days ago pretty hard on some things, so I don’t even remember exactly what it was, but they had to be like pump the brakes. This is too much, and all it has to do is go really wrong really quickly for one second and they could find themselves in a world of hurt and possibly even having to be shut down. So I think it’s fair and makes sense until people have their heads wrapped around this a little bit more, just doing low risk.

01:11:59 – Fred (Host)
Yeah, I think it’s interesting. I mean, two things come to mind. One is, eric, your vision of co-pilot I think is interesting and certainly will nudge more people that direction. I think that and I’m not a big Microsoft guy I do have one Outlook 365 email account that I interact with and I have noticed increasingly over the last two weeks and I first noticed it two weeks ago or so it was a Friday, it’s been a week and a half ago that when I opened up my Outlook 365 on my phone first thing in the morning and I had like 20 unread messages, I had a little note on the bottom that said would you like Outlook to read you a summary of your 20 messages? Obviously, that’s an AI powered function. I never asked for it to be turned on. And then I had another one and I guess this happened. This has been on for a while on the Google side, but I noticed Outlook is now doing generative email completion suggestions. So I started a sentence and it’ll suggest what I might want to finish saying for the rest of the sentence, and I see some of these features coming out more and more. So I think there’s going to be some accidentally falling back where it’s into using AI.

But I think, though, even beyond, at the point of customer engagement, or bankers using Clotter or ChatTPT, I think it’s some of those broader use cases.

I think of a commercial banker and you guys don’t have the benefit of this, but the interview segment that is airing alongside this was with Manvir from Zennify.

We talked all about AI use cases in banks. Like, if I’m a commercial banker and I’m getting ready to go out for the afternoon to visit two or three of my clients in the field, I would love AI to go through those records in my CRM and in my banking system and give me a summary Like, hey, and then maybe pull in something from S&P to say, hey, you’re going to go visit this manufacturer first and here’s what’s going on in their industry trend-wise, and here’s what’s going on with them specifically, so you could walk in more prepared and then go to the next one. So I think that part of it is helping banks identify what’s AI good for, because I think sometimes hard especially for bankers that have been in the game for a while to look at some of the silly stuff that ChatTPT does, or Dolly, or some of the generative stuff, and try to apply it to what is actually useful for the bank.

01:14:31 – Eric (Co-host)
So Ron Shublin over at Cornerstone. He also writes for Forbes. He had a post. He was at Money 2020 in Vegas last week and did a really good breakdown of the stuff that he saw, and I’m going to read an excerpt from his post. In addition to, there’s really no real vendors or no big vendors related to crypto, which was all the rage last year, of course, because we didn’t have anything like ChatGBT on the horizon.

But he said if you had asked me before the conference what would be hot in the exhibit hall this year, I would have said AI in your face. 24, seven. Nope, it’s important folks. Tech firms are telling the world they’ve embedded integrated AI into their offerings, but they’re not showing in all caps it at conferences. My BS detector is in the red and anybody that knows Ron knows he’s got a really good BS detector and he’s not afraid to turn around and tell people when it’s going off. And so I also think that, while certainly looking at vendors that are out there to help banks embrace AI, I think you really need to go back and turn on your own BS detector to figure out okay, well, what is it that you’re really doing with AI and explain to me the use case about how it makes your process different, better, more efficient, more accurate, whatever the promise of value is. So I don’t know.

01:16:04 – Fred (Host)
I agree and I’ll say this like if I were on the product side you vendor product side for, you know, and my market was predominantly or exclusively banks I would be very cautious right now.

You know banks have not yet signaled what they’re interested in adopting and not adopting AI.

For there’s a lot of places you can run up against regulatory issues, you know, in using AI for things, you know, regulators haven’t really weighed in on where they would want to see, you know, and not see AI play a role in bank decision making. And if I’m investing, you know, millions, hundreds of thousands to millions of dollars in product enhancements only to have nobody want to buy it or only to have the regulator to say, hey, this is, this is not kosher, I would, I would absolutely like I’m not saying I’m not an an an an integrist person I am but I would absolutely be tempted to go to a conference and say, oh, yeah, we’re, we’re on the forefront of AI. We’ve got a lot of stuff, you know, on the roadmap, here it comes. But I’d be hard pressed to like, make a hard, muddy decision to build AI product for for banks right now, but I think it’s different for the bank themselves, like I think banks should be playing around and having these conversations and figuring out how to, how to do some of the stuff themselves internally.

01:17:24 – Josh (Co-host)
Do you think there’s a leader right now in banking, either in community banking or in big banking or or finance in general? That is is actually kind of paving the road right now.

01:17:37 – Eric (Co-host)
I would say, and I don’t know about paving the road, but I think Chris Nichols over at South State Bank is a very just, well followed thought leader on LinkedIn, obviously South State being a correspondent.

Their target market is banks and Chris has been very vocal about what South State is doing and they’ve always been at the at the forefront, just testing and figuring out business cases, whether it’s digital transformation or if it’s analytics, or if it’s chat or whatever you want to call it profitability, customer modeling and he’s posted and shared some insights of what South State has been doing in the area of generative AI and and using things not just to create content which I think is probably the easiest and the safest play for most banks is just to think about the amount of content and the educational material that you’re producing, but also understanding that the human banking expert has to be involved to ensure that it’s accurate. We don’t have hallucination going on that it is compliant and meets all the regs. But he’s posted some things that they’ve done as far as you know internal data analysis and other sorts of things and if you’re not following Chris, would strongly suggest plug into his content and see what’s going on over.

01:19:01 – Fred (Host)
I’ve tried to get him on the podcast. He so far has not accepted my invitation.

01:19:06 – Eric (Co-host)
If you know him, give him the little nudge that his buddy, eric gave him, a little name drop, and tell him. I was. Now I was going to say tell him I was dogging him, but he knows that’s not the case because I’m a big fan boy of him. But yeah, he’s. He’s definitely got a lot going on as it relates to this and is a is a brilliant mind just from an innovative banking perspective.

01:19:29 – Fred (Host)
So yeah, totally that that that he, his name and South State in general came immediately to mind, and that I mean a lot of the big boys right, like GPMC, you know it was very public about the fact that they built their own generative AI model with their own proprietary data. Goldman Sachs has as well. I know. I’ve read a lot of, a lot of reports that capital one has filed for a lot of AI patents. I’ll be honest, I’m not sure what they do Like. I haven’t seen it necessarily baked into the product, but you know, kind of outside of the, you know the super giants, I think. I think South States at the forefront.

01:20:07 – Josh (Co-host)
Hey, fred, is now a good time for me to just share with everyone real quick that you gave an amazing session at Salesforce dreaming last week.

01:20:16 – Fred (Host)
I will tell you anytime you want to say good things about me, okay.

01:20:20 – Josh (Co-host)
Well, you know I set my clock to seven PM. That’s usually when I’m talking nice about you, but here it’s a little bit earlier in the day. And, fred, it was a terrific like. I learned a ton about how AI works, how it actually works, particularly in generative AI, the three primary ways that you can go about engaging with it, how just a little bit of extra, a little bit of extra time and energy can produce significantly better results from AI, and really the value per based on the amount of time that you’re going to be spending on AI, like sort of which direction you want to go. So if you happen to get that up and posted at some point, I definitely think a lot of people will walk away with a much more clear understanding of what AI is actually doing and how it actually operates. So thanks for running that man.

01:21:09 – Eric (Co-host)
Yeah, as we’re recording this, it’s a Monday morning, so thank you for allowing me to start my week with a serious case of FOMO. I appreciate that, yeah.

01:21:18 – Fred (Host)
I’ll see what. I’ll send you the link, eric, and I’m looking for a good way to distribute it. I might just release it as a special banking on disruption, you know podcast, or post it somewhere else. I’m going to give you Josh Eddie Casey for that recording. It turned out much better than I expected it to, considering it was just my iPhone, kind of in the middle of the floor picking up the audio. So it did a pretty good job. So kudos to Tim Cook, I guess as well the folks over at Apple.

But no, I really I’ve delivered that talk or a version of it a few times and it’s amazing to me still with as many people that raise their hand in the room and say, hey, I’ve used chat, gpt or I’ve used AI and I played around with it. Like how shocked some people are when you kind of pull back the hood and say, well, here’s how it’s actually working. You know underneath and you know, I feel sometimes a little bit like that. That father that doesn’t hide the set of claws costume when they’re when they’re five year old is poking around like a little bit of like taking the magic out of the eye, but I think that the more people exactly, the more people understand how it works.

I think, though, the easier it is to make the decision to adopt and move forward, and that’s kind of why I always like to start like with a, with a baseline. So thanks for the thanks for saying something good about me.

01:22:42 – Josh (Co-host)
Well, now I don’t feel like I need to say please and thank you to it anymore too. So there’s that I still do.

01:22:47 – Eric (Co-host)
I still do. I know they’re coming for us at some point. I’m ready, I’m going to be saved.

01:22:55 – Josh (Co-host)
There’s actually a really cool little YouTube short or Tik Tok or whatever it is Musk talking about. Musk is breaking down the real plot line of Terminator and it’s. If you just Google Musk Terminator and listen to him talk about the movie, it sounds a little bit different than what we we actually thought.

01:23:18 – Fred (Host)
So, yeah, I’ll have to go.

I have to go check it out for you.

Well, you know, I don’t know if it was the real plot of Terminator or not, but I think part of it is about the interconnectivity of different systems and how you know, with AI or without AI, with interconnectivity, you have the ability to have compound effects.

One compound effect I want to talk about is open banking, and you know a bunch of new CFPB rules that are coming to effect over the next few months that are really giving a lot more power to consumers to decide who’s going to get their banking data and banks I think about half the banks that I talked to you are still coming to the realization of what kind of a gold mine they’ve been sitting on with. You know customer data, transaction data, et cetera. You know, just in time for now it’s going to be not quite the Wild West, but much more open. So I’m curious, you know I’ll start with you, eric. Like, what are the banks you’re talking to you saying about these rule changes? How are they expecting it to impact? You know their services, you know how they’re going to be more responsive to customers, or are they even kind of tracking these changes?

01:24:30 – Eric (Co-host)
Well, first off I want to give you kudos for probably one of the better segues I’ve been able to be a part of. I was like that, was like freshly shaven, like smooth, like your melon smooth. I’m really impressed. But I would say, you know to your point, reinforcing the fact, even back in the day when I was a banker, the amount of information that we collected on a mortgage app, the good old Tenno three that would go in the loan file, into the vault after the loan was closed and not use it.

01:25:03 – Fred (Host)
Never to be seen again.

01:25:05 – Eric (Co-host)
Unless unless what they want to refinance, they want to get a home equity loan, or they go past you. But other than that, there was no reason to go back in and look at any of that data. Yet on that application people I mean other than probably going to your doctor you’re not as revealed and as open as you are when you fill out a mortgage app, and all of your income, your debt, your obligations, your payments, your investments, your other financial relationships are in that, and it’s amazing that it’s taken us this long to figure out ways that we can leverage that data. And, as you guys probably have picked up, I’m a staunch advocate of the smaller community bank and the bigger banks have been data mining this, but why it hasn’t trickled down where I think a community bank can benefit even more so? Because they’re the ones that typically have more of the feeling that they know their customer, because they see them in the grocery store, they sit next to them at Little League, they go to church, kids are in the same classes.

Yet the data wasn’t something, and I don’t know why.

If it’s, I felt uncomfortable, like I don’t want to ask them because I don’t want to offend them.

We’re just glad that they did their mortgage with us and we let it go, but I think the fact that things are changing and going to make it even easier for people, compounded by the fact that I think the next generation coming up doesn’t have as much loyalty they’re going to, it’s easy for them to bounce around and they’re familiar with digital conveniences and you don’t get the.

I opened an account when I was in high school and I bought my mortgage there, and that’s why I’m going to retire. I don’t know how often that happens any longer in the financial services area. So I think financial institutions of all sizes are going to have to do this, and I know of a handful that have invested in data lakes, so they’re not relying on a file server, a Jack Henry, to be the source of data, cause getting information out of those platforms is cumbersome and expensive and just not very fun, but they’re bringing all of it into their own platform. They’re building their own sequel environments and they want to know something. They go to their own platform and get it and it’s grabbing data from across multiple different sources. But that’s probably the exception, not the norm.

01:27:30 – Josh (Co-host)
My only anecdote on this is that the CTO for five serve used to coach my kid in football. That’s all that’s like. That’s literally all the input I have on this segment.

01:27:39 – Fred (Host)
Yeah, well, you, you, you say that but, like you know, I know you’re not day to day like having conversations with the banks, but you are a day to day dealing with banks personally and you’ve got some, some, some kids that are, you know, adult, adult age, that are making some of these decisions Like what, what, what are you, what are you, what’s going into your thought, what are your thoughts and in your kids, thoughts as they’re navigating things like credit cards and loans and auto loans and mortgages. Like for me and I’ll just throw this out there I am, and the embodiment of what Eric just mentioned I have very little loyalty and very little stickiness to any financial institution, and the one that I do is mostly because if I give them a lot of my money, they give me a lot of benefits, right, like if I keep a certain amount with them, you know I get more, but it’s it’s. It’s very like gimme, right. If another bank came knocking and said, hey, move all your stuff over here, we’ll do you better, I’m probably moving.

01:28:39 – Josh (Co-host)
Yeah, I’ll tell you, I’ve got I don’t know eight accounts, 10 account, like I’ve got a lot of accounts because of the business right and personal stuff too. And switching banks. It’s a real world pain in the neck, like it’s no fun, Like I don’t like to do it. I’ve been, I was with us bank for decades and the only reason why I switched to Wells Fargo where I am now I’m not, can’t say I’m stoked about that but the only reason why I switched is cause there’s no presence for us bank here in Florida.

You know, if you go with an even smaller community style bank and you’re the kind of person who wants to move or wants to do a lot of travel or like whatever it is, it’s kind of a pain in the neck. I mean it’s fine if you want to get your little car loan from them or even do your mortgage, but beyond that I don’t know. I’ve always shied away from the smaller ones and I’ve seen the smaller ones go under too. Right, I mean that’s, that’s another thing. I mean we’ve seen plenty of, we saw plenty of that between 2008 and now and so I don’t know, I get a little bit hesitant. I’d much rather be with with with a larger bank that has broader. You know more services, broader services. But I’m also not a finance guy. I don’t read the fine print too carefully and I don’t know how that those decisions have impacted me, you know.

But the idea of going into a bank, I don’t like it, especially nowadays. I didn’t mind it back in the day, but now you go in and no one’s there, like no one’s there, you know. You want to go in and get a signature for your I can’t even tell you whatever it is. You want to go in and do you know, just take care of business. It’s like, yeah, they’re all out to lunch or come back in two hours, or I’ve got, I’ve got three meetings today so I can’t meet anyone till Wednesday and I get a lot of that. That’s not a community bank, but that’s Wells Fargo, and I mean you walk into a local bank. You remember every movie you watch someone. There’s a bank robbery. How many people are in the bank? 20? I think quite a few. Yeah, quite a few. Right, you walk into a bank. Now, not that I’m playing on robbing one. There’s definitely no one to rob in there anymore. There’s like two people in line and one person behind the tail.

01:30:47 – Fred (Host)
I will say this I think that a lot of your experience of walking into a bank and that experience of not having a lot of people there to help you is because it’s a larger bank. I have accounts at community banks and at larger banks and I think a lot of that feel is still there with the community banks that you don’t get with the larger banks because they’re making staffing decisions in entirely different ways. But I get you like I don’t want to go into a bank either, like I want to be able to go into a bank, right, I want to. When I need to go to the bank for something that I need to do in person, or maybe I just feel more comfortable or have a discussion with somebody, I want to be able to go in. I don’t want to have to go in. I want to be able to do everything that I need to do completely remotely, whether it’s open an account, whether it’s make a transfer, whether it’s whatever. It frustrates me when I deal with banks that don’t let me experience that.

01:31:46 – Eric (Co-host)
I want to revert back, josh, to your comment. You left the US Bank and went to Wells because they didn’t have much of a presence in Florida. Yet you’ve also said you hate going into a bank and when you do, the experience kind of sucks. If a community bank had the same digital capabilities as a Wells, with online applications and some of the other digital conveniences, what is it that, I guess, makes you, and, I guess, other consumers, think that a bigger bank is always going to have the better technology? Is that really the case or has it been a while?

That’s something that a lot of the banks that we work with struggle with is. In many areas, we can go toe to toe with the bigger banks and some things and some of the newer stuff with AI. Chat bots like Erica from B of A and whatnot might be a little out of the reach. There’s platforms like Glee out there that are in community banks that provide a really slick chat ecosystem that a community bank can take advantage of if they want to invest the money. So is it just the bigger bank gives you more comfort, or you’ve tried a smaller bank and it’s fallen down? I just was curious on unpacking that.

01:33:04 – Josh (Co-host)
Yeah, truthfully, I’ve never tried a smaller bank. I never have. I don’t know what it was, my dad said, my first account ever. I was in college. I got it with Wells Fargo and I got a $900 credit card. I immediately bought a new Rick and Bakker guitar, a new amplifier, and spent the rest of the money taking my roommates out for dinner and then spent a very, very, very long time at my $7 an hour wage trying to pay that off. I was just a dumb kid and so this isn’t part of the question, but something that Fred asked about.

With kids and credit cards and things like that, I’m like, yeah, you don’t need it. You do not need it. You’ve got the bank of Josh right now. Don’t set yourself up for something that is going to when you’re not working. That’s just going to add stress to your life. I mean, I’m a huge fan of zero debt and I went zero debt for a very long time and it was some of the happiest years of my life. It was awesome. No, it’s fantastic, it’s fantastic. But then you get a car loan, you get a mortgage, you get lines of credit because you’re running a million plus company and all this other stuff. It’s just like it’s going to happen.

The more I research, the more it seems like living in debt, if you do it the right way, is actually the affordable way to do it. If you look at guys like well, I must does this Rich, got poor dad guy I can’t remember his name I mean these guys are at a certain level where you can live off of debt and not pay taxes and all this other stuff. But I never really thought about community banks I did do some work with. I hired about 40 people to work for a major financial institute. They got bought by a major financial institution. They used to just be a small company that helped build out systems for credit union. I mean I had guys in there that were spending a solid year in Java just to figure out how they could begin to figure out how to solve their problems because it was so jabbed Right.

I’ve seen that part of banking which is fricking legacy, ugly, legacy, ugly. Bad right, but anytime I shop for rates I got better rates. I got better returns at big institutions. Maybe I didn’t shop enough, but I mean I don’t care about the chatbot. I want to know that my money’s secure. I want to know I can get to it. I want to know I don’t have to pay $3.50 if I want to get cash out anywhere in the country.

01:35:37 – Eric (Co-host)
Right, right, cool. I just was curious, though you did give little notes.

01:35:43 – Josh (Co-host)
Yeah, no, I do know a little bit, though, about what you’re talking about. So my uncle worked in community, but he worked in mortgages and he did a bunch of different things, but he also worked in community banking. He was supporting mostly blue collar workers, firemen with their retirement accounts and things like that. He did great. He did great. These were the folks who walk in like, hey, I don’t know much about the stuff, what these are, my goals are, what goals should I have? And they can get a live person sitting right there and they’re going to help them out and that’s something special. That’s a lot better than opening up your own TD Ameri America account and losing 10% a year, right. So I mean, I like that aspect of it. I definitely don’t feel I have that with my big box today.

01:36:30 – Eric (Co-host)

01:36:31 – Josh (Co-host)

01:36:33 – Fred (Host)
Well, and I think that at the end of the day, that’s the answer right. Many customers don’t want to compromise. They want to have safety and security, they want to have good rates, they don’t want to pay a bunch of fees and they also want like the feel of somebody’s actually knows me and helps me. And I think that’s the key. If you’re a committee bank and you want to compete, you’re showing up strong on the relationship side. You also need to show up strong in the technology and in the product you know side. You can’t just use relationship and expect it to get you over the line.

01:37:07 – Josh (Co-host)
Yeah, I had a great relationship with my banker, and or I had it for many, many years. Just text her what’s up with this Boom. She handle it right away. So I got that with US Bank, but US Bank isn’t the biggest, is it Right?

01:37:22 – Fred (Host)
So oh, they’re not small.

01:37:26 – Josh (Co-host)
They’re not small, but they’re not everywhere. They’re not here, that’s true, they’re not right, no, yeah, no, totally get that.

01:37:34 – Fred (Host)
Well, cool, well, this was awesome. This is a fantastic Monday morning right out of the gate. I’m impressed. Hopefully you guys showed up strong with the coffee. Before we wrap up, just always like to ask like anybody traveling any conferences or replace people can find you this week.

01:37:49 – Eric (Co-host)
Eric, it’s not a conference, but taking my wife to Palm Springs for a little uh vacay which would be, which would be nice, Wonderful.

I’m going to work the Eastern time zone from the Pacific time zone and get some afternoons off. But yeah, we got our link banker happy hour coming up on the ninth on LinkedIn. Anybody that like to join that, follow me on LinkedIn and join and be a part of that. And then I’m going to be remote in Wisconsin, in the Dells, for the Wisconsin bankers associations, their retail, flex and marketing summit and I’m going to get to spend a time with Allison Netzer from uh think like a brand, not like a bank one of the authors. She’s going to be our mastermind guest on the link banker and I’m going to get to interview her after she finishes her presentation on Thursday and I’m doing a session on the digital dozen 12 digital marketing strategies that we bank needs to know about. So that’s going to be a fun trip. I don’t think I’ll be enjoying very many water slides, though not this time of the year, not in the Dells.

01:38:54 – Fred (Host)
I would, I would, I would pay money to see that and put that up on the uh.

01:38:58 – Eric (Co-host)
I would post the rug burns or the uh slide burns pictures. You’d see that.

01:39:03 – Josh (Co-host)
You’re real.

01:39:04 – Eric (Co-host)
Yeah, so that’s where I’m going to be. What about you guys?

01:39:08 – Josh (Co-host)
Josh, my conference season is over. So, uh, you know I was, I was there at Florida dreaming with Fred last week gave a talk on negotiating skills. We’ve got to record it and that’s getting processed right now. Hopefully the audio comes out good enough for a podcast and possibly, if the video works out well too, we’ll do a video on the Josh force channel on YouTube. It’s just at Josh, for it’s just at Josh force.

And then, uh, we’ve got a new podcast, a live podcast, on Wednesday, so you can join us at at 530 PM, eastern 230 Pacific on X spaces for the Salesforce career show live, and we don’t have a guest on other than me. So I’m going to be over some things that I wasn’t able to come, uh, actually target in the discussion last Tuesday at dream and focus a little bit on how how you can go about having a good negotiation for your compensation or salary. So that’s going to be the topic. And then we’ve got a new podcast that’s going to be launched or not launched, but released tomorrow. And we’ve got a guest Jen is going to be joining us for, uh, well, she’s a stylist, so she talks about how to level up your career by changing how you dress. So I think that’s an interesting topic. It’s not a very long podcast but that’ll be out tomorrow at the Salesforce career on the Salesforce career show podcast.

01:40:32 – Eric (Co-host)
You don’t have to grow hair, do you?

01:40:35 – Josh (Co-host)
Uh no, you don’t have to grow hair. You don’t have to grow hair, but if you’re looking for a job and you’ve got a white beard, you should probably shape it. So that’s, that’s the truth. It’s not something that we’ve actually talked about on the show, but it is something that I have done research on. It’s a real thing.

01:40:51 – Fred (Host)
What if you’re? What if you’re looking for a job as a Santa Claus?

01:40:54 – Josh (Co-host)
Well then, it can work out quite well. There you go, you get to eat.

01:40:59 – Fred (Host)
It’s funny.

01:41:00 – Eric (Co-host)
I’m totally unemployed right now.

01:41:02 – Fred (Host)
When I first started out in financial services, my first gig was at Edward Jones. I was an advisor, I was. I was very young, I was in my twenties and I actually went out one day and I bought like some gray highlights to like put a little bit of gray in my hair. So people would think that was a little older than I was, a little more season than what you were, a little little more season than I was. And now I guess, when I’m hearing from Josh, as I got to, you know, comb some black through my, my, my gray and my beard.

01:41:32 – Josh (Co-host)
I don’t know if that beard right, just a little, I was 20. I haven’t had a good beard since then, but I grew up here when I was 20 for the same reason, because I was taking people on hot air balloon rides and they’d look at me with my baby face and be like do you, how old are you? Do you know how to do this? And I’d be like, no, just look who lightest cigarette and grow a beer and I’ll be fine. Everyone will be like, yeah, let that guy fly.

01:41:57 – Eric (Co-host)
This guy’s been around for a while. We’re good yeah.

01:42:00 – Fred (Host)
I’m fantastic. I actually don’t have any. I’ve got some travel, some business travel, like several weeks no conferences, but I am looking forward to some of the upcoming Salesforce world tours and so look forward if any of our audience will be at those. Look out for me definitely to York at a couple of the ones that are still up in the air, but that’s not till December. But anyway, gentlemen, thanks again, fantastic broadcast and look forward to seeing you guys in a couple of weeks.

01:42:24 – Josh (Co-host)
You guys are great, see you guys.

01:42:31 – Fred (Host)
Well, everyone, we hope you enjoyed episode 15 of banking on disruption. Don’t forget you can find show notes and a full transcript of the show on our website, bankingondisruptioncom. New episodes drop every other Thursday, so we’ll see you in two weeks and in the meantime, don’t forget to follow us on LinkedIn and Instagram at at banking on disruption. Until next time, this is Fred Kavanaugh, wishing you success in your digital pursuits.

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