In this episode from the Accrued series, presented by LoanPro, hosts Tedd Huff and Colton Pond sit down with Raktim Mitra, the Chief Lending Officer from Varo Bank. They dive into how AI is changing the game in financial technology, especially in fraud detection and credit services.

Raktim explains how important it is to use different types of data, like transaction data and customer behavior data, to make better credit decisions. He also talks about the role of relationship data in understanding customers and offering personalized services.

The discussion covers the challenges of serving underserved markets. Many Americans have poor credit scores or no credit history, making it hard for them to access banking services. Raktim shares how technology can help provide timely access to credit for these people.

Personalization and efficiency are key themes in the conversation. Raktim believes financial products must be tailored to meet individual needs, not just when customers sign up but throughout their entire experience. He explains how modern tech can help banks and lenders offer more personalized services, like adjusting payment dates based on customer behavior or offering installment loans for big purchases.

The hosts and Raktim also talk about the importance of following regulations in banking. Compliance with rules like KYC (Know Your Customer) and AML (Anti-Money Laundering) is crucial for safety and customer trust. Raktim points out that doing the right thing for customers often aligns with these rules.

Looking to the future, Raktim sees financial products evolving based on what customers need. He expects more companies to use advanced technology to improve how they serve customers and keep up with market demands. This episode is packed with valuable insights for anyone interested in lending, credit, and how technology is shaping the future of banking.

Tune in to learn more about these exciting topics and hear Raktim's expert advice on staying competitive in the fast-paced world of financial technology.

Key Highlights

AI Takes Over Banking!

Raktim Mitra shares how AI is used in banking today. Learn how it helps with things like credit services and fraud detection. Discover how banks use AI to understand and serve their customers better.

Unlocking Customer Secrets!

Raktim talks about the power of relationship data. Find out how banks use information from their customers to provide personalized services and make better decisions.

Cracking the Code of Credit!

Raktim explains the importance of alternative credit data. See how transaction data, customer behavior, and payroll data help make accurate credit decisions.

Banks Vs. Bad Credit!

Many Americans struggle with poor credit scores. Raktim discusses how technology can help these underserved markets get the credit they need.

The Tech Behind Your Bank!

Modern tech stacks are changing banking. Raktim shows how these systems help banks launch new products quickly and stay competitive.

Personalized Banking for All!

Raktim believes in personalization at every step. Learn how banks tailor services to meet individual customer needs, from signup to everyday interactions.

Banking Rules You Need to Know!

Compliance with banking regulations like KYC and AML is crucial. Raktim discusses how following these rules helps banks maintain safety and trust.

The Future of Financial Services!

Raktim predicts how financial products will change based on customer needs. Find out what he expects for the future of banking and lending.

Efficient Banking Explained!

Raktim talks about combining operational efficiency with customer satisfaction. See how banks can provide quick, personalized services without cutting corners.

How AI Improves Banking!

Discover how AI helps banks run simulations and analyses. Raktim explains how these tools help banks make better decisions and offer better services.

Five essential items that we dive into.

1️⃣ AI Boosts Fraud Detection!

Raktim Mitra explains how AI helps banks spot and prevent fraud. Discover how advanced tech is making banking safer for everyone.

2️⃣ Alternative Data Rocks!

Learn why Raktim Mitra thinks alternative data is a game-changer in credit decisions. See how using different data types can improve lending accuracy.

3️⃣ Serving Underserved Markets!

Raktim Mitra talks about how to help people with poor credit scores. Find out what banks can do to provide better services for everyone.

4️⃣ Modern Tech for Fast Service!

Discover how modern tech stacks help banks offer quick and efficient services. Raktim Mitra shares why staying updated with technology is crucial.

5️⃣ AI and Customer Care!

Raktim Mitra discusses how AI can make banking more personalized. Learn how banks use AI to understand and meet customer needs better.

Watch on YouTube

Links:

Raktim’s LinkedIn Profile: https://www.linkedin.com/in/raktim-mitra-125a34116

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Time Stamps:

Time Stamps:

00:21 AI and FinTech: Current Use Cases

00:54 The Importance of Alternative Data in Lending

01:46 Compliance and Customer Experience in Banking

04:07 Introduction to Raktim Mitra and His Role at Varo Bank

06:54 Trends and Innovations in the Lending Market

09:50 Addressing Underserved Markets

14:52 The Role of Alternative Credit Data

21:34 Modern Tech Stacks and Personalization

25:20 The Future of AI in Financial Services

29:01 Harnessing AI for Scenario Analysis

30:04 AI in Customer Flexibility and Automation

31:24 Proactive Customer Service with AI

32:33 Personalization in Financial Services

37:11 The Future of Credit and Lending

43:25 Navigating Regulatory Challenges

51:08 Looking Ahead: The Future of Lending

58:00 Closing Thoughts and Final RemarksThis is a Production of Diamond D3, Media

ABOUT:

Raktim Mitra: Raktim Mitra is a seasoned financial executive with over 15 years of experience in fintech and banking. As Chief Lending Officer at Varo Bank since 2022, he has played a key role in expanding the company’s lending business. His leadership in lending operations, credit risk strategy, and financial innovation spans prominent institutions like Carvana, and Goldman Sachs, where he led the decision science team for Apple Card.

Mitra’s career also includes roles at Lending Club, managing credit risk for small business and personal loans, and Discover Financial Services, leading a team handling credit lines for over 25 million cardmembers. Throughout his career, he has used data and technology to drive business growth while focusing on risk management and customer experience, earning him respect in the financial services industry.

Hosts: 

Tedd Huff: Tedd Huff is the Founder of Voalyre and DD3 Media, professional services and advisory firms focused on global payments and marketing. He is also a host and producer of Fintech Confidential.

Over the past 24 years, he has contributed to FinTech startups as an Advisory Board Member, Co-Founder, and Chief Experience Officer, providing strategic and tactical direction for Global Payments OpenEdge, Heartland Payments, Nuvei, and TSYS, among others, focusing on growth while delivering innovation, process improvements and user experience-driven value to simplify the complexity of payments.

Colton Pond: Colton Pond is a seasoned marketing executive with a strong fintech and financial services background. In his latest role, Colton is the CMO for LoanPro's API-first lending platform, aiming to meet the increasing market demands. His track record includes a significant tenure at Truv, where he led the marketing team to achieve a 300% growth in year-over-year revenue. Colton has also held key marketing and sales positions at MX, Lucid, and HealthEquity, demonstrating his ability to drive success and innovation within the fintech sector.

Diamond D3, Media: A media creation, management, and production company delivering engaging content globally

Welcome to FinTech Confidential, bringing you the people, tech, and companies

that change how you pay and get paid.

Welcome to Accrued, the FinTech Confidential series presented by LoanPro.

We actually have Rakten Mitra, the Chief Loaning Officer from Varroa Bank on.

AI, you know, kind of permeate into this space as well.

So there's a lot of use cases that have already come up around,

you know, the use of FinTech.

AI and servicing.

There's, you know, some fraud use cases.

I think soon enough, we will see more AI use cases in credit.

I recently saw a survey where I think About 45 percent of customers said

that you know, they were looking for credit Credit, which is so important and

they get denied for, you know, whether credit is, uh, it's, it's so important

to kind of think about, you know, how do you kind of serve that space?

The things that have stood up to me in terms of alternate data, it's, it's,

it's the relationship data element.

Uh, obviously cashflow, transaction data, payroll data is very important.

If you, if you just compare it with, you know, traditional bureau data in

terms of underwriting, customer behavior data is another thing that I've seen,

um, you know, reasonable success with underwriting at least for new businesses,

I mean, they have to be fast, as I said, they have to be efficient, they have to

be personalized, they, they, they need to meet the regulation and I, I just

don't know how they do that without.

Um, and if you are in kind of the financial space and the banking space,

you know, enabling, um, the ability to spend, borrow, save at minimum

is a core tenet that you have to kind of at some point in time serve.

Look, I think it's very important that there is, uh, you know, compliance with

the basics of basic elements of banking.

You're talking about KYC, AML, customer due diligence.

You know, having the right fraud controls and mechanisms.

How do you make your businesses more efficient, uh, but at the same time

don't dilute the customer experience.

And, you know, the, the important thing here is, you know, how do you,

uh, leverage technology, be it AI, be it, you know, new tech stack driven

platforms and programs to achieve that.

I wouldn't characterize it as regulation is holding us back.

Regulation, I think, is here to help us, guide us in a way where we deliver

products that set both the customers.

And the financial institution of success.

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Welcome to Accrued, the fintech confidential series presented by Loan Pro.

In this series, we're deconstructing the complexities of lending and exploring

compliance, optimization, modernization, and personalization through insightful

conversations with the industry's best.

I'm TeddHuff here with my co host Colton Pond.

We'll be guiding you through the intricate lending world.

Whether you're deep into lend tech or just intrigued by how technology is reshaping

lending, you're in the right place.

Now let's dive into another episode of Accrued.

Welcome back.

Thanks, Tedd.

I'm, I'm trying to notice your beard looks really good.

I'm trying to grow the beard as good as yours though, my friend.

So it looks awesome.

Well, I'll have to send you the link to the, to the beard stuff that I use.

I'm telling you it is fantastic, but today we're not talking about beards.

So we've all got a little bit of a beard going on.

We actually have Raktim Mitra, the Chief Lending Officer from Vero Bank

on, and man, welcome to the show.

Thank you for having me.

It's my pleasure.

Before we dive into all the fun questions, like I mentioned, we're

thrilled to have Raktim Mitra on.

He's the Chief Lending Officer of Vero Bank.

He joined the bank back in January of 2022 and has been at the forefront of

our lending initiatives, overseeing the development and implementation

of their credit products.

Now he brings a wealth of experience to this role.

Prior to joining the bank, he held significant positions at

industry giants like Lending Club, Gordon Sacks and Discover.

He's leveraging his experience by launching and scaling businesses has

been instrumental in shaping the way that Varro's lending strategy has evolved.

Now in this role, he's responsible for driving that lending business, which

also includes innovative products like Varro's Advance and their

recently launched line of credit.

His experience in financing solutions and his leadership in the lending space

makes him uniquely qualified to discuss what's going on in the marketplace and

around credit and financial inclusion.

Raktim, welcome to Accrued.

We are so excited to dive into your journey and your perspective on the

lending space and get some great insights from you on the future

of lending and digital banking.

Colton, I know you always have these really good stories and all these little,

little bit of tidbits, but I'd love for you to share with us what your experience

has been with Rock Tim and, and what got you so excited to bring him on the

show.

I mean, the, the quick TLDR is imagine talking to someone, they, they, Was

that discover during discovers crazy growth lending club in the one I've

used the heyday of lending club, right?

The early days before radius, like doing some really cool things.

I had a lot of my, my money and lending club at the time that was

through peer to peer, uh, lending.

And the innovation lending club is doing Goldman Sachs.

And don't think Goldman Sachs.

Well, I think the apple card and what they're doing with apple card and

then, uh, at borrow bank and that breadth of experience all the way

from discover to peer to peer lending to, uh, at borrow bank is a bank.

Now rock team, we're excited to dive into that breadth of experience and,

and dive deep into lending credit.

Thank you.

Thank you

for having me and thank you for the kind words.

So, we talked about all these breadth of all the different areas that you've had,

had been able to participate in, right?

Like, these aren't small things, right?

They're very well household names.

They're products that people are still using today.

I really want to understand what trends you're seeing in the current marketplace

and just from a, like a really high level perspective, how is that adjusting or

changing the current market ecosystem?

Absolutely.

I think, uh, there's, there's a lot of innovation that's happening in this

space, which is, which is, which is good.

I think of late you've seen a lot of companies and institutions Take a very

first principles approach to, you know, products in the space and, you know,

designing products, really keeping the customer pain points in mind, rather

than, you know, historically, I think how products were developed a bit

where, Hey, you know, does this product make sense from a P and L perspective,

let's, you know, find a way to like, you know, stick this to a customer

and, you know, maybe market it to them.

So that's kind of a refreshing approach.

I think what we are also seeing is, is, is a lot of personalization and

customization, which is, I think.

You know, need of the hour.

So even with existing products and services, there's a lot of

personalization that's happening, which is great for customers.

Um, and, uh, I think, uh, outside of that and, and not, you know, you're

seeing a little bit of, you know, risk management and compliance and compliance

kind of, uh, uh, discussions happen.

And, you know, there's always been some new, there's been some news recently

around, you know, uh, You know, some of the, the best kind of players

get under the radar a little bit.

Um, I think, uh, it's, it's kind of, uh, calling out that, you know, while

innovation is important and you want to continue to innovate, you also have

to keep the fundamentals, uh, right.

Get the fundamentals, right.

Um, so in general, a lot, a lot is happening.

Obviously, you know, AI is here and you're, you're starting to see AI.

Yeah.

So that's the earliest in our conversations that's come up.

So, well, well, if

you, if you, if you really ask someone like what's happening and it's, you'll

go amiss if you don't mention AI, but you actually seeing like AI, you know,

kind of permeate into this space as well.

So there's a lot of use case that have already come up around, you

know, use of AI and servicing.

There's, you know, some fraud use cases.

I think soon enough, we will see more AI.

I use cases in, in credit, which I think will, if used correctly is, is going to

be really, really good for the space.

Having said all of that, like fundamentally, I think that

the core problem still remains.

There's like millions of Americans who still don't have timely access to credit,

um, access to, you know, even like core banking services in a way that's

simple, transparent, that works for them.

Um, the good thing, as I mentioned, though, there's a

lot of innovation happening.

A lot of players are trying to address the space.

So I'm really excited to kind of see, you know, what's going on.

The one thing that you brought up that you started to hint towards, right?

And one of the things that, that I'm seeing happen a lot more is really the

focused on the underserved markets, whether that be due to a thin credit

file, or maybe it's because they've had something happen in their life.

How are you seeing the market handle that today?

Maybe with technology and maybe with the empathy piece of it.

How are you seeing those two things play together, especially for that market?

If you look at the size of that market, it's astounding, isn't it?

Um, you know, uh, there's almost 25 to 30 percent of, uh, Americans that have,

uh, what do you call a poor credit store?

Um, you know, Vantage, for example, scores, you know, 240 million Americans.

So that's like, you know, almost 60, 70 million customers you're talking about.

Um, I recently saw a survey where I think about 45 percent of customers

said that, you know, they were looking for credit, which is so important.

From, you know, managing their day to day-to-Day lives, and they get denied

for, you know, where their credit is.

Um, so it's, it's so important to kind of think about, you know, how

do you kind of serve that space.

And then this is not to mention, I think there's about, you know, 50 plus million

customers that are unscorable because they, they don't have a credit file

or, you know, they're not scoreable.

So you have to like, really think about how you, uh, you know, elevate.

Um, you're offering in a way you can, you can serve the space and this is just

talking from a credit perspective, right?

Like if you, if you pull back and, you know, think about it more fundamentally,

you know, millions of Americans don't have basic banking services that work for them.

Uh, in a way that speaks to their pain points, you know, up until recently, uh,

you know, if you look at, uh, up until 2019, uh, banks made an absurd, I think,

11 billion charging overdraft fees.

So, you know, banks are basically dinging these customers in

the moment of their need.

So not just.

The kind of products that they serve don't speak to the customers.

They're also kind of dinging, you know, these customers.

So there's a lot, a lot that needs to be kind of thought through in terms

of putting together, uh, you know, products and services that really speak

to millions of Americans, you know, helping them with their day to day lives.

And it's not easy.

It's not easy.

There's a, there's a reason that that kind of space is not served that well.

It's not easy.

Traditional.

Line of thinking, you know, will immediately tell you, like,

don't go into that space, right?

That's where, that's where I think you have to kind of have that

intent, have that mission, but then, you know, couple that with.

You know, the ability, uh, to serve that space.

And when you talk about ability, you have to have the right capabilities, the

right tech stack to serve that space.

Um, you have to be really, really efficient, uh, when it comes to your

revenue and, you know, cost trade off perspective, we cannot like wait

for, you know, multiple days to get, you know, their needs addressed.

So you have to be fast.

Um, and then.

I think you have to be, you know, personalized and that's the

name of the game today, right?

And you can't have a one size fits all strategy.

Where, uh, you know, unless you're, you're kind of personalized, you are interrupting

in some way some of these customers with, you know, key things like access to money.

And, you know, these customers traditionally don't have a

lot of money lying around.

So it's very important that, you know, you manage those

experiences in a personalized way.

So there's a, there's a lot that needs to come together.

It has to be track driven.

Uh, you have to have the intent.

In the end, you also have the right, you also have to have the

right people driving that, right?

Like marring that intent, marring that tech capability and, and creating

products and services and experiences that speak to these customers.

So, so Raktim, there's a bunch to dive into, but I want to dive into one,

one aspect of what you said, which was awesome is you said, the traditional way

of thinking does not align with this.

And I love that because I feel like for so long, oftentimes

within financial services, When you're like, why do we do this?

The answer is, Oh, cause that's how it's been done.

Um, and that's a bad answer.

If the answer is, Oh, this regulation is this way, or it's more efficient or

something else, that's a great answer.

Um, so when you think about this underserved market, thin file, no

file customers, a lot of folks in the market stay away due to two reasons.

One, fraud risk rate, which we can talk about at another time,

but directly relevant to this is credit risk because we're.

Banks and financial institutions really make money is on taking

deposits, lending those deposits and earning interest on that.

Right?

So alternative credit data has become a big thing, especially within FinTech

and looking at other data points.

We'd love to hear your perspective on where the future of

alternative credit data is going.

And also some examples you've seen from other folks using alternative

credit data well, and what that looks like and what those data points are.

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Take

a step back, right?

Like when we talk about credit underwriting, uh, you mentioned

like, you know, serving the spaces is tricky and it's challenging.

So absolutely you, you have to think about underwriting in the context

and you have to understand, you know, what's the customer, uh, you know,

base that you're serving, right.

Uh, and you know, really tailor your credit underwriting to that, but

there's the, for, for good credit underwriting, you have to fold in

multiple other elements as well.

Right along with that.

Mm-Hmm.

one, for example, is, you know, what's the product that you're

kind of thinking through?

Is it a short term cash advance loan?

Is it a credit card product?

Is it, uh, you know, a longer installment loan product?

The second I would say is, is, you know, what's the context in which

you're kind of serving the product?

Is it in the context of an established relationship?

that you have with the customer?

Is it within your ecosystem versus is it served up in more of a direct

to consumer fashion, you know, extending on that, like, how are you

acquiring or onboarding that customer?

You know, are you onboarding that customer through an, uh, through, uh,

an organic channel or are you competing in a space like, you know, credit karma

or not nerd wallet, for example, where you're competing with other offers.

For, for, uh, I'll take examples, you know, that I've been very close to.

So for a product that's delivered in a, in a relationship kind of structure,

right, where you have another sort of engagement with the customer,

leveraging that, that relationship information, that relationship data is,

is extremely important, uh, you know, in, in, in terms of credit underwriting.

Um, If, for example, that, that relationship happens to be the

customer is banking with you, um, you know, bringing in their paychecks,

like you have to look and leverage that, that data in your underwriting.

And it's, it's so important, but it goes beyond that, right?

Like when you have someone interacting, living their financial lives with

you, you get so many other signals and you have to bake in those signals.

One example I'll again give is.

You know, if a customer is raising their hand and saying, Hey, I want

to get on a path to better credit and they have enrolled into your credit

building product, for example, and they're, you know, doing the right

things and taking the right step.

That's a fascinating signal to kind of bake into your, into your underwriting,

um, you know, overall, like, look, like, Credit Bureau data is important.

It's not going anywhere.

But I think increasingly, lenders and institutions are starting to realize,

especially, uh, for a certain combination of, you know, customer based product,

how it is served up, you know, what channel are you serving through, you

know, non, uh, Non credit bureau data, alternate data is perhaps starting

to become a bigger piece of the pie.

Now, in my experience, I've looked at a bunch of data, but as I said,

I think the things that have stood up to me in terms of alternate data,

it's the relationship data element.

Obviously, cash flow, transaction data, payroll data is very important.

Um, If you, if you just compare it with, you know, traditional bureau data in terms

of underwriting, you know, you get a very early and a deeper signal versus trade

bureau data tends to be a bit lagged.

So in the context of who you're underwriting, when you're underwriting

them, that becomes very important.

Customer behavior data.

is another thing that I have seen, um, you know, reasonable

success with it underwriting.

You start using that a little bit more when it gets into fraud risk

management, but I've seen the use case, uh, in, in the credit space as well.

There's a lot of data that you just talked about, right?

And, and, and it's not like it's It's all in this one spot or it's

all in this one spot over here.

It's, it's everywhere and it's in different formats and it has

different descriptions and heck it may have the exact same label but

means something completely different.

How, how are you seeing the market navigate all of that to bring

the real time or near real time decisions you said earlier, the

near real time decisions that are.

Extra important to deliver, especially for those who need the money now,

and they need that instant access.

How are you seeing all that get pulled together?

There's been a fair amount of innovation and decisioning systems and

platforms to be able to enable that.

Like, first of all, there's recognition that.

Yes, we need all that data.

You know, some of that is point in time data.

Some of that it's longitudinal data.

Some of that is like, you know, lines and lines of like transactional data.

And you need to bring all that together from different sources to your point.

Like some of them may be in different formats and kind of also digest that in

a way that kind of, you know, goes into a final decision that is customer facing.

So I think there's recognition of that fact.

And, you know, based on that, there's a, there's, I think a ton of

innovation that's happened, happened in kind of the decision space.

And I'll give you one example, right?

Like, uh, You know, maybe, you know, five, six years ago, uh, when I used to have

conversation with, uh, you know, folks trying to build decision platforms, they

used to always like tell you that, oh, you know, we have a decision platform.

That's a no code platform.

You just can, you know, stitch together a bunch of rules and

decision tree environment.

And that's your decision.

And.

You know, I, I used to be like, like, no, that's not how you can make these

customized personalized decisions because I have to go through so much data and

to be able to digest all of the data.

Some sometimes through like models, machine learning models, whatnot,

but you know, stitch that together to a customer facing outcome.

Like we have to write code and.

It generally like that's what like financial institutions do.

They do a lot of simulations getting into it.

So I think there's a there's that switch.

I've started to see happen, right?

Like people, institutions that are building, you know, decision platforms

are now kind of taking that into account.

That like, this is the reality of what needs to be kind of achieved.

So I've kind of, I'm, I'm seeing the transition happen.

Colton, what I'm, what I'm hearing him say is like, you have to have a modern

tech stack to compete in the market.

Like that's everything that he just said.

That's really where my brain goes.

Yeah.

And it ties directly, Tedd, you're spot on.

Tyson also wrecked him to the point you're making on personalization.

I recently, I did a survey with about 80 or so bankers that I know within the

lending space and only work in banks and credit unions, I said on your current

tech stack, and most of them, I think we know what the current tech stack and

legacy infrastructure is credit unions.

I don't need to call them out, but I said, what is the average time That

it takes to launch a new product from, Hey, I want to launch a new

product to launching a new product.

Um, the average time was 22 and a half months.

So if you think about what really needs to happen, Brock Timper, what you're

talking about is you need to be nimble.

You need to be quick.

You need to launch personalized product.

Maybe it doesn't work.

You roll it back.

You try a new one.

What does that work?

Does that work?

But if you're spending 22 and a half months from beginning to end,

that product is going to work.

You're going to make sure, even if it's not working, you're going to continue

to push it because you have so much set costs that you've, you've put into that.

Right.

Right.

Right.

Absolutely.

Rectum.

I'm curious your thoughts and advice you would give to anyone out there that's on

a legacy infrastructure and experiencing those problems of the inability to launch.

New products or sliced products.

And what does that look like?

What's the advice you would give them to them to compete in a market where

you have folks that are actively

testing new things?

I'll pull back a little bit, right?

Like at the end of the day, every business is, is trying to solve a

consumer problem, consumer pain point.

Uh, you know, that means they know that the customers that they are serving

and what's the key job to be done.

Um, now if, if that key job, job to be done.

Solving that key pain point requires that they elevate themselves to a

more personalized decision, a decision that, uh, you know, uh, needs to

happen on a more rapid cadence, you know, the product evolution needs

to happen at a more rapid cadence.

I'd absolutely, you know, encourage these people to, these organizations

to think through, you know, the platform that they are on and,

you know, how they can get there.

On a modern tech stack, and it's not just about, you know, pushing products quickly.

A lot of it that you're hearing about the gaps in risk management and

inefficiencies being able to kind of test that right before you kind of.

Put put that out in the market and you can get a bunch of impact.

It's also about having the right capabilities and right governance

and controls mechanisms to, you know, get those products to the market

in a safe and sound manner in a manner that's regularly compliant.

So, I think, uh, My advice will be again, like, based on, you know, what you think

is the core pinpoint of your survey.

So solving, you know, your customer base, how you want to kind of see that journey.

Um, you have to kind of make those calls.

But to me, I think.

At least for new businesses.

I mean, they have to be fast.

As I said, they have to be efficient.

They have to be personalized.

They, they, they need to, you know, meet the regulation.

And I, I just don't know how they do that without being on a modern tech

stack where they can iterate quickly.

Uh, they can bring in the necessity complexity on the backend that

creates a smoother front end experience for the customer.

Um, and you know, they can, they can get quicker reps on,

you know, product innovation,

you mentioned.

You know, we're talking about modern tech sack and early, you,

you very early mentioned AI.

So I'm going to just kind of skip, skip a little bit over to that side real

quick, but, you know, machine learning AI, I see that as being A space for

for financial services, companies, banks, credit unions, if they do it

right to leverage that to pseudo test these products before they roll out.

Um, to look at the data that they have in their loan management

software or within their core banking software and run a bunch of models

to get a better understanding of it.

And then also, at the same time, be able to take their, their policies

and procedures that they have around the regulatory environment for all

of those things and just slam it up against the wall with that too.

And I believe, and I feel, and I'd love to get your opinion, I believe that by

using AI and machine learning to use that data to test before you go to market,

before you spend the 22 months, as Colton said, uh, To really figure out, is it

even worth spending any more time on it?

What is your perspective and your thoughts on that?

To build on that, right?

Uh, a lot of times for, you know, companies end up doing is that, you

know, running experimentations, like that's how you learn, but there's

always a cost to experimentation.

You know, sometimes it's, you know, just.

You know, the experiment itself is costly.

Sometimes it's building that experiment is costly.

So you have to be really mindful about, you know, how you run experiments.

So, and there's going to be two kinds of experiments that you run.

One is an experiment that you know has a decent chance of success.

You're just trying to, uh, estimate the scale of that success.

The second experiment, kind of experiment might be more

foundational in nature, where you're intentionally making the investment.

And, uh, To, you know, you know, gather data and learn from that experience.

But regardless, I think where AI can come in and help is, you know, before

you choose to run these experiments, for example, and I'm keeping product

launches aside for a little bit.

And I'm talking about this specific thing.

because this is what you kind of tend to do more frequently.

Um, you know, you can leverage AI to run these simulation models and

scenario analysis to kind of test the boundaries of what could be

possible with certain experiments.

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The

ton of hypothesis that people are generating, you have to distill all of

that hypothesis into a few experiments that you want to, that is really

going to, you know, you know, have a good impact on your future roadmap.

And that is where you can use a lot of, you know, the power that AI has to

run a lot of this scenario analysis, simulation analysis to really understand

like these are the bounds of what I could see through the experiment.

And then you can kind of stare at those results and say, you know, Hey, you know,

out of the 10 experiments that I thought of, like, these are really the things

that, you know, have a good chance of, you know, success, or will, you know,

help us gather data that we could really leverage to, you know, move forward.

So that immediately comes to my mind.

Of course, you know, an extension of that is, you know, if you're trying

to build a product that in my mind is a broader experiment in it on

its own, but you absolutely kind of hit the nail on the head about.

Uh, you know, people generally keep talking about how AI, uh, machine

learning can be used in, like, customer facing, uh, decisions.

And there's a use case there as well.

But on the back end, there's a, there's a big use case for AI, right?

Like you spend ton, ton of time to kind of do all this analytics

scenario analysis, like that can be done so much more efficiently.

Colton, you've brought up a bunch of times, like the importance of being

flexible with, with the, with the customers and, and how, like making a

small change, like moving a due date from the 15th to the 21st can make a huge deal.

And a lot of companies don't even, don't even look at that.

And in my mind, I was just sitting here thinking, because you bring it up.

So you bring it up Colton before, is it.

What if you were able to run that and go, Hey, this person has been, had been

late by two days, a couple of times.

What if we just moved the due date out a couple of days?

Because we're starting to see a pattern here.

And then now I go, I, I, I build that model over here.

It informs my LMS that, you know, we're going to make this adjustment,

or maybe we just send out a message to the person and say, Hey, we've noticed

this has happened a couple of times.

Would it help if we moved it by two or three days?

If yes, click here.

And when they click there, then it's You have a lot of automation in the

background and everything happens.

And I just, in my mind, as you were talking through that, Rock Tim, that's,

that's where my brain was going.

And Colton, I thank you so much, man, because you've, you've brought

it up a couple of times in past episodes that that's, that's exactly

immediately where my brain went.

Yeah.

100%.

One of the cool things, not a Lone Pro promotion, but the we're working

on, on the Lone Pro side, uh, has been an AI based servicing Nexpex action.

So how do you predict?

Right now, um, uh, folks are relatively reactive and with the

legacy infrastructure, customer calls in, I need to do X.

Oh, I can't even do X.

My platform doesn't even allow me to change a due date or to do

this, or I got to do it manually and recalculate a bunch of things

manually, and then maybe make a mistake and get in trouble with regulators.

There's a whole suite of snowball effects with.

Just legacy infrastructure.

Take that out of the equation.

How do we go from being reactive to proactive and how do we use artificial

intelligence to enable us to understand this is a subset of customers I

should reach out to with this message.

Maybe this is a subset of customers most likely to go in and in

default, but aren't in default yet.

Or this is a subset of customers that I can help in this way or

need help with this or need this.

And if you can predict that, There's some really delightful customer

experiences there that drive customer

delight.

Absolutely, and this goes back to my point around like per

personalization and customization has to be the name of the game.

Not just like at, you know, onboarding your customers, you know, putting them

through the right funnel, matching their intent with the value, but.

More importantly, as the customer is, they become your customer, right?

Like on a, on a day to day basis, as they're interacting with your

product, things like, Hey, you know, when I set up my due date, uh, it

was set up for the first, somehow I just get paid on the third.

In a sense, right?

Like you're interrupting this, the customer, this, The, for the same reason

over and over again, and that erodes trust and, you know, how delightful it

will be if you can be proactive and, you know, come up to the customer instead of

the customer calling you and saying, Hey, you know, like, please change the delay.

Like that's a delightful experience that goes over and beyond the

personalization that's kind of necessary.

Another cool example that we've had on our side, cause, uh, um, with our

recent foray over the past three or so years into credit, one of the things

we've seen with revolving credit cards.

Has been, uh, uh, customers who will monitor spend and understand generally

where they're at within the spend.

And if they go over that or are projected to go over that, they'll ping them or

reach out and say, Hey, I just saw a big expense of 5, 000 expense at Home Depot.

Would you like to roll that into an installment loan right away?

Yes, I would.

Great installment loan.

It opens up the line of credit availability for them to do

their purchases that they're generally at those types of things.

And what I love is.

So much of AI has, in my opinion, within lending credit has been

focused on underwriting origination, uh, how to do so on that side.

And.

The concerns a lot of people have are within fair lending

and the CFPB is pushing pretty aggressively on if you can't explain

it perfectly You can't use it.

It won't work.

It won't cut cut the the test for us What's awesome is that shift now that

how does AI impact loan servicing?

collections Payments, the experience post funding, I think is where

there's less focus and even potentially even a bigger gap.

All I was going to point out is that personalization isn't

putting your name on something.

Personalization isn't running you through the funnel.

I think you've both have really outlined really well that personalization is

it every single step it's everything from due dates, it's everything from

Terms it's it's using the right name.

It's it's sending it to the right email or it's sending the right text message

It is truly about Getting it personalized for that individual not in one aspect of

the journey but the entire journey and that that's something that I'm starting

to see happen more in the marketplace as people move to more modern tech stacks.

I would love to get your perspective Raktim is on how How do you

think it could be done better?

We just have to like, get reps on it.

I think these ideas are, are, you know, starting to form now.

As I think Carlton mentioned, when, you know, AI and machine learning, you

know, came about, the first thing was, let's go use this in underwriting.

Um, and, and I think the shift is now happening is that, The, the,

the better usage is in, you know, customer experience, getting that

personalization, going through tons and tons of data to really inform you

that where the customer is on their journey in their individual journey and

tailoring your experience, your front end experience, be it how you communicate,

how you, you know, offer products, elevate them to new products, like to

that individual customer's journey.

And that is where I think people are kind of, uh, getting to.

I think.

Has it been done yet?

No, um, it's, it's perhaps the North Star for a lot of companies and you know,

different companies are at different stages of kind of reaching there.

And again, you know, it's always through experimentation that

you have to kind of go there.

Uh, you also have to feed You know, these models, the right data.

So they continue making the right decisions.

So I, to me, it's, it's a process, but I think the, the thing that I'm excited

about is that recognition is there.

That intent is there.

Um, you know, and companies absolutely realize that, you know, the name of the

game has to be that personalization and customization, so they have to elevate.

I love it.

And I couldn't agree more.

Uh, Raktim, what I would love to do and what I really wanted to

do, actually, from the beginning, we just dove into so many topics.

We've talked about how to actually do it.

Let's rewind back a little bit and Think about what's happening in the

credit and and lending space right now And what i'm personally seeing is we're

seeing debit interchange shrink Uh, and in my opinion and I think generally

industry's opinion is it's only going to go to zero As pay by bank and other

payment methods come debit interchange will become relatively irrelevant

Lots of folks are saying, Oh, cool.

Let me shift your credit.

Let me go figure credit lending out and like make money with

interest in higher interchange rate within credit, uh, transactions.

Um, you have over your career successfully launched several

new lending and credit products.

So I've got a two part question, if that's okay.

One, looking back, when is the right time to say, yes, absolutely.

And how do you think about evaluating where to start and how to expand

when it comes into lending credit?

First of all, I'll say that, uh, you know, the fact that we are offering

customers and businesses, uh, more options to, Pay is absolutely fantastic.

I think the rest of the world, you know, most countries have kind of enabled

that and made significant strides.

It's great to see that, you know, things here in the U.

S.

are catching up with real time payments.

You know, FedNow, I know there's a bunch of institutions that are, you

know, pushing on this, uh, to, uh, manage, uh, payments through bank,

you know, in a kind of risk free way.

Uh, there's, there's, uh, some ground to cover here, but I think it's,

it's pointing in the right direction.

The point around, uh, being reliant on debit and, you know, uh,

having to move, uh, or focus on, you know, credit based business.

I'm not sure if most financial, uh, organizations or institutions, uh,

want to intentionally, uh, You know, build a, build a business model that's

solely reliant on one revenue stream.

It may be where they started, uh, in, but the long term kind of business, uh,

they have to, they have to think about diversifying their monetization, right?

Um, and, and if you are in kind of the financial space and the banking

space, You know, enabling, um, the ability to spend, borrow, save at

minimum is a core tenet that you have to kind of at some point in time serve.

So maybe a lot of businesses are in that phase where they're just, you

know, going from one phase to the other, um, and kind of that, that's kind of

what you're perhaps, uh, seeing, um, to your second part question about

what is the, the right time to, uh, to, to, uh, you know, uh, launch

lending and, you know, go with credit.

To me, it kind of goes back again to that fundamental, uh, the fundamental

thing that I was discussing, right?

Every business is, you know, trying to solve, you know, some customer pain point.

They have a very good idea about who is this customer base that they are serving.

Ideally, they're trying to deliver that value to the, to the customer

that the customer is seeking.

Um, and, and I've seen different businesses go about it in different ways,

uh, for, for someone like a lending club.

Uh, they identified this opportunity to help customers consolidate debt, and

they leaned in with lending and credit.

Eventually, they made the transition towards a more kind of banking space.

For example, Varo, for example, identified a more fundamental need.

As I said, you know, there's millions of Americans that, you know, did

not have access to banking services that work for them, you know.

They often got tanked in their moment of need.

So it was kind of a more fundamental buildup of let's let's offer these

customers a banking service that works for them and then if you look

at the product journey and evolution It has always gone back to There's

always gone back to the core customer need that you're trying to solve.

And if you look at it deeper, you'll always find and you'll probably more

often than not see that it's not just one product or service that

helps you address that pain point.

It's actually a bunch of things that need to come together in a

simple, transparent and logical way for it to truly help the customer.

And that You know, most businesses will be talking to

their customers about it, right?

And that's a very good way to go about it.

So, you know, when you talk to the customers, you get a good sense of, okay,

you know, where they are, what is their pain point, you know, what's the current

value prop and how do I need to elevate that value prop to meet the customer with?

with, you know, what they need to manage their day to day lives and, you know, be

along with them on the financial journey.

So I think the choice that you make in terms of what you lead with and

then, you know, how you evolve your product is, is really based on that.

I've seen different businesses take different models.

Um, The other thing obviously is, you know, lending and credit

requires a slightly different set of muscles and different capabilities.

So that's another thing to consider from a tech capability perspective.

Uh, but to me more often than not So you're

saying we have to do leg we have to do leg day.

You have to skip legs.

I think you have to, what we are realizing is you have to

do leg day regardless, right?

Like with, with, uh, you know, a bunch of the, the, the articles that we are seeing

on the regulatory side and risk management side, you have to do a leg day regardless

if you want to deal with people's money.

Uh, right.

So, but it's just a different, yeah.

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Let's let's jump into like day.

And I want to ask a controversial question, if it's okay, given that we

went there and it's very topical and I'd be remiss if I didn't ask about it.

You work at Varo Bank.

Varo is a chartered financial institution.

Y'all went that direction.

There are a lot of folks that do lending and credit and deposit

and any banking relationships through sponsor banking aspects.

And we've had, in my opinion, some of the best sponsor banks on this actual series.

We had Robert Kyle from Finwise Bank.

They do an incredible job.

And we had the folks over at Column as well doing some really cool stuff.

It's

fun having been on.

It.

It was awesome.

Um, what's, what was fascinating over the past few weeks and shout out to Jason

McCullough, he's done a really good job covering it, uh, from a news perspective.

Evolve got a consent order.

Evolve got the data, uh, hack shortly after, um, today there was

a consent order with ThreadBank.

Yeah.

Um, I don't think it's gonna stop, right?

I think that there's more coming.

I think there's certain sponsor banks that do a really good job and are very focused.

From your perspective, Rock Tim, what does the future look like

given this regulatory uncertainty when it comes to sponsor banks?

For folks that are outside of being a regulated financial

institution and relying on that.

Yeah.

Yep.

Uh, it's, uh, it's, it's interesting to see this.

Of course, it's also hard to kind of listen to some of the customer

stories that have unfortunately gotten caught in the middle of this.

Um, Look, I, I think it's very important that there is, uh, you know, compliance

with the basics of, of basic elements of banking and you're talking about

KYC, AML, customer due diligence, you know, having the right fraud

controls and mechanisms, uh, basic safety and soundness, uh, aspects,

uh, right, like, you know, liquidity controls and capital requirements.

These are the basics and these requirements, and therefore a

reason we've all seen multiple times and, you know, a priori.

Until very recently, right?

Like, not, not long ago, where, you know, noncompliance with these basic

tenets of banking can, you know, have severe impacts, not just on the

customers, but, you know, in some scale to the broader American economy.

Um, I think it's also definitely eroded, um, you know, customer confidence.

Um, but at the end of the day, it highlights the importance of prudent risk

management and governance frameworks.

Um, And I think there's something to be said, uh, here, uh, about,

uh, being a regulated bank, uh, about having a skin in the game,

uh, which in some sense necessitates that you build, you know, everything

on top of a solid risk management, uh, And governance like foundation.

So I mean, like that, that's kind of where my head is going.

Uh, I know this is like evolving story.

I, I agree.

I don't think this is going to be the end of it, unfortunately.

So,

so you say it's an evolving story.

I hear you.

I was like, pun intended.

But I think the way you've described it is, is really interesting

because we've got a couple of factors also kicking in, right?

So we've got, we've got the economic climate where, you know, most lenders

are seeing slower and slower repayment.

You're seeing inflation continue to increase.

Now we start to see financial institutions that, Have have shown to have been

participating in unsafe business practices on top of that, as Colton

mentioned a little bit ago, is the reduction in a major revenue stream

for a lot of these organizations being credit card or debit card interchange.

How are you seeing.

Yourself at Varro as well as others in the industry really navigate that

level of uncertainty and ambiguity that is really going on between

the regulators and the economy.

Talk about a lot of people do right, especially in credit.

For example, it's very easy to give away money You really have to you know, do

your due diligence and you know, how you get that money back So from a credit

perspective you you need to again not just have the right underwriting criteria But

you have to have the right setup You know the right product use case match to be

able to kind of serve that space and I've seen a lot of Folks kind of get tripped

up with that last part, which is like, Oh, you know, I looked at all the data I

could and I did this fancy underwriting, but still, you know, the product isn't

performing and you go back and it's a clear mismatch between the use case

that you're trying to serve and in the product construct that you have created.

Um, And I think the other thing that's happening, um, and will, you know,

institutions will have to navigate that.

And, you know, some, some unfortunately have to kind of level, not unfortunately,

some have to level up their game is, is the compliance with necessary regulation.

I think there are.

Sometimes with the push to, you know, do things quickly, uh, in a cost efficient

manner, as I said, you kind of forget the third leg that you have to do

this in a, in a, in a compliant way.

And that is where, you know, some institutions have to like

level the, level up their game.

Um, because otherwise, like you may be, you may be in business, but you're

not in a business that's sustainable.

Right?

Like you have to kind of do all of those things together.

So, um, I don't think there's a perfect answer again, um, here, but there's a few

things to consider on the credit side.

As you said, I think it's a, it's a very interesting space we are in, right?

Like, um, you know, it's been a few, a few interesting years, right?

Like 2020, when we suddenly went into, you know, COVID related.

Uh, you know, shutdowns, I think most financial institutions thought that we

are going to walk into, you know, a deep recession that led to, you know, deep

underwriting cuts, you know, people, you know, pulled back on marketing heavily,

um, in the government put in stimulus.

You, you know, financial institutions saw the, the, the, the opposite

of what they were expecting, and they then had to get step on the,

the, the growth pedal a little bit.

Um, financial institutions did, you know, these things that were really good for

customers or customer assistance programs?

But, you know, what that essentially did is a lot of the

signals that went into your data, it kind of masked those signals.

So you, you did see kind of some of the, the defaults and

credit losses kind of go up.

Uh, you know, people, I, I think latest origination cohorts seem like, seems

like, you know, there's been some control there in terms of managing those losses.

But we are not out of the woods yet, right?

Like, uh, you know, inflation is sticky.

Interest rate continues to be high.

A lot of, uh, you know, savings, uh, that were built up through the

stimulus programs have been eroded.

So it's kind of a watch kind of game, um, for the next one year at least.

And then there's, you know, all of these other items that

you have to keep an eye on.

Love that.

So as we talk about today, we've talked about a lot of things

from what I've loved about the conversation personally has been.

AI within servicing.

We haven't spoken about that.

And I love that, that theme.

Um, let's four minute at the end of every episode we do in the series.

We, we ask you to look in the crystal ball, step inside the time machine,

look three to five years in the future.

My son, actually, my year old son, Hudson, uh, the other day came up to me and said,

dad, when are we going to travel in time?

Great question, Hudson.

I don't know if it'll be possible.

We're gonna try and do it with Rakuten here.

Um, specifically when it comes to lending credit, let's look at lending

credit in the next three to five years.

And what are some of the themes that You're paying attention

to as you're looking at cutting edge or what's upcoming.

You continue to see, um, you know, products evolve and see introduction of

new products and, you know, some of it may be enabled by AI, some of it may not, but

I think we've already started to see that.

And it's a good thing for the customers that we are seeing products

being built from first principles.

Um, I believe I also mentioned that.

Uh, and we've spoken about this multiple times, so it's kind of beating a dead

horse here, but like, the, the need to, need to elevate, elevate experiences

with, you know, your current products.

So, you know, that, that needs to happen.

Uh, I think it's, it's been a theme right now that, you know, while you do all of

that, you need to ensure prudent risk management practices and compliance.

Um, and, and.

You know, now the final thing is kind of how do you make

your businesses more efficient?

Um, but at the same time, don't dilute the customer experience.

And you know, the, the important thing here is, you know, how do you,

uh, leverage technology, be it AI, be it, you know, new tech stack driven

platforms and programs to achieve that.

Um, and you know, one of the use cases you, you mentioned here is servicing.

I think there's a lot of focus on, you know, digital servicing.

A lot of customers right now are, you know, interacting with you digitally.

So, you know, how do you enable a digital servicing ecosystem, which is

also, doesn't kind of take away from the fact that, you know, you know,

you see some of the complaints about, uh, digital ecosystem where, you

know, people want to talk to people.

Where the, the reason behind that is, you know, the responses perhaps you're

getting back, are not personalized to you.

The generic responses.

So how do you make those, you know, more personalized, uh, but still kind of serve

them up in a, in a ecosystem that the customer is willing to interact with you?

Like, that's one example that I see, uh, not necessarily the lending space,

but absolutely in the lending space, but the broader banking space kind

of embrace, uh, a little bit more.

Just to sum it up, you said something that was spot on, Raktim.

How to drive operational efficiency without diluting the customer experience.

There's a lot of decisions that are made to drive operational efficiency

than to dilute the customer experience.

Solutions you should look for combine both together and that's the

key operational efficiency with a best in class customer experience.

I think one of the things that we haven't really touched on that has been

alluded to a number of times through the conversation is the fact that the

products and services that are being delivered today and the product services

that are going to be delivered in the future are going to be focused heavily

on digital natives, not the digital tourist or the digital refugees.

Um, as I like to call them because they, they, they weren't, they weren't

from the digital native, but they're, they're, they're kind of getting to the

point where it makes sense for them.

But all of these things that you've mentioned really are showing that like

we've got to focus on the digital natives, got to have the modern technology stacks,

got to have the personalization that.

Gen Z and Gen A are becoming accustomed to with all of the consumer based products

and services that they're using today.

And all the things you just mentioned really line us up to

say, Hey, this, This has to happen.

It's no longer going to be a choice.

And although it may seem today, like the regulatory environment

doesn't allow for it to happen.

That's where we as financial technology leaders have to figure out

how do we deliver that experience.

While maintaining that regulatory compliance and delivering

a safe and secure product.

That's what I heard throughout today's conversation is that we keep

coming back to that piece of it.

I just make one point though, which is, uh, I, I don't think it's correct

to say that regulatory environment doesn't allow us to do certain things.

Like, if you look at, you know, what's happening, I'll take,

for example, open banking.

Right?

Like that's a law that was probably, it's probably a decade old.

The CFPB is now, you know, intently pushing forward on enabling open

banking, which is very, very good for the customers, right?

The ability to share customer permission data so that a customer

can get a better product and service is being enabled through regulation.

Um, so I, like, I wouldn't characterize it as regulation is holding us back.

Regulation, I think, is here to help us guide.

Uh, us in a way where we deliver products that set both the customers and the

financial institution of a success.

Like that's, that's kind of my take there.

I think, and I love that perspective where I was more coming from is when

we look at regulation, it's typically reactive as Colton mentioned before.

And in financial technology, we have to be a little bit more proactive

and then adjust to the regulatory environment that may not be currently

configured in a way that makes sense for that type of product and service.

And I, and I, and I get what you're saying, like, yeah, it isn't really

holding it back, but it does, it isn't also at the same time, it isn't enabling.

Right.

Or, or pushing us forward.

We've, we've got to, we've got to, we've got to pull the regulatory

process with us versus wait for it to push us, I guess is where I was going.

Right.

Right.

Like, and obviously as we, as we think about new products, uh, you'd have to

kind of think about regulation, but I think in my personal experience, you

know, something that I've seen is if you really, you know, think about a product or

a service with, you know, two key things.

One is like.

Is this the right thing for the customer?

And am I setting up the customer for success?

You really, really, and I stress on the word, really, you know,

come across a point where you are at odds with regulation.

Like I, at least in my experience, you know, I haven't seen that, but like,

that's what kind of, I think about, uh, when I think about, you know,

trying to do something new or, you know, trying to think about a product

or a capability in a, in a new way.

Well, Tim, it's that time, man.

I want to tell you, thank you so much.

The conversation today has definitely been intellectually and mentally stimulating.

So I appreciate you diving in and sharing your perspectives and your insights.

Definitely learned a lot by listening to you today and really appreciate you

coming on the show and sharing that experience and that knowledge with us.

Thank you so much for having me.

It was a fascinating conversation.

Loved every bit of it.

Yes.

Thank you, Rakesh.

Thank you.

Well, folks, that does it.

That's another episode of Accrued.

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