Guests:
– Michelle Young, Credit Product Lead at Plaid
– Ashley Knight, SVP of Product Management at Experian
Host:
– Brett King
What Sparked the Plaid–Experian Collaboration?
HOST: How did this collaboration between two industry giants come about?
ASHLEY KNIGHT: Open banking has been around for years, but its application in credit decisioning is now gaining serious momentum. Experian wanted a partner to help lenders access and use consumer-permissioned data seamlessly—Plaid’s technical prowess and consumer trust made them a natural fit.
MICHELLE YOUNG: Plaid built its reputation on helping consumers safely share their financial data. This partnership brings together Experian’s credit scoring expertise with Plaid’s cash flow insights and open banking APIs to better serve lenders and consumers.
“The market is innovating so quickly. Real-time cash flow insights are no longer a nice-to-have—they’re essential.” — Michelle Young
Why Real-Time Credit Decisioning Matters
HOST: How is the need for real-time decisions reshaping lending?
– Traditional document-based risk assessments create friction and delay.
– Consumers expect instant approvals due to buy now/pay later and mobile experiences.
– Real-time cash flow data from open banking eliminates latency.
ASHLEY KNIGHT: Modern lenders can’t afford lag in credit risk evaluation. Instant access to behavioral and transactional data enhances both decision accuracy and borrower experience.
“No latency. The freshest data possible is what lenders need now.” — Ashley Knight
How Open Banking Drives Financial Inclusion
HOST: Is this data expanding access or just refining risk?
– YES, it’s doing both.
– Analytics show up to 30% more approvals when using open banking data—without changing risk thresholds.
– Helps “thin file” borrowers (e.g., recent grads, immigrants, gig workers) qualify for credit.
– Enables better credit decisions for the underbanked, 100 million Americans currently underserved.
“There are perfectly good borrowers out there without credit histories. Cash flow data brings them into the fold.” — Ashley Knight
How Lenders Are Using Open Banking Data Right Now
Use Cases:
– Underwriting: Particularly for personal loans, credit cards, buy-now-pay-later (BNPL), and earned wage access.
– Customer Management: Identifying hidden risks (e.g., payday loan usage in prime credit segments).
– Mortgage: Verifying assets/income early in the loan cycle streamlines underwriting and approval times.
– Cross-sell/Upsell: Real-time income tracking helps tailor credit limits and loan offers dynamically.
“Why ask if your income changed when your account activity already shows it has?” — Michelle Young
The Technical Lift: Easy API Integration
HOST: Is this hard to implement?
EXPERIAN:
– Data shared via seamless APIs.
– Lenders get categorized cash flow attributes or scores directly from Experian.
– Supports credit cards, auto, personal loans, mortgage underwriting.
PLAID:
– Consumers onboard through a familiar, trusted Plaid interface.
– Lenders can connect via direct API or third-party loan origination platforms.
– Fully FCRA-compliant under Experian partnership.
AI and the Future of Lending
HOST: What role does Agentic AI play in this?
– Cash flow data + Agentic AI = hyper-personalized lending experiences.
– Imagine your AI assistant finding you the best loan offer in seconds by scanning thousands of lenders.
– Both Plaid and Experian are building toward this AI-integrated future.
EXPERIAN has already launched the Experian Assistant, built on Agentic AI, enabling easy, real-time access to financial insights for businesses.
PLAID envisions a world where consumers don’t search for loans—loans find them through AI.
“Cash flow data is real-time and dynamic. That’s what makes it AI-ready.” — Michelle Young
Regulatory Landscape: What About 1033?
– Rule 1033 (from the CFPB) is expected to shape how consumer-permissioned data is accessed, shared, and secured in the U.S.
– Both companies are confident that open banking is “here to stay,” with or without immediate regulation.
– Consumers own their data—and the industry is rapidly moving to empower them to use it across financial and data ecosystems.
Final Takeaway: Cash Flow is the New Credit Score
– Cash flow data isn’t just an alternative data point—it’s a core signal of financial health.
– Real-time insights enhance underwriting, portfolio risk management, and cross-selling.
– Early adopters will set the standard for future-proofed lending strategies.
How to Learn More
Visit: https://www.plaid.com and https://www.experian.com
Connect with Michelle Young and Ashley Knight on LinkedIn.
Episode 602: Smarter Lending Expanding Credit Access and Improving Risk Decisioning at Scale – Full Transcript
Brett King
Welcome to Breaking Banks. I’m your host, Brett King. And this week, we have the return of our partners at Plaid, and they brought along their friends from Experian.
And some interesting things are sort of happening in the lead up to sort of the world of agentic AI and so forth. One of the things that’s really interesting in this space right now is as we look at the next generation of generative finance, a lot of what we’re talking about, whether it’s smart contracts or GenFi or these sort of things, is going to require a new way of us thinking about data. And so this is sort of the theme of this collaboration that’s come about between Plaid and Experian in terms of using data to get a better view of customer behavior, looking at credit risk in particular.
So what we’re really going to get into today is looking at how this market is changing, how data access is driving the demand for open banking, regardless of whatever the regulations are in place. And we’ve got the team here to talk about it today. So let me introduce you to the two speakers that we’re going to be speaking to today.
We have Michelle Young, who’s the credit product lead at Plaid. She builds products that leverage cash flow data to expand responsible credit access. And obviously, Plaid products like this are used by SoFi, Zillow, Home Loans, BMG, Affirm, and others.
Prior to Plaid, Michelle was that head of lending product at Figure and worked in risk at SoFi and did some work with EY. We also have Ashley Knight joining us. She is the SVP of product management at Experian.
She leads the product management team for financial services and data business with a focus on these sort of alternative data relationships, alternative data credit scores, open banking, and so forth. And she fosters innovation and drives financial inclusion and likes to do that by using this new data. So Michelle and Ashley, welcome to Breaking Banks.
Ashley Knight
Thanks for having me.
Brett King
So let’s start with this collaboration before we start talking about some of the particulars, particularly in terms of cash flow insights and so forth. But how did this start off? Because both of you are fairly senior players in the market.
Typically, when we look at these types of collaborations, it takes a fair bit of time because you’re both fairly well developed in the market. So how did this sort of natural collaboration come about?
Ashley Knight
This collaboration started because open banking has been on the rise. And it’s not new to most of us. It’s been out in the wild for many years now.
But in terms of use of this data for credit decisioning, that’s what’s starting to emerge more. And so as Experian has embarked on offering open banking solutions for the purposes of decisioning as part of credit underwriting and such, what we found was that clients, lenders, et cetera, are super interested in this data and they want to start using it. However, they face challenges around, how do I access the data and how do I get consent to use the data?
And so that’s where Experian started to assess different partnerships in the market. And Plaid obviously rose to the top because of their capabilities.
Brett King
Yeah. Michelle?
Michelle Young
Yeah. Look, I mean, I think as Ashley mentioned, we are a market leader within the open banking data. And the thing that I am so proud of is just the relationship that we’ve built with consumers and facilitating sharing of bank data information.
As this has evolved over the last kind of decade and kind of the comfort for consumers to share this for different use cases, we’ve really seen an opportunity to have this data be leveraged as you mentioned at the top of this for credit risk and underwriting and access to new types of loan products. And so as we’ve really focused on the consumer relationship, we’ve also thought about how we develop relationships with other customers in the space or lenders using this data. And I think we bring that open banking expertise, the conversion expertise and how consumers really share this data.
But working with a partner like Experian allows us the opportunity to really expand the types of lenders that will be able to access this data. Between their expertise in the credit space and our expertise within the open banking space and really cashflow specifically, it’s really a great partnership that I think is really differentiated in the market.
Brett King
So I want to get into the cashflow stuff obviously, and I want to talk about how it can be used and also give some insights from the work I’ve seen globally where we see cashflow utilization. But before I get to that, the other thing that sort of occurred to me in the prep for this show is that there’s something also different happening right now experientially in the credit business, in financial services, where there is an expectation because of mobile and because of buy now, pay later and so forth, that there needs to be real-time credit decisioning. So if you have a process internally in a bank or in a lender where you have to request paperwork off a customer to be able to analyze their credit risk, you’re already essentially got a data risk in terms of protecting the moat for your business as a lender.
Because everything we see right now, whether it is, as I said, sort of contextualized lending like BNPL or whether we look at agentic AI and its role potentially in lending moving forward, you’re going to have to have that real-time analysis. Would you guys agree that a large part of this data requirement is that moving forward, credit risk and credit decisioning is going to be in the domain of real-time and therefore you need the data? Is that a safe assumption?
Michelle, you want to kick us off?
Michelle Young
Yeah, I’m happy to. 100%. I’m laughing at you saying paper documents.
I don’t even know if paper bank statements even exist anymore in the world that we’re living in.
Ashley
I know. It’s insane, right?
Michelle Young
Yeah. It’s like when you set up everything, it’s like digital statements and then they email you over and over again to make sure you do digital. I think that just goes to show the world that we live in is so much different than I think the world that was set up when some of these traditional credit products in place.
For the record, I think that those do have benefit in terms of measuring the willingness to repay. I think that as we look at cash flow data in general, it’s the ability to pay. I think that the piece that you talked about is the market is innovating so quickly.
There are new products all the time coming up and especially the mergers and fintech. If you think about credit builder applications and products in that space, if you think about buy now pay later, which you mentioned, these are different tools that do show up in real-time data. The value of having that is that snapshot that is actually able to keep up with the innovation in the market and ensure that you can continually update your credit risk and your understanding of that consumer’s ability to repay this loan from a credit risk perspective because that data is real-time.
Brett King
Absolutely. Ashley, I think you guys would agree that you see that as your business is expanded, the credit score is at the heart of what you guys do, but it’s not all of what you do. There’s a whole bunch of other data that you’ve been specializing in building on, right?
[Speaker 1]
Yes, absolutely. There’s so much more data that has a wealth of information that goes beyond credit and really helps to complement the overarching view of a consumer’s ability and willingness to pay. That additional data is hugely valuable to the companies we work with, and that’s where open banking and consumer permission data becomes even more important, especially as we go forward because we truly believe this is going to be the future of scoring where lenders start combining credit data, alternative data, such as consumer permission.
Buy now, pay later is obviously top of mind in getting more transparency into that data overall, in addition to other data metrics that clients are looking for to better assess risk. See, to emphasize there too, that is so important because there can be no latency, and having the freshest data delivered as fast as possible is extremely important to lenders in terms of their application flows and pull through, et cetera.
Brett King
I don’t know whether you guys heard this stat, but this is to show how behavioral lending is and what the psychology is behind this, but I heard this stat out of the, again, it’s a Chinese market, and we talked about the Chinese market in the lead up to this, but there was a really amazing stat from, I think it was WeChat Pay and some of the lending stuff that they were doing, that someone who keeps their phone charged correlates with a much lower risk of lending default.
Just a really simple data point. I remember I had Scott Sanborn on from Lending Club, and he came up with a data point. He said, you know what is the best predictor of default risk for us?
He said it was whether someone pays their mobile phone bill on time. So there are other sources of data that are really useful here, but how does this additional data for lenders in particular, how is that opening up the market in terms of lending? Is it changing approvals?
I mean, I’m not just talking about default risk, but does it mean more people are now getting access to credit as a result of this?
[Speaker 1]
It does. It does. In the analytics that we’ve run, we’ve seen there can be as much as a 30% increase in application approvals for those that use open banking data.
And that just means so much more opportunity for consumers as well as lenders. And keep in mind too, that’s not changing risk tolerance. That’s maintaining existing thresholds, but just approving more consumers with this bank account information.
And so most of the use cases, because we’re really talking about benefit and return for lenders to use this data, most of the use cases initially that lenders are starting to look at is leveraging this for underwriting specifically to expand their lending universe, score more consumers, really target the thin file population, which is consumers who don’t have a lot of credit. And that could be someone who just graduated from college. We’ve all been there.
We haven’t had a first credit card yet. And we signed up for one on campus as they were promoting it.
Brett King
Try being an immigrant and building a thin credit file. Let me tell you about that.
[Speaker 1]
Right, exactly. And so that’s where cashflow and open banking data is so important and what lenders are starting to look at in terms of, I can better assess a consumer, not just by one piece of information. I can go even further and approve more applications and maintain my existing risk tolerance.
And we know there’s so many consumers that don’t have access to mainstream credit. 100 million Americans do not. And so that just further reinforces why this is so important and how it benefits lenders and consumers alike.
I’d also add to just that, you know, that’s one example of how cashflow and open banking data can benefit banks. But there’s so much more around leveraging this data to assess potential risks or opportunities with an existing portfolio. So if you think about banks that have an existing deposits portfolio, right, leveraging open banking technology to assess opportunities within that portfolio is another area where organizations are starting to see opportunity to leverage this data for upsell, cross-sell.
Yeah, which I think the exciting part is it all comes down to, you know, different use cases from a lender’s perspective. I think there’s this broad impact that we all know, and I think cashflow in general has been talked about, you know, around how this can really develop and change the industry. It all comes down to you as a lender, where do you want to get started?
You want to look at populations where you gave them an interest rate, maybe they didn’t take the loan. Could you be giving them a better interest rate? Do you have a better idea of that risk of that borrower?
And then all the way through the full lender lifecycle and not thinking about it as a point-in-time solution, but as a lender thinking about the broad impact. You know, what we’ve talked about with customers is that account line management on the credit card side, on the servicing use case that Ashley talked about, you know, don’t we all hate going into your credit card and getting the prompt that’s like, has your income been updated? Like what if the credit card company knew your income was updated and then adjusted your credit line because of that, because it can be productive.
And so we’re just excited to see that, you know, the value is broad, but it all comes down to the experience and how a lender actually brings that into the process and rolls it out to a customer.
Brett King
I think we’ve learned a great deal about data models and the role they have to play in managing risk over the last decade or so, you know, as FinTechs have come into the market and sort of taken these more creative approaches. I know I talked with you guys about a couple of examples of that, you know, New Bank in Latin America, where they’ve had, you know, with their credit card rates, 30% lower delinquency rates than the rest of the market there. Primarily, I think that’s because of cash flow data.
And another great example out of China is with Alipay’s, or Ant, MyBank’s SME lending portfolio. And I mean, this is considerable. We’re talking about 60 million SME businesses annually that they lend to.
They have 40% of the SME lending market there. And that’s driven in large part because they have this platform ecosystem around Alibaba and other, you know, merchant platforming services like that. But their NPL ratios are half of the big banks in terms of lending because their ability to know that platform and wallet-based cash flow data gives them a huge data advantage in being able to anticipate risk.
And I think that’s where it’s really important in, you know, particularly for first-time credit usage. If you don’t have a credit score, if you’ve got a thin credit file, it doesn’t necessarily mean you’re a bad lender. The cash flow data could tell us you’re actually, you choose not to use credit because you manage your money very well.
And, you know, that should give us, you know, and if we see you manage your money well, then that reduces risk. So I do see a real demand for this sort of behavioral data sets in terms of this. You know, in terms of AI, I want to get into the tech a little bit, but in terms of AI and how you guys see that develop, what do you think beyond this cash flow data, what sort of other data sources might you guys be looking at to augment, you know, credit decision-making and understanding customers better?
What about you, Michelle? What are you guys thinking about?
Michelle Young
Yeah. I mean, I think like you hit on that point of the behavior. So if you think about like within cash flow, the, you know, the pieces that you’re looking at is the behavior of how you manage your money.
I think the thing that we also find very interesting is like the behavior of what is happening with that account that you connect. And so how do you think about, you know, I am connecting an account for a credit card. Where else am I connecting that account?
Am I also connecting that account from, you know, an open banking perspective to a personal financial management app because I really care about managing my money or a wealth management app because I’m actually trying to invest in my future. Those are all positive indicators of a behavior that would result or impact credit over time. And that is something that we continue to invest in.
Does like, how did those other multi-dimensional data points actually really drive the impact or correlated or predictive of credit risk? I think the point that like, I want to hit on is you’ve talked about like credit and kind of like credit in general as this thing around traditional scores. And then we’re talking about cashflow, like in the end of the day, like drivers, like, you know, Lending Club, who you mentioned and others, like they’re innovators in this space because everything they look at is multi-dimensional.
It’s not single source data. And I think that’s where, especially in an unsecured loans, like that’s where you really begin become competitive as a lender to really access these different data points that you’re not seeing today.
Brett King
Absolutely.
Ashley
I would completely agree with that, Michelle. And I think open banking is just the starting point and it’s going to very quickly move to open finance and an open data ecosystem where the, you know, the key component is still the consumer in control of their data and they share it and they are empowered to share it with who they choose to in a secure manner. And so it’s open banking today.
In the future, they’ll have the power to share whatever data they want. And so when we think about going forward and what other data will want to empower the consumers to share, it is more around employment and pensions and wealth information, all of this that shows more information about a consumer’s financial profile overall. But I think going broader, I know we’re talking about, you know, lending and bank data specifically, but I do think it’s going to be just open data, right?
So I can share with you. Yeah.
Brett King
Health data is going to be big. Yeah, absolutely. Identity.
Yeah. Exactly. Like if you want to start coding your own LLM, think about the data you’re going to have to share.
If you want to personalize your AI to integrate into your life better, think about the sort of data you’re going to have to share for that. I think we’re moving into a very different era when it comes to that stuff. Let me ask you about the technology a little bit.
You know, I hope you guys are okay to sort of dive in the weeds a bit, but, you know, if I’m a bank, you know, or a lender and I want to get access to this type of data, you know, help me understand what sort of technical agility am I going to need? You know, what’s the, you know, how complex it is to sort of build this into my decisioning matrix? And, you know, do you think that this sort of speaks to technology architecture moving forward that’s going to have this sort of flexibility?
Maybe you can kick us off, Ashley.
Ashley
Yeah. Yeah, absolutely. So I’ll let Michelle speak to the actual design of the integration component with the consumer.
But what we’ve built with Plaid is very streamlined connectivity with two connections through APIs so that the data can seamlessly be shared from the consumer at the time of application. And then that information is shared with Experian. Experian takes that information and we categorize it and we deliver back directly to the lender a cash flow attributes or a cash flow score, depending on what they choose.
And then they can leverage that information to make a credit decision across a variety of use cases. So credit cards, personal loans, automotive, mortgage. And the way that we’re seeing this adopted today is separate from the credit score.
It’s often either pulled at the same time or pulled as a second chance as we talked about before. But what we’ve set up and created with Plaid capitalizes on the already streamlined experience that Plaid has today with lenders and consumers directly and only a few extra connection points through APIs to get to Experian cash flow attributes and cash flow score.
Brett King
Cool. Michelle?
Michelle Young
Yeah, on the consumer side, I mean, I think it really comes down to, you know, Plaid’s role in facilitating sharing this data. And so, you know, as customers or lenders identify, yep, I want to start testing this product. I want to look at this.
They can integrate directly with Plaid through our own APIs, or they have the opportunity to integrate through our ecosystem of partners, loan or donation systems, platforms to actually access this information depending on what their technology stack looks like today. And then we would go through the thing that Plaid is the most known for is the ability to allow consumers to go through a streamlined flow to share this information. For our Experian partnership, it’s specifically through our consumer reporting agency, which allows us to share this data in FCRA compliant manner in order for consumers to actually have this be under a specific permissible purpose and for lenders to be able to actually decision on that data.
Something that we are really proud about at Plaid is the relationship that we have built with the consumers itself for that sharing process. We see one in two consumers have connected an account with Plaid, and that really drives that high converting flow that allows a consumer to share this information. Once that information has been shared, then as Ashley talked about, we have a seamless integration with Experian in order for that information or data to be sent over to Experian, and then they can then send back the attributes and scores that she talked about to the lender.
Brett King
This does speak to, I think, technical agility more broadly, because if you’re looking at integrating this type of data, which every bank should be looking at it, another great example I give is the mortgage business. The intent to buy a home is something that banks don’t have, mortgage lenders, brokers don’t have that data, but Facebook has it. When you joined a real estate group, Apple has it.
When you downloaded an app and you’ve been doing property searches, Google has it because you’ve been doing searches. There does seem to be, moving forward, data is a competitive edge that you’re going to bring to different elements of your business, but it also requires a pretty significant technical agility to be able to plug in these different ecosystems. So I think that that’s increasingly technical agility and cultural agility of organizations is going to be a real hallmark of those who are able to thrive in this sort of new era of financial services.
On that note, let’s take a quick break and we will come back after the break and get into some of the more detailed aspects, particularly around the use cases, how regulation is going to adapt to this and the future roadmap, particularly around AI. You’re listening to Breaking Banks. I’m talking with our friends at Plaid who brought along Experian.
We’ll be right back after this break.
[Speaker 3]
Hi, this is Rob Tercik from The Futurist Podcast, which is part of the Provoked Media Network. I’m excited to tell you about some news. The Futurist is expanding into the real world.
We’re doing a live event in Dubai. Now, folks who listen to The Futurist Podcast, you’re going to be familiar with the fact that my co-host Brett King has been working very hard in Dubai and other parts of the Middle East for a long time. And for more than a year, he’s been putting together this event.
And now, with the help and support of MasterCard and Emirates, MBD and many other partners, we are putting together the world’s largest futurist meeting in Dubai. It will take place at the fabulous Jumeirah Beach Hotel in Dubai, and it’ll be on the September 22nd and 23rd this year. So just a few weeks from now, the speakers are going to include some of the world’s leading futurists and forecasters and future thinkers, people like Brian Cox and astronaut Scott Kelly.
Of course, Brett and I will be there to conduct interviews and introduce some of the other folks. We’ve got speakers from around the world. And if you’re interested in meeting futurists in person and participating in an event that attracts the future-minded, please join us on the 22nd and 23rd of September.
You can learn more about it at futuristevent.com. That’s futurist, singular, event, dot com. It’s all one word.
Futuristevent.com. And that’ll tell you all about the event. I sure hope to see you there in Dubai on the 22nd and 23rd of September.
Thanks.
Brett King
Welcome back to Breaking Banks. This week’s episode is brought to you in conjunction with our partners, Plaid, and they’ve brought along their friends at Experience. And we’ve been talking about cash flow data and its application in open banking and sort of more broadly in credit decisioning and so forth.
But Ashley and Michelle, let’s just talk a little bit about some of the use cases in terms of cash flow adoption. Where are you seeing sort of the primary adoption areas right now? I know we’ve talked a little bit about the user experience, but which specific areas and product portfolios is this seeing usefulness in today?
Ashley
So I’ll start by saying that it’s a broad spectrum in terms of who’s prepared and ready and willing to use cash flow data, but everyone’s talking about it. And so that’s the main point. Top of mind for all, a lot of adoption in fintech and credit unions are exploring this automotive from a segment perspective.
That’s a significant focus. I think you’re hearing the same too, right, Michelle, on your side? Yeah, definitely.
I think personal lending, I think just with the appetite and the need to really differentiate on the credit side of how do you grant loans versus collateral loans don’t necessarily have that sense of urgency to start. I think we’re going to see a lot of personal lenders, credit cards, all of that really start to adopt as first movers outside of those that have been in the market using it for years, like some of the alternative credit products like Earned Wage Access or Cash Advanced or Buy Now, Pay Later. Mm-hmm.
Yeah. And the use cases we mentioned, the underwriting use case, of course, is prominence and customer management, so overseeing an existing book of business. And we’ve done a lot of analytics on our side, and it’s quite surprising and just sort of fascinating to see what can be uncovered in a large portfolio that organizations may not even know.
I’ll give you just one quick example of an organization that uncovered a significant amount of payday loans within their prime population that they weren’t aware of. And so that’s just two great opportunities, one for the consumer mostly, right, to potentially get a better-priced loan. So that’s one of the use cases and just sort of interesting to see what you can uncover using open banking technology.
And then we’re starting to also hear more around the mortgage space. I think, Michelle, too, you’ve seen that as well, where mortgage organizations are looking to better understand transaction behavior and patterns as they look to sell portfolios and how to price those. Yeah.
I think mortgage is really an interesting space because I think at times we talk about cash flow as this broad bucket that’s like anything that you can do with a bank account based off of that transaction and how you can use that to underwrite, verify, or really help from a process perspective. I think in mortgage, the places that we’ve seen is that the ability to get a mortgage, you always have to share bank data in order to verify assets, especially in a purchase transaction. And so that familiarity with consumers and a very high-intent product that has a lot of friction already.
I mean, if anybody’s been through the process, it probably wasn’t the most enjoyable experience. They’re going through and they need this information. And the thing that we are excited about that we’re seeing on really the originator side is that you actually are having access to data.
It’s all about how you use that and where you get it in the process. So the earlier that a consumer can share this information or a borrower can share this information to really apply, the earlier you have access to things that can assess where is the source of that down payment fund coming from? Was there a large transfer or deposit that they need to look at and evaluate for the underwriting process?
Can they actually use income and partner with the GSEs, Fannie and Freddie, to actually use that same bank account to qualify and verify assets and income at the same time? But it really comes down to getting that information as early as possible. And then the mortgage lenders that I think are really on cutting edge on this side are going through the process to actually use that data earlier to drive the workflows downstream and really create process efficiencies and close mortgages even faster.
Brett King
You know, as you sort of think about the application of this in specific models, you know, I mean, even in the mortgage business, when you’re talking about all of the data we’re trying to collect, we’re really trying to approximate cash flow anyway, because we’re trying to see whether the consumer can afford to lend. So much of that could be simplified even, take friction out of the process. How are you, how’s this being sold to consumers?
Is it sold on the benefit of lower rate or, you know, what percentage of consumers are willing to give up cash flow data, for example, to get access to better loans? Have you guys got data on that?
[Speaker 1]
I’ll talk a little bit about what we see from just a consumer comfort perspective. I mean, we’ve done research and consumers don’t necessarily feel like, you know, a credit score itself or a representation of their full and complete financial picture, which really indicates that like there’s a desire to share more. And in fact, we did a research study with Datos Insights and saw that 74% of consumers are more comfortable sharing their bank data.
And I think as we see adoption and as we see consumers, you know, develop a relationship and we talked a little bit about the one in two Americans that have shared their information with Plaid, like their desire is to have this information be a part of that evaluation.
Brett King
That’s such a flex stat, that one, one in two Americans.
[Speaker 1]
It’s so flex, I had to say it twice.
Brett King
Well, you know, I noticed it, right? So anyway, Ashley, you know, in terms of specifics around the consumer willingness, are you, you know, is this a sign of greater sophistication or is it more just consumers, I think, a little frustrated that the existing data we used to assess, they don’t feel it accurately portrays their position?
[Speaker 1]
Yeah, I think the consumers, as they’ve shared with us, are willing to do that and share the when they know there’s a benefit to them at the end of the day. We’ve done our own research, which ties very similarly to what Michelle said of around over 70% are willing to share, but it’s important that they know why they’re sharing and that there’s a benefit to them. And the better interest rates or a better product or service is one of the reasons they’re willing to share.
Brett King
Great. Well, at this point, let’s do a call out to Stuart Watterson. Stuart is a strategic advisor for Datos Insights, and in November 2024, they did a research piece on this, how the availability of cashflow data addresses two key or two critical industry challenges.
This is what Stuart had to say. The availability of cashflow data addresses two industry issues, challenges that I think will cause just a real ground shift in consumer lending. So the first is creating pathways for the credit underserved consumers, the credit invisible.
[Speaker 4]
And this is a number of consumers that choose your estimate anywhere between 30 and 90 million consumers across the US that don’t really fall under and or work well with legacy scoring models. So they’re either new to credit, no credit, bad credit, new to country, students. And we all know that there is perfectly good opportunities there within that population.
And this expands that opportunity like it’s never been expanded before. So it’s really a good step forward as far as serving that population. But then on the other side of the coin, it expands a consumer lending addressable market significantly, and also improves the ability to manage credit.
So the Experian-Plaid partnership is, I see it as kind of like some basic infrastructure that can expand addressable markets and serve consumers better. And that’s truly a win-win situation. This could be a real change.
Brett King
Well, I mean, look, we know there are people out there that are good at managing credit risk, because we know the other metrics that align with people who are good with money. And we know that a lot of them have poor credit score or thin credit file. And the only way to get that credit file improved is either they got to earn a lot more money or have a lot more credit history.
And neither you can do if you’re starting off. So that’s, you know, that’s a core problem. So this is where the behavioral cash flow metrics is actually a better indicator of someone’s core financial health and their ability to manage money.
Okay. So Ashley and Michelle, coming back to, you know, the space around this, one of the things that sort of, one of the reasons for Plaid’s existence in the US market in particular, is that in this field of open banking, it has been left to sort of commercial aggregators and platforms like Plaid to do this work instead of seeing mandated open banking, as we’ve seen in the European Union and other parts of the world.
But in terms of the regulatory response to this, is there any regulatory guidance right now in respect to how regulators see sharing of cash flow data? I do know that, you know, I mean, we’re talking many, many years ago now, but in the early PFM days, when we’re starting to, you know, allow people to share their data on platforms like Plaid, it became an issue of some contention because banks thought they owned the data and so forth. But I mean, we’re talking about consumers’ own data here.
That’s been clearly established. But what other regulatory concerns come into this space?
[Speaker 1]
Yeah. I mean, I’d love to just touch a bit on kind of the evolution of open banking. I think that’s super important.
Sure, that’d be great. I love Ashley’s perspective on other regulations from a, you know, credit perspective. But I think like that point is so key that like the internationally open banking has been around a while.
Like those stats that you talked about as you talk about things like new banks doing, like that is powered by the fact that other markets are much more advanced in this space. I think there’s been a lot of regulatory kind of evolution of open banking in general, you know, with the rule 1033. I think the verdict’s still out on where that’s going to land.
But like, my firm belief is open banking’s here to stay. And as you talked about, as it moved into the US and it started in a world where it was just getting up and running, we’re so much more advanced in the space of this information being shared securely. It’s powered mostly by APIs that actually share this information and allow a consumer to grant access to a platform like cloud and then also have a securely actually access that information through the financial institution.
And so despite the regulatory environment around open banking, like our strong view is that like it is here to stay. And all of the stuff that we talked about in terms of how do you use cashflow data, it can’t happen without the ability for like scaled access to that data, which cloud is a very core part of.
Brett King
I’ll be clear in respect to this, you know, my role in the industry is largely as a futurist, looking at, you know, future proofing the sector, being able to talk about the changes that will be happening in five and 10 years from now and putting in context that. But the reason I say that is because you cannot have AI-based banking without open data. I mean, you know, the two are absolutely correlated.
So if you want to have a modern, you know, autonomous, you know, banking system or highly autonomous banking system using AI to really increase, you know, the effectiveness of the system, you’re going to have to have open data. That’s my position anyway. And I think most of the regulators probably, you know, agree with this.
But there is, of course, GDPR concerns and other things like this, you know, more broadly, there is data restrictions. Ashley, you guys have to deal with that all the time with credit scoring. You know, who is the primary regulator that you guys generally feel you’re working with or who regulates your part of the sector?
[Speaker 1]
Yeah, well, yeah, you’re so right. We are one of the most heavily regulated industries for good reason. And so we’re very well-versed and experienced in this.
We’ve operated in this highly regulated environment for many, many years working with federal and state administrations on, you know, FCRA obligations, etc. So we’re very familiar here. We have several practices in place, compliance, rules, governance, etc.
to make sure that our business is meeting expectations around privacy and security. And we’re well-equipped going forward. Whatever those future regulations may be, as Michelle mentioned, 1033 is up in the air right now.
But either way, we’re very well-equipped to handle what’s to come. I’ll say too, because we all sort of watch 1033 unfolds and folds back up and do different things in that way. And what’s been interesting is that while that’s evolved, let’s say, the lenders that we work with are still so focused on this data, regardless of the regulation, because they do know and they’ve seen the results that it does have predictive power and it does drive greater financial inclusion.
So I think as well, while regulations are so important to the industry, even if 1033 takes a longer time to come to fruition, it’s not going to change how the industry responds.
Brett King
For our listeners who are outside of the United States, do one of you want to quickly explain what 1033 is?
[Speaker 1]
Yeah, yeah. I’m happy to, although like I will say I’m a product person. So there are people that are the experts in this space at Platt.
I think we’ve got a ton of content out there. So check us out if you want to go deeper. But it is really the regulation that sets the framework for how open banking data is shared, what type of data can be shared, what can be used with that data, and how the actions of those that are actually facilitating sharing that information, what are the criteria, what kind of data can be shared.
And so it really kind of sets the framework for open banking in the U.S. so we can catch up to other international areas that, again, have more advanced spaces here.
Brett King
Nicely covered. All right. So let’s look, let’s do a bit of future gazing.
Let’s talk about where do you see this in a few years’ time in terms of sort of the way cash flow data is sort of built into the system. Do you see it as table stakes? Do you see that it’s going to take a fairly significant amount of time to get adoption like credit scoring did in the early days?
Or do you think it’s going to happen quicker?
[Speaker 1]
So I think my prediction, especially with collaboration between companies like Experian and Platt, are going to accelerate adoption much faster. And a few reasons why. One is that we can demonstrate with real data, real performance data, the impact that this has to risk to financial inclusion and more.
And that is so key to anyone starting to use any data set is prove it. Prove to me that it works and how it can help me and my growth objectives for my business and also help my customer. And so I think the combination of us together helps to drive that adoption much faster to prove why you need to use this data.
Brett King
All right, but let’s talk about agentic AI, right? Because in five years, I could see agentic AI being a big part of lending decisioning and automating this sort of data. I can imagine my personal AI saying to me, I think I can get you a better loan if you’re prepared to release your cash flow data.
Would you like me to proceed with that, right? I could see that as being a sort of a natural use case, but how are you guys preparing or looking at leveraging AI in relation to this specific data set and feature?
[Speaker 1]
Yeah, I mean, I’m happy to start on my side. I think that scenario just planned, one, that data has to be facilitated, being shared, and that data needs to be shared in a safe manner. So in order to show that reality, there still needs to be that safety and soundness around a consumer having the ability to share that information and really the trust behind the provider that’s helping facilitate that, which I think is so important from a pod perspective in our role there.
But 100%, I think today, the way that consumers manage their money is so different, but really a lot of the decision becomes around what the consumer wants to do. How do I want to spend? When do I think I need to go get a loan?
What are my financial goals? I think the place where the agentic AI gets so exciting is it really allows everybody to have an advanced sophistication of how they view money and how they manage their money. What if a world happens that instead of me going to look at a marketplace, the marketplace comes to me because the agentic AI has gone out and actually found those options for me.
I think that’s a place where the evolution of cashflow data in general and the trends that we’re seeing today, they’re going to dramatically change with the opening up of AI and different tools that’s going to do that. I think that’s also where the power of it is, is because the fact that cashflow data is real-time and can dynamically change with those trends versus I do think on the credit side, it’s going to be has that lagging factor that this is a really new established source to be able to keep up with innovation.
Brett King
I can imagine my personal AI telling me, I’ve gone out in the space of 180 milliseconds, it comes back and says, I’ve gone out and reviewed 3000 lenders and I think I can get 120 basis points better off if I share your cashflow data. I can imagine that being a real case. What about Ashley, what are you guys doing to prepare for agentic AI and its inclusion in your system?
[Speaker 1]
We’ve been innovating with AI for nearly two decades, so it’s definitely not new to us and it’s baked into virtually all of our products. In fact, we recently announced Experian Assistant, which is a virtual real-time assistant and it’s built on agentic AI framework and it allows businesses to interact with financial data in a very easy, not complex way, makes analytics much more accessible. We’ve started to promote that more and help customers drive insights faster and make better business decisions.
Having said that though, with regards to cashflow, I do think it’s really early days and what we’re seeing is organizations want to get their hands on this data first themselves before they start fully automating and empowering decisions to be made on their behalf. And so that’s where we come in and are critical to the process to help them access the data, derive insights from it, and then use it within decision-making processes.
Brett King
So you guys have heard of KYC, have you heard of KYA? No. No, you’re an agent?
Here’s my question to finish the show on, and it’s a question for you, Ashley. When are agents going to have to get credit scores? I’ll leave that thought.
[Speaker 1]
Is that a new model that we’re going to have to build?
Brett King
Look, I think so. You’re going to have to assess the risk of specific agents, maybe agent platforms. But that’s a billion dollar business idea for Experian.
I just but I’ll leave it at that. All right. So let’s wrap up, guys.
We’ve got to wrap up. We’re running out of time. It’s been a really great conversation, but where can lenders find out more about this partnership, about what you guys are doing and maybe access the program?
[Speaker 1]
Yeah. They’re welcome to find us at plaid.com experience or reach out to Experian at plaid.com.
Brett King
Fantastic. And before we go, how do people follow you guys personally? Do you have a social media platform you use, LinkedIn or whatever, where we can find out a bit more about what’s happening in your space?
[Speaker 1]
Yes, absolutely. You can find me right on LinkedIn. Yeah.
So you’re here.
Brett King
Fantastic. All right. So Ashley Knight and Michelle Young, thanks for joining us at Breaking Banks this week.
And it was a really interesting conversation and all the best with changing the world of open banking data.
[Speaker 1]
Thank you. Thanks, Brett.
Brett King
Great. That’s it for Breaking Banks this week. Thanks for joining us again.
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