Lessons learned architecting open finance for growth and inclusion

Chris Hansen: All right. And with that it's my pleasure to welcome everybody to Lessons Learned in Architecting Open Finance for Growth and Inclusion. I'm Chris Hansen. I'm our GM of strategic partnerships at Nova Credit where I help work across all of our cashflow underwriting solutions here and some of our impactful.

Partnerships in the industry to help move everybody forward. I'm joined here by Vijay Krishna, Chief Product Officer at Akoya. Vijay, it's great to have you. He's bringing extensive infrastructure experience in the open banking architecture space and across the industry, working with many of you on the call.

As do I. And we get the pleasure of working together. Really excited for the conversation today. Talk about how we can build extensible programs. From a macro at Nova Credit, we've been working on open banking, architecture and solutions for over five years. And I've learned really that most of the successful deployments that we've seen with our customer base and many of the lenders that we interact with, that it's really not just about unlocking the data connectivity.

It's really about architecting your system beyond just compliance requirements and also starting to understand how data out and data in can play with one another. And that's, more relevant than ever with the 1033 landscape that we're all currently in. And we're gonna dig into that a little bit today.

Really, I want my hope is that people walk away with practical knowledge and some lessons learned that Vijay and myself have both experienced in understanding how to architect better open banking infrastructure that is sensible, scalable, and takes revenue into account. And with that, Vijay if you don't mind taking a couple seconds to introduce yourself and giving us a quick overview of kind of Akoya's role in the open banking ecosystem, please.

Vijay Krishna: Yeah, of course. Hi Chris. And really nice to be here and good to be doing this with you. I've been been looking forward to this. Yeah. So my name is Vijay Krishna. I lead the product function at Akoya. Akoya was established in 2020. So we are around five years old largely as a service provider to various stakeholders within the open banking ecosystem in the us.

So on, on the data recipient and the data aggregator side. We are the conduit to over 4,500 financial institutions on our network. And we provide that through consumer permission, safe and secure APIs. We are we don't do screen scraping. We are purely only API based and permission based access network.

And on the on the other end of the spectrum we help financial institutions get off the ground, their open banking platform, their journey when they're trying to make secure data available to third parties. So that's the spectrum we operate in. We purely look ourselves, look at ourselves like a service provider, and excited to be here.

Chris Hansen: Awesome. Thank you for being here. It's great to do this with you. A pleasure to have you. For those of you in the audience who have not met Vijay, please feel free to take notes, reach out. He's seen quite a bit over his time at Akoya and beyond. Really thrilled to have him with me to today.

I won't dig in too far, just by way of introduction. Like I mentioned at the top of the hour, Nova Credit's an a credit infrastructure and analytics company. We work with people and providers like Akoya within our platform solution to help businesses and lenders grow responsibly by harnessing alternative data.

And so when we talk about open banking data, it's something we've been down the path for the better part of a decade in leveraging for credit risk analytics and more. And we've been, had the pleasure of working with many of you on this call working through what can open banking architecture look like?

Is this a compliance requirement? How can I create this revenue flywheel within my organization and actually bring key stakeholders along? And so really excited to, to dig into that with you all. Before we jump too far in just a couple quick reminders. Please feel free to submit questions through the q and a module in the on 24 platform.

We'll try to answer as many questions at the end of this webinar as possible. If we don't get to it, we will make sure that we follow up afterward. We can commit to that. And then this session will be recorded and on demand and available for you. So if you miss something, if you're taking notes, please feel free.

Put the pen down, engage with us and ask those questions that are rumbling around that are really difficult that you think your organization might be struggling with.

With that let's get into the first topic here. I think we just want to talk about the fundamental shift in the industry where we see a lot of institutions approaching open banking as a compliance exercise as opposed to a revenue opportunity.

Part of that is due to CFPB Section 1033. And also just the kind of give, get mentality that has, been in the industry to date, Vijay from your vantage point, working with institutions across the spectrum, how do you see a compliance first approach, potentially limiting business outcomes and, elephant in the room obviously is 1033. And what, where all that goes. How is the industry adopting to impending 1033 regulations and what are you hearing from lenders?

Vijay Krishna: Yeah, sure. Chris, from what we see right now, there is no way to predict what's gonna happen with the rule.

I'm not a betting man. I'm not gonna start now, so that's not a good place. So I think I'm looking at this as the two bookends that could happen. The most pessimistic scenario is that the rule gets vacated. The most optimistic scenario is that probably the rule is going to get delayed, right?

There are pending no litigation going on. So that's probably the most optimistic scenario. So the industry as such, the financial services industry is definitely looking and trying to absorb what is happening. It's happened in a fairly quick timeframe and trying to understand what their strategy looks like as a consequence of that.

But I think if you take a step back, the regulation by itself already looked at a staggered approach to adoption. The biggest financial institutions had the shortest timeframe because the regulator realized that they were already there. They were already making data available in a secure fashion to folks who were looking for it.

If you look at the tier two banks, I think most of them are already there or on the journey to making that data available in a similar fashion because they understand the risk of screen scraping much better than anyone else. And the importance of being part of the consumer journey in a safe and, secure manner they do recognize their fiduciary responsibility as the custodian of that data.

It's the tier three and below where the kind of compliance. Lens was allowing for the, the initiative to rise to the top of the prioritization table. That, that's where the challenges are. And I think that's where we are working with them to try and, create that business case.

The, we are, being consultative and trying to showcase to them not just the risk aspect, but also the value aspect of open banking and doing it the right way. So yeah, I think it's an exciting inflection point. But I feel like most financial institutions that we've spoken to. Their question is more about when it's not about if anymore.

So it's definitely a trend that's moving in the direction that we wanted it.

Chris Hansen: Yeah, resonates. And that's something I hear quite a bit from our large lending partners as well. And frankly, many institutions who have the data that falls under open banking starting with kind of core data and permeating out a little bit into what are the additional sources of data that our consumer might actually want to leverage across the financial ecosystem.

And that definitely pattern matches. It makes me think of a recent article that came out a couple days ago actually for Citizens in American Banker. Drawing a line in the sand publicly that, just because of a rural rollback doesn't mean that we're not gonna pursue open

The cat's out of the bag and the tipping point has passed. And we see that across many different organizations. Also on the other side of the coin, we see the revenue opportunity. We've seen enough vintages now to, go full scale and think from an enterprise perspective.

Let's architect this and scale it out. I would ask you, Vijay, how should from a technical architecture standpoint, how should somebody think about the key decisions separating out the revenue driven and focused implementations from compliance focused implementations?

Vijay Krishna: Yeah, if you take a step back and there is this entire debate around whether open finance, open banking in the US is, compliance driven or market driven.

And I think fundamentally the distinction, I mean if you think about it, we are largely market driven because it's grown organically. But the distinction I would make it is prob is probably the fact that it's consumer driven and it's consumer driven because of FinTech apps like yourselves. I. Who are providing a much better user experience to del develop much better outcomes for consumers.

Some startling facts out there, if you can wrap your head around it. FDX, which is the financial data exchange which is the quasi, standard setting body in the US for open banking has, they release their data from earlier this year and they have, they stated that over 114 million accounts are connected.

Yeah. The FDX APIs, if that's not staggering enough, that was a hundred percent jump over a year. So consumers are increasingly using fintech apps and they are connecting to them on an average. A consumer in the US is connecting their finance. Financial institution to three FinTech apps, right? And that's a data that's been proven.

And if you look at that momentum, I think the importance is that compliance is just one part of this entire equation. I. Being part of the consumer journey, being part of the consumer journey as I said, the fiduciary responsible party of their data is the part that the financial institutions need to look at, right?

By nature, compliance based approaches are limited in terms of the scope. They are there to do the bare minimum. We believe, at least at the coa, that I think what the regulation was intending was purely just scratching the surface, right? They were talking about checking data, savings data, lending data, not really the scope of what's available out there and what's possible.

Fair. It drives the primary use cases that are there in open banking today. But I'll throw out an example, right? Imagine you doing your taxes next year and connecting to TurboTax. Right now, the traditional option is to download all your, tax forms from your financial institution and upload them into TurboTax.

But if you're able to connect your bank account to TurboTax directly and them being able to get all of the data from you, there is value right there. It's saving the consumer time, effort, and money, and you as the enabler, as the financial institution enabling this experience become a far more engaging.

Participant in this flow, right? So I believe there is a lot more value out there to be derived. I think the financial institutions need to look at it that way. Compliance will lead to the decent outcomes, but the better outcomes stay outside of that realm and which is where, players like you are showing the way in terms of what that's possible.

Chris Hansen: Yeah. Yeah. A couple great pieces you touched on right there. I think FDX as one of the standards has been recognized in the industry and the growth there has been. Exceptional. At worst, I think there's quite a bit more now around the edges on what all data do we want to make available.

It's not, it's no longer are we going to make the data available. And usually when we talk to lenders, a lot of that is, everything Reg E Reg Z type related, we'll make that available. That's like our core principle, but how can we get more strategic with thinking about things like tax data and actually taking advantage of that across the ecosystem.

Is where we're starting to see, more and more conversations focused on things like tax investments other data elements that might be found within open banking, open finance. And so that's a really good crucial distinction that you're making there in terms of like how to think about those two things in tandem.

And really brings us to our first design principle in here which everybody sees on the slide here, which is building redundancy by design in our first kind of. Big lesson in that flexibility really is king in this industry. And thinking extensively goes hand in hand with that.

And early in our journey, we architected open banking solution that was a single data connection. No matter how elegant we made that single data connection there was always systemic risk that was actually brought forward. And so the most successful implementations we've seen incorporate redundancy by design.

And that's something, core to the thesis and part of our Nova Credit platform, but also we've just seen across multiple different technical architectures and implementations. From your perspective, Vijay, why do you think multi-source connectivity might be critical for enterprise scaling in the deployment world?

How does things like OAuth actually filter into that architecture? How should we be thinking about we know the data needs to be made available. How can we actually leverage a solution here in the market?

Vijay Krishna: Yep. So again, I'm going to link back to my earlier, point in terms of fintech's driving the adoption of open banking in the us.

And I think apart from the fact that they were, they're delivering much better consumer outcomes, what they've also done really is that they've delivered a much better user experience compared to the traditional alternatives. And that user experience always comes to bear when it comes to providing a solution.

And if you really look at it, having a single point of failure when it comes to the data that you need to power your application is a problem, right? You need to have the ability to be able to route to another network if one of your networks is down. But more importantly, I think on the other side of the spectrum, it allows, multi-sourcing allows you to do a lot more in terms of optimization.

Not all connections are the same. Some connections are gonna be better than the others for certain financial institutions. So based on uptime, based on availability, based on latency, there is a lot of smart routing that have, some of our evolved customers have started doing either in-house or through players who are able to provide that, right?

So I think that level of flexibility that multi-sourcing provides is sometimes missing in the single sourced approach. The only distinction I would make is that not all use cases are the same. So for instance, if you have a PFM app, which is a personal finance management app and it's a budgeting app, you can probably get away when there is a downtime by having a time sticker to say, listen, this was the last time it was refreshed.

But when it comes to, let's say, cashflow underwriting or buy now, pay later, where you are at the point of sale, you're trying to get a loan, you're trying to make that, loan happen. That's a, that's an inflection point. And at that point in time, the consumer experience matters and that's where the redundancy plays out its part.

And having the consumer go through that experience the first time they will come back and they will do it again. And as can be seen in all of the use cases that I've talked about. So there are inflection points, but there are far more important than certain use cases like payment use cases and lending use cases where the consumer is trying to achieve a certain objective.

And I think that is why. That's, that, that's the lens with which I would look at it.

Chris Hansen: Yeah. Need to get Vijay in front of more of our prospect conversations to help anchor the use case, lack of sensitivity if somebody, something does go down. I think in, in most of the use cases we work through I.

The paramount importance of that time sensitivity is there. And to Vijay's point, that's mostly because we're living and breathing in that space of hypersensitivity from a workflow and consumer journey perspective. We'll talk a little bit about that later in the session. But but yeah, Sage advice looking toward what's the actual application, let's look into the use case itself and understand where is this and is this not a necessity, but on the whole.

We've seen great results in our own platform, honestly, actually having redundancy by design, bringing through, one and a half to two times typical conversion amounts within that user experience. Because we're optimizing for ultimately conversion by virtue of coverage, latency and uptime.

And that's a critical ingredient in order to actually drive forward really a business case in your organization. For many of you on the call 'cause that will come up if it hasn't already. With your executive sponsors how do I think about downtime? What do I think about uptime?

How do I think about coverage and latency? And what specific technical considerations, Vijay, would you, should architects on the call keep in mind when designing for that kind of like multi-source connectivity?

Vijay Krishna: Yeah I think there are two that I would call out. The first one is, which part of the journey does.

Do you want to own? Do you want to own all of it? Or some of it? So I'll give you an example. There is the bank selector, or the bank picker, which is a fairly integral part of an open banking experience where the consumer searches for their financial institution and then links their financial institution to the app.

Right? That's a critical part of the journey. Now, if you are a single sourced, data recipient, then I think using whatever your aggregator gives you particularly works well. But if you are a multi sourced data recipient and you're looking to do optimization, you're looking to try and, do some sort of smart routing, then owning that experience becomes super important because that's when you're able to do the smart routing in the backend while the consumer is completely oblivious to what is happening in the front.

So that's one place where I would say just be very conscious about which part of the user experience you want to own and which parts you're willing to outsource. The second one I would say is more around data standardization. Again, the idea is to deliver a consistent user experience.

So if you're using with multi, multiple aggregators, the way you get that data in and you're able to standardize the data to deliver that unified experience, is important. As much as possible, if you look at aggregators who are more aligned to FDX standards. Versus their own bespoke standards will give you that opportunity to make sure that you can deliver the most standardized, approach on the other side for the consumer, which is what you're trying to drive at.

So those are the two, I would say mostly around the experience, which part of it you wanna own. And the second would be around the data standardization to make sure that you can, whatever you get in, you are able to deliver a unified user experience.

Chris Hansen: Yep. Yeah, the standard, the standardization really resonates. I know we talked about FDX a little bit earlier as one of the recognized standards, but that participation is integral for the industry to move forward. I can't think of. Any new kind of mountain moving initiative in the financial ecosystem that has not come with some version of standards to precede it.

And actually operating against that, seeing the growth of that, I think is, a great proof point that a lot of this is here. And it's really around like, how do I think about this from a more extensible perspective? And how do I actually bring those standards a across the board without kind of major re-architecting down the line?

And so that probably brings us to our second principle here, which is really just talking about platform-based architecture. We like to say platform architecture beats point solutions every single time. And most institutions the name of the game here is breadth and depth which is, how do I think about where to get started versus how do I think about how to architect that solution for getting started and scaling beyond.

And so when you're working with financial institutions, Vijay, how are you working with them to think about scaling beyond that initial business use case or initial pilot that they might be running within for us, whether that's, cards or personal loans or anything else.

Vijay Krishna: Yeah. Great question, Chris. I think from our perspective it's fairly natural for a financial institution to start with one particular use case, right? I think it's fair everyone, understands that. But I think what we do try and bring to their attention is what some of the larger financial institutions have done.

And and they have taken an organizational approach to it, which is interesting, which kind of also transcends to the architectural design. Which is the fact that they have a central unit that is looking at all data sourcing. It could be data in or data out, right? And that allows for a significant amount of, scaling it.

It makes sure that there is consistent application of risk. Third party risk management. Making sure that everything that they're doing is consistent across business units because their own consumers could be interacting with different parts of their own institution, right? So for them to have the same experience right across the board.

So what we've seen is that has worked really well because they then act as the conduit between the internal business units that are going to either use the data or share the data. As well as the third parties or the aggregator who are looking to get that data. So I think that is probably from an organizational perspective, the most important thing to look at.

Even if it's a small team, establish that team right upfront. The payoff actually really becomes later though. Comes in later though, right? I think the fact is once you have that kind of architecture and the design of the team, they're also the folks who are able to see all the data and they're able to clean insights across the organization.

And I think that becomes a very important point. As you mentioned earlier, the fact that as you get into monetization, as you get into things of, trying to drive value versus just manage the bare minimum, I think that's where those pieces come in, where that insights layer that is across the organization, allowing for engagement, cross sell, upsell, all of that becomes viable only when that happens.

So my, my, my single. Advice would be to look at it as an architecture, as an enterprise architecture. Even if you're starting with a single use case, how do you plug in other business units to make sure they can make the data available? And how can you make sure the data that you get in is something that can be absorbed by different business units within your organization?

I think that would be the fundamental principle that I would focus on.

Chris Hansen: Definitely. Definitely. And I know up on our slides here accompanying us. Here's just a kind of a generalized look very simplified view for all of these solutions architects on the call of, what a credit card architecture might look like, and really tip of the spear, what one front end or pilot might look like within one piece of your business or one business unit under the hood in the iceberg effect.

There's quite a bit of orchestration going on here but this might bring some sophisticated sophistication to your organization to actually have. A decision engine that works across an orchestration layer that can tap into different elements because you will, as you start going down this journey, find value across the board, whether that be in KYC and fraud from things like open banking data and architecting open banking solution for that.

As well as the actual, credit risk insights all the way through compliance and things like adverse action notice in our instance. And thinking extensively across this workflow will be really important. And even more critical than that will be stakeholder alignment. And so we hear that, day in, day out, help make my life easier.

Nova, please talk to me about how I can bring in the right key stakeholders. And so really looking at this and thinking about the concentric circles of opportunity within your organization. From a business case standpoint, and then on the backend talking about where you get started from a technical standpoint, but ensuring that you aren't boxed in that once it starts working, you have the ability to scale exponentially.

And I think, in most business cases, that's a critical need. So long as you can, iterate, figure out how to get started quickly. But in many of the large institutions who already have this kind of hub concept, you mentioned vj, a team that's dedicated toward making data in and out work. Has been very successful in our experience.

Yep.

I think one one other piece, and Vijay, we were talking a little bit about this was just really cashflow underwriting in general. We're playing deeply in that space and trying to see, what does this look like when starting to apply that type of a use case or a value prop.

I know you had a couple questions that you were floating to me Yeah. Previously, but how are you thinking about that?

Vijay Krishna: Yeah, so I think the one question that's been on my mind, which I think for a change maybe you can answer first, is cashflow underwriting really has the, is an incredibly interesting use case where financial institutions can start using open finance data for their own use and to deliver better outcomes to their own customers.

So I see that as a great use case and it does the other part of this use case. Touches on all the layers that we talked about, which is the data layer, the analytics layer, the, decisioning layer and all of those. So when you've worked with financial institutions as you've done, these implementations, what are the common mistakes that you see happening from an architecture perspective that you would bring to bear as part of your conversation for folks who are getting into the cashflow underwriting process?

Chris Hansen: Yeah. Yeah, it's a great question. It's part of the breadth and depth dance as we were talking about earlier, which is like, how do I get started and how do I think from a platform perspective, if you have a dedicated team, it means bringing that team in early. I have seen people silo their business case and their use case of architecture and build out what they believe will help be extensible across the organization with, without actually bringing along those key stakeholders.

And that can be a fatal flaw because the minute you go talk about technical resources for your project, if you don't own them you're now in a prioritization queue. And like bringing people in early to understand the impact across your business and across the loan life cycle has been invaluable.

Honestly I would say the other big one that we see is really just underestimating the consumer journey and journey design component. This is just crucial for consumer permission data. Product teams live and breathe this Nova Credit. We've had, nine years of experience designing consumer permission workflows within large lending applications.

And you must treat that as seriously as you treat your customer relationship and, understand what good incentive design looks like, right? Understand what clear communication and consent truly looks like. Each piece of your organization will want to pull pieces of that apart, understand it, evaluate it.

But thinking cohesively from the start will help you long term, even if it requires a little bit more upfront work to get started. And really that's really just thinking and kind of architecture and infrastructure as opposed to features and benefits within your one particular business unit. That a lot of people hear that and feel bogged down oh man, I gotta bring my entire organization across the line. There, there are efficient ways to do that and we have found the right ways to do that with the largest issuers and lenders in the world. And it involves both stakeholder management and also thoughtful architecture around how do you get started, how do you scale and how do you do that in flight when you're against, frankly, growth targets in this type of an environment.

Yeah. A quick plug. I know we're about half an hour into it, but a quick plug just to keep q and a coming into the dialogue boxes. We'll make sure we answer some questions here at the end, but we'll make sure we follow up at the very end as well to yeah, make sure we close the loop on any of those.

So please feel free to engage on the QA. I guess that we touched on this slightly actually in that, but the consumer workflow and consumer experience in, in our view at Nova, this is our third big lesson, is that experience itself is technical architecture. And as I mentioned before, you mentioned this, like thinking about what use case you're working on and how to think about that consumer experience.

Obviously you, you spend a lot of time thinking about consumer experience as well at aoa. How do you guys think about the relationship between kind of technical implementation and consumer experience?

Vijay Krishna: Yeah I mean for us consumer experience, because we are working with data, we are working with consumers.

Data I think comes with as I think, was it Spider-Man's uncle who said, with great powers come great responsibility. So I feel like that's where we are. I think the important piece to my mind is. The consumer experience of being a completely seamless experience for the consumer has to be balanced on the other side with providing the consumer the visibility and the control over that data, right?

I think sometimes we over rotate on one side, either on the control side or on the user experience side, compromising the consumer. So for instance, listen, I, there could be a mortgage use case where the consumer has taken the mortgage and has no reason to share the data anymore. To be able to give them, and this is the responsibility of both the FinTech side as well as the bank side, to be able to give the consumer the visibility and the control to switch off that connection when they don't need it, that the task is done. They no need to share the data anymore. So those are the pieces I believe should be architected into the solution itself rather than it being a bolt on later, because one business unit needs it and the other business unit doesn't need it. I think this level of visibility, which could come in the form of, a, in your online banking portal, having a place where the consumer can go and check all of the connections that they have, how long they've had those connections, and the ability to toggle them on and off, right?

I think that just increases the trust within the ecosystem. And just builds on that in the consumer's mind as they engage with these apps more and more. The second piece, and I think, we've touched about this a little bit. I think there is an importance in terms of consistency in terms of, the user experience.

I liken that to going to restaurant that you liked the pasta the first time, but it tasting completely different the second time and then the third time. And so frankly, that's not the place I would go back to. Essentially, how do you deliver that consumer experience? And that's where having proactive reactive alerts making sure timeouts are consistent and your uptime, et cetera, is clearly communicated to customers.

I think those pieces in terms of just being able to communicate with your customers and to alert them to what is happening on the platform and what step they're in, is I think, an important part of the architecture too.

Chris Hansen: Yeah. Yeah, that, that resonates a lot in our conversations as well. I'd say the restaurant analogy is a great one.

Means some of that consistency when you're going to one of your favorite places. And I think when we see it, there's three core principles that we see in that incentive alignment with the customer, ensuring they know exactly what is on the other end of going through this kind of experience.

Which, don't take that for granted. People need to understand exactly what they're doing within your application flow. Building trust which comes both with brand as well as communication and clear, concise communication as to like data privacy. Consumers are more and more aware of their data being used across the financial ecosystem, and so they want to be in control and understand that.

And then finally, technical reliability. Really can I ensure that if I'm doing this, it's gonna come through from a lender's perspective? Obviously that's a big point of feasibility, Vijay. Just even more tactically in the kind of design patterns. What have you seen work well for maintaining high conversion rates with while ensuring kind of robust data collection?

Vijay Krishna: Yeah. I think from our perspective, the first thing, and I guess for us it's even more evident when customers come to us is that, you need to take the conscious decision of how much of screen scrape data do you want to indulge in, right? As much as, but now a significant part of the US retail banking infrastructure is connected via APIs, screen scraping breaks often.

It doesn't allow for the biometric authentication that the consumers are used to when they're going to the financial institution and then leads to a drop in. Success rates or, conversion rates because the consumer's confused. They don't remember the user ID password anymore.

At least I don't. So I think those, I think that's a very important part. Having all of the access done through three-legged wat and secure APIs, I think is super important because then the, you're not holding onto the consumer's credentials. You're not increasing the risk in the ecosystem.

By capturing those credentials. And I think just on, it's a responsibility on both sides of the equation too, right? For the financial institutions to provide that three, three legged walkability and secure APIs and for the data recipients to be able to use them and the aggregators to use those, those more advanced versions of how to authenticate and get the data.

We talked about redundancy in terms of. Multi-sourcing. We talked about streamlining the consumer experience by not having too many screens, et cetera, as part of the overall process. I think the only last piece that we've seen really work out well is instrumentation. We've seen some of the better players really instrument this to death, and I've seen some of those dashboards.

It looks like, the flight control tower or something. It's insane because they're able to, because they ma conversion matters so much that they're able to route. Take the smart routing decisions on the fly and their instrumentations, give them the alerts to do that.

I think we've seen that a lot, right? I think the institution loading time connection, success rates data freshness, all of that kind of goes into that instrumentation and that kind of leads to smart routing decisions that. Leads to higher conversion rates. And finally I would say things like session optimization just based on the use case.

Some use cases are looking for 12 months or 24 months of transaction data. That timeout has to be different than just a balance check, right? Again, being sensitive of use case and how you manage your, architecture accordingly. So I think that's where it is. I don't know if you have any other. thoughts there.

Chris Hansen: No, it sounds like you've seen some of the Nova Credit dashboards and how have we look at this and approach this as well? I do. I just, I do see a question we'll save q and A for the end, but we'll hit it here. Where do the super aggregators fit and are they necessary that kind of falls directly into this world of is redundancy.

Necessary. I think short answer you would hear from both VJ and I on this call is yes necessary for a host of reasons, and in particular for specific use cases like lending and payments time sensitive applications and the ability to route on an intelligent basis can bring you fundamental results.

At the top of the hour, we talked about, 1.5 to two x baseline conversion rates when working with single aggregation versus across multiple different data sources. And that's the combination of things like, optimizing for latency and fall off coverage across different providers in the industry.

And then ultimately, converting that end user. You can actually, derive the analytics that you might need or the value that you might need out of that connection in a stable and secure way. And so that's where a coia has been leading the way with hosting OAuth only authentication there from a secure standpoint and a latency standpoint outperforming most of the market.

You know that intelligent routing capability is just critical and we see that user experience being a pretty key differentiator in the market.

Vijay Krishna: For sure. Yeah, I have one last question for you, Chris, before we move into q and a if that works. You've as no credit have integrated into many financial institutions of different sizes.

And you're unlocking opportunities that they probably didn't even realize they were unlocking when they started working with you. It starts off as an experiment and suddenly it becomes a fairly, important part of their their underwriting process, what are the key elements of the infrastructure, do you believe that need to be set right for this to happen?

Just as you walk in, what are the things that make you say, oh my God, I can get this done in a month or so, versus, oh my God, this is gonna take me six months to get it off the ground, because there's a lot that needs to get done. So any thoughts there?

Chris Hansen: Yeah, a lot of thoughts in particular around two things.

One, just open banking infrastructure and the kind of foundation around that. And I would say cashflow underwriting in and of itself. I would say from a infrastructure standpoint, moving from this proof of concept mindset into a production infrastructure mindset is exceptionally important.

And if you are actually operating on a proof of concept ensuring that you're bringing the team along and lining up accordingly from a technical feasibility standpoint, the architecture that will enable it across the org. So that means considering what other buss might be interested in this type of functionality, what use cases can this truly support?

Again, thinking in breadth when it comes to the business case and depth when it comes to getting off the ground from a technical standpoint. And so the institutions who have thought about this as foundational infrastructure and true open banking transformation and open finance transformation within their walls are the ones putting together real 1, 3, 5, 10 year plans.

Because of the impact they're seeing. It is extraordinary to understand that cashflow underwriting can bring double digit approval rates to your previous declines at the same marginal bat rate. Those are exceptional numbers. You talk to any risk officer I get to, I get the pleasure because we're, I still would say we're pretty early in these innings even though we've seen the adoption and the vintages of seeing risk officers get the results.

And understand, oh wow, this is so meaningful. I need to figure out how the organization can leverage this in a more real way. And so the people have really started looking broader in their organization, but focusing in on how do I deploy this in a real way, have been seeing a ton of impact and actually starting to move the needle for the industry.

The opportunity around API first infrastructure is huge. The opportunity to build trust through OAuth mechanisms like the ones Sequoia brings to bear is huge. And the ability to create cross-functional teams that actually understand data in and data out and can leverage that kind of conversation across their organization has been, a huge benefit in actually gaining adoption within the organization.

And frankly. Outside of the walls. Last point I would make on that is the vintages for many people in the industry. There have been people, working on cashflow underwriting in particular for years. And it's the worst kept secret at this point in the industry. Nova is obviously, singing high praises here across the board, but, you've seen more and more players start to sing the same tune, which actually starts to tip the adoption. It is not no longer an isolated conversation where we're seeing these results and trying to talk to the market. The market is telling us, we know this exists, the value is there. How can I think about this in a thoughtful way?

And so we're excited to lean into that. It's a, we've been working on it for a number of years, and so excited to tip that adoption, the time really is now to be working on that. Especially when it comes to enabling open banking data at your own institution to be a part of that on a data out basis.

The next 12 to 18 months are gonna be pretty critical for many people to take advantage because of the speed at which adoption is occurring in a competitive way. And so we're excited by that. Obviously that means my team at Nova and the Nova team is very busy. I'm certain that you are as well, dj.

But the kind of catalyzing cashflow adoption has been a real boon in the last year.

Vijay Krishna: And the halo effect that you don't talk about, which I think is something we need to recognize is the fact that you are expanding the pie. Again, something that financial institutions are desperate to try and see how they can get more people under the tent.

How do they do that? And financial inclusion as a consequence of that, right? I think that those become super important. As an immigrant who came into the country who had no, credit score, I can tell you the pain it took me to get there. I wish I had the opportunity to, do something like what you guys are doing at that point.

Chris Hansen: Yeah. Yeah, definitely. Definitely. I will just be conscious of time. We'll move to q and a here. I see one, one question at the top, Vijay, maybe I'll shoot this to you first. For open, for institutions just starting on their open banking journey which principles should they really prioritize First, we talked about three core principles here.

We talked about redundancy by design, platform architecture, consumer experience, someone getting started, where should they be focusing their energy?

Vijay Krishna: Yeah, I would say platform architecture is the right place to start because you are going to ask for investments from the organization and that investment is the thing that should last you, but at least five years in terms of, future proofing yourself.

You don't want to go back and ask for more because you get it, got it wrong. Of course, the other two inform it, redundancy informs the architecture, the consumer experience. Definitely informs the architecture but the consumer experience could be limited to the first few use cases, which may be myopic when you think about the broader scope of what's possible from a timeframe perspective.

So I think that's probably where I would say that architecture is probably the top of the house.

Chris Hansen: Yeah. Yeah. Architecture architecture, both technically and from a business case perspective, I think then brings the organization along. It's really how do you think about this?

Across the org? From a technical standpoint and then from there, how do you build out? I, that resonates with me. I'd probab I'd probably say the same out of all three of those, honestly. To ensure that you're anchoring correctly what this will look like strategically for your business over the next time horizon.

I've got another good question here that Vijay, again I'll shoot your way just on data normalization. What's your view around data normalization? I think you see better than anybody how messy some of this data can be across different fis. How do you think about that and how that data can be leveraged in a more unified way?

Vijay Krishna: Yeah I think it's a problem that we've seen. We, it's a problem we've encountered, our customers have encountered, it's a tough sell to a financial institution to tell them to reformat, to make sure it's standardized, it's not a revenue making opportunity it's something that they're doing because they think it's the right thing for the consumer, but it might be a bridge too far for a lot of them to actually indulge in a lot of standardization, as much as we would like to.

So that's where the intermediaries come in. The aggregators come in. And some of the most evolved, data recipients do it themselves because they're trying to drive towards the user experience. But the aggregators like koya do take all of the data and try and obfuscate the, the issues that are there across the banks and try and normalize them into a kind of standardized format, right?

So I think there's a long way to go. I think still in the industry. And, but there has been significant progress over the last, I would say, six to 12 months, where I think the data recipients are able to, at least our data recipients, are able to get off the ground within probably three weeks at some times.

Because we've done a lot of that work, which they would've had to do if we hadn't done it.

Chris Hansen: Yeah, that's right. Yeah. We see a similar co component there in terms of how do we move and expedite speed to market. Obviously there it will take time from a standardization component, but, players like Akoya Nova are working to, take a platform approach to those problem statements and bring them to bear in a real way so that people can actually, leverage the data in a more unified way instead of building on a one-off basis. That will take a long time.

There's certain, probably some of the most the fastest moving conversations we have are people who have started down that journey themself and then found themselves working through partnerships to move faster. Yeah. That, that I'm sure you, I'm sure you hear that too, vj. One, one last question.

I'm I'm happy to take this one best framework to measure ROI on open banking. I think this kind of goes back to top of the hour when we were talking about think about that particular use case for us, whether that be something like cashflow underwriting income verification, looking at your marginal population of declines or no file thin files.

People who are commonly not using credit in a traditional way, and therefore bank data can be very orthogonal to credit data and help get them above the line in a responsible way. I would size some of that population on an initial use case very tactically. I would look at the results of this open banking architecture, both, what will the conversion look like ultimately through that experience.

And then what will my approval rate look like to eventually take a net new origination rate. I would multiply that by your your typical MPV for a customer, an LTV for them. And then I would look toward your other business units to start building out what this really looks like.

And once you have that on the revenue side, I think on the the cost side of the equation, there's an architecture question, which Vijay alluded to, think platform and what this can look like truly. To make sure the ROI is there it almost certainly will be in the amount of gain that you can get across different use cases here.

And then, also start to think about in your particular use case, what else can you be doing on the consumer journey design? You could you could architect the best solution on the backend as possible, but if you don't get consumers to thoughtfully work through the consumer open banking experience, you'll never get the data to realize the benefit.

And so you, you must consider product as a function of that kind of ROI exercise and what the user journey experience is gonna look like. I know we're running out of time here, but I just wanna say thank you Vij, for joining us today sharing your insights. And thank you to the audience for the excellent questions.

I see a number of questions filtering through, so we'll make sure we capture those, reach out to you all. Please feel free to reach out directly to VJ or myself. At our respective organizations to answer some more questions, but I think key takeaways here are fairly clear. Successful open banking architecture moves beyond just compliance into thinking how can this actually drive revenue outcomes for me?

And the best way to start working through that is to build flexibility and run redundancy by design approach enterprise wide platform architecture from an infrastructure standpoint. And then never forget about the consumer experience because that is pinnacle. It will be your customer of your institution that is extremely critical for you all and ultimately determines technical success.

So for those interested in continuing the conversation we're both happy to jump in, have conversations with you all. We also have a cashflow underwriting Summit. Nova Credit has our second annual in September of this year. Please feel free to reach out to me. Directly and follow up with Nova.

If you wanna dig into more of these conversations, hear from some of the industry leaders talk to the Quaia team as well. And we'll be thrilled to have you there. So thank you all for joining and we'll speak with you all very soon. Cheers..