E058 - Cash Flow Data at The Marketing Stage - How Engine by Gen & Prism Data Are Helping Marketers Unlock Cash Flow Underwriting

So now that we kind of understand how this works, I'm curious how you all thought about maybe the business case or the use cases from both the lenders and the publisher side.

So this is a question for both of you.

Maybe David, I'll hand to you first.

But like, how do you...

How do you think lenders view this? How do you think publishers view this? What are some of the key benefits that they brought to the table?

Yeah, I mean, it's fun to say, but yeah, I'd say cashflow decision and cashflow underwriting is definitely what's hot in the streets these days.

Many of our partners are very interested in this.

And just to even kind of tee off of what James was saying a moment ago, using our Spark platform to either host models with inside of our ecosystem, using the Prisma attributes, but also our A-B testing capabilities, our partners are now able to build these sort of champion challenger type experiments with inside of our ecosystem to validate that.

So with that, I really see partners testing and iteratively expanding what their buy box is while keeping risk constant or even more improved.

So really using this as a opportunity to test and learn, be able to try different attributes, different thresholds, and see really what fits both at an upstream function as well as an eventual application function.

Ultimately, we're in the business of trying to drive the most number of high quality leads.

And this is really an opportunity to take a totally different lens than we've been able to historically.

James, anything you'd add?

Yeah, I think when we talk to our customers or even prospects, it is really all about we can help you find more qualified customers, make more competitive offers for them, and we're excited to bring this further upstream and expand that buy box there.

It's assessing these kind of attributes and analytics further upstream and We've seen a lot of success with our customers in terms of kind of, I think that the risk is very limited here, you know, because we're just adding in an additional data source.

We're not asking you to replace something and to come back to something you said earlier.

We do see the biggest lift from our clients when they are combining cash flow analytics with traditional credit data.

Yeah, no, I see the buy box expansion.

I think it seems very clear it could benefit, I mean, all three parties, the consumer, because some folks aren't going to have access to credit that now may qualify.

the lenders, the publishers, I think both benefit from that.

Do you think lenders will use this information to perhaps change their pricing or line assignment on someone they might've already approved with credit data only? And now maybe they conclude that the customer's even more credit worthy than they thought and therefore they could price it at a lower rate.

Is that a dynamic you expect to see?

I think at some point, yes, but also I think for ongoing servicing experiences, a lot of our partners have that ongoing relationship, ongoing link where they can identify that.

I think where things get interesting is we see the same consumer many times, especially depending on what that product vertical is.

So using the engine network, we're able to identify, hey, this is somebody that already belongs to a given lender.