Income verification might not be the sexiest part of fintech, but it's arguably one of the most important. What's the point of having a slick lending app if you can't tell whether borrowers have the means to pay you back?

I recently caught up with Kirill Klokov, CEO of Truv, to get his take on how lenders should think about income verification in 2025. He shared his hard-earned lessons that every lender should internalize.

1/ The Waterfall Strategy Is Everything

Here's a stat that should make every lender's product team nervous: 35% of borrowers drop off when presented with bank credential verification (like Plaid).

The worst part? Those dropoffs might actually be your best customers – the ones with other options who leave at the first sign of friction.

Kirill's solution is elegant: the waterfall approach. Start with consumer-permissioned data (lowest cost option), then fall back to instant databases (more expensive, but lower friction), then finally manual document review (the failsafe). As he explains, "You want to subsidize the instant database cost with a very cheap solution upfront."

The key insight: present the low cost option first, but always give borrowers an escape hatch. A simple "skip verification" button can dramatically reduce funnel dropoff while still capturing the data you need from willing participants.

2/ Most Verification Vendors Are Selling the Same Commodity

This one might sting for vendors in the space, but Kirill doesn't mince words: "If you actually go ask five aggregators who they're using, you would realize that everybody under the hood is using roughly the same dataset."

The differentiation isn't in the underlying data – it's in the intelligence layer on top. Can you rebuild pay stubs from bank statements using machine learning? Can you spot expense patterns that indicate risk? Can you handle the complexity of gig workers, multiple income streams, and variable compensation?

For financial institutions evaluating vendors, this means looking beyond coverage statistics and focusing on the analytical capabilities that turn raw data into actionable insights.

3/ Fraud Is Everywhere (And Getting Worse)

Want to buy a fake pay stub? Google "pay stub" and add "$7.99" to your search. You'll find plenty of options that look completely legitimate. And you’ll find them on the first page of Google, not the dark web!

This is the reality lenders are operating in, and it's only getting worse with AI-generated documents. As Kirill notes, "If you run risk scores on your existing documents, most likely you'll find a bunch of fraud."

The solution isn't better document analysis – it's getting data directly from the source. Payroll data is much harder to fake because "you have to go through multiple cycles of somebody paying taxes on your behalf. No fraudster would do that."

Check out the full conversation with Kirill Klokov on The Free Toaster Podcast.

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4/ Pressure Test the Sales Pitch

Sophisticated lenders don't just take vendor claims at face value – they demand proof.

Kirill's advice: "You want to actually ask to run the back test analysis on your own data." Give vendors your last 10,000 transactions and see how they perform. Then verify those results using their API.

This data-driven approach cuts through marketing fluff and gives you real insight into which vendor will actually improve your business metrics. Too many lenders skip this step and regret it later.

5/ The Complete Product Wins

The future belongs to vendors who can handle 100% of your traffic, regardless of employment type. W2 employees, 1099 contractors, government workers, gig economy participants, self-employed borrowers – each requires different approaches and data sources.

As Kirill explains, building a complete product is like airlines beating railroads: "Airlines were in the business of transportation. Railroads were always in the railroad business."

Lenders don't want to piece together five different vendors for different borrower types. They want one partner who abstracts away all that complexity and just delivers clean risk signals.

6/ Financial Alignment Matters More Than You Think

Here's the most interesting development in the space: some vendors are moving away from per-transaction pricing toward success-based models.

Truv's "per closed loan" pricing means they only get paid when loans actually fund. This creates economic alignment – the vendor's success is directly tied to the lender's success.

For lenders, this eliminates the anxiety around verification costs eating into margins on low-conversion funnels. For vendors, it requires much tighter integration and partnership, but also demonstrates real confidence in their value proposition.

The Bottom Line

Income verification is quietly changing.

The vendors that survive won't be the ones with the best coverage statistics or the lowest per-transaction costs. They'll be the ones that best understand the core problem: helping lenders make better underwriting decisions while minimizing friction and fraud.

For lenders, the message is clear: think bigger than just verifying income. Look for partners who can help you understand borrowers holistically, handle the full complexity of modern income sources, and align their success with yours.

With AI making document fraud easier and the gig economy making income patterns more complex, the problem just got harder. And with vendor prices rising in the category (so we hear in the industry rumor mill), the stakes involved in getting this right may be higher than ever.

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About Us

Welcome to The Free Toaster! The newsletter for marketing pros at fintechs, banks, and lenders. 

Inspired by the free toasters banks used to give to each new customer, we’re here to help you acquire more customers at scale. We deliver fresh news, data, and insights to help you acquire more customers, minus the breadcrumbs.

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Carlos Caro is the founder of NMG, an agency that helps lenders build affiliate programs.

Nick Madrid the co-founder of Ghostmode, a media company that builds Newsletters, Podcasts, and communities in high-value B2B niches.