Baselayer Raises $20 Million to Automate Fraud and Risk Checks for Banks

Baselayer Raises $20 Million to Automate Fraud and Risk Checks for Banks

Baselayer, a New York startup that uses artificial intelligence to vet businesses and hunt for fraud on behalf of banks and government agencies, has raised $20 million in Series A funding, the company disclosed on August 3, 2026. The round was led by investors including Koro Capital and M13 and brings the three-year-old company's total equity funding to roughly $47 million.

The financing lands squarely in the middle of a rush of capital into AI-native compliance and risk tooling. The same day Baselayer's round surfaced, the AI compliance platform Dili announced a $15 million Series A backed by Khosla Ventures and Y Combinator, and the sales-coaching startup Othello disclosed a $6.85 million raise, according to AlleyWatch's daily funding report. Together they underscore how quickly investors are betting that machine learning can take over the slow, manual review work that has long bogged down financial services.

Baselayer was founded in 2023 by Jonathan Awad, Timothy Hyde, and William Slessman. The origin story has become part of the company's pitch: Awad and Hyde, its CEO and CTO respectively, were unable to open a business bank account in the wake of the regional bank failures of early 2023, leaving them unable to pay bills or vendors while a manual review dragged on for more than a month. Rather than wait, they set out to rebuild the process themselves, drawing on Hyde's background building and selling a machine learning company to a Fortune 500 firm.

The product targets a persistent pain point in banking: Know Your Business, or KYB, the process by which institutions verify that a commercial customer is legitimate before onboarding it. Traditionally that work can span days or weeks of document collection and manual checks. Baselayer's platform uses AI-generated knowledge graphs to authenticate government registrations, build risk profiles at onboarding and for ongoing monitoring, and flag suspected fraud through machine learning predictions and a shared fraud-intelligence network that pools signals across participating institutions.

"We automate manual reviews, authenticate government registrations, create risk profiles at the time of onboarding and for ongoing monitoring, and prevent B2B fraud via machine learning predictions and fraud sharing infrastructure," Awad has said of the platform's approach.

That fraud-sharing layer is central to Baselayer's thesis. The U.S. Treasury Department has flagged the lack of data sharing between financial institutions as a structural weakness in the fight against fraud, and Baselayer pitches itself as one of the few systems built to pool that data and issue real-time alerts, effectively leapfrogging legacy credit bureaus. The company says it can assess and predict the risk of a prospective business customer in seconds rather than days.

Traction has scaled quickly since the company emerged from stealth in May 2024 with a $6.5 million seed round that was five times oversubscribed. Baselayer now says its technology reaches well over 1,900 financial and government institutions, with its APIs embedded in platforms that manage tens of millions of accounts. Early adopters have included the business banking platform Rho and one of the top-five loan infrastructure systems in the market.

"Working with Baselayer has been a game changer for us," said George Remennik, Acting Chief Compliance Officer at Rho. "Baselayer helps us accurately verify business applicants and get new Rho customers up and running on our platform significantly faster, while also supporting the integrity of our world-class compliance operations."

The company plans to use the new capital to scale its platform and expand the features of its generative AI risk models.

Why It Matters

Fraud is an enormous and growing tax on the financial system, costing global banks an estimated $500 billion in 2023, and the rise of generative AI has made deception cheaper and more convincing to manufacture. Synthetic identities, forged registrations, and shell entities are easier than ever to spin up at scale, which puts pressure on the same institutions to detect them faster.

That dynamic has turned RegTech, the market for regulatory and compliance technology, into one of the more durable corners of fintech investment even as broader startup funding has stayed cautious. Baselayer's bet is that the defense has to be automated too: if fraudsters use AI to attack, banks need AI to screen every applicant in real time rather than relying on manual reviewers working from stale bureau data. The shared-intelligence model also hints at a broader shift, from every bank fighting fraud alone to a networked defense where a signal seen at one institution can protect the rest. If that model holds, the winners in this category may accrue advantages that compound with every new customer and every new fraud pattern they observe.

What to Watch

The immediate question is whether Baselayer can convert reach into deep, recurring revenue. Being integrated into platforms that touch tens of millions of accounts is a strong distribution story, but the company will need to show that banks pay for and rely on its scores rather than treating them as one signal among many. Watch for named enterprise banking contracts and evidence of pricing power.

Competition is also intensifying. Incumbent bureaus and identity-verification giants are racing to bolt AI onto their own KYB stacks, and the flood of freshly funded rivals, from Dili to a widening field of compliance startups, means differentiation will hinge on data quality and the strength of the fraud-sharing network. Finally, regulators are still shaping the rules for AI-driven decisioning in financial services; how Baselayer handles model explainability, bias, and the accuracy of its automated risk calls will determine whether banks can safely lean on it for decisions that carry real legal weight.