We built Lendiro because 45 million Americans couldn't get a fair shot at credit.
I spent three years in credit risk at a regional bank watching the same thing happen every week: applicants with strong bank account histories declined because FICO had nothing to say about them. Those people weren't bad credit risks. They were invisible ones. That's the problem Lendiro solves. — Omar Hassan, CEO & Co-Founder
The Team
Two people who've worked the problem from both sides
Omar Hassan
CEO & Co-Founder
Before Lendiro, Omar spent three years in credit risk modeling at Bancorp Southwest, where he built and deployed underwriting models for consumer installment products. He saw firsthand how bureau-dependent decisioning was leaving creditworthy thin-file applicants behind — particularly recent immigrants and gig-economy workers whose bank accounts told a very different story than their empty FICO files. He left in early 2025 to build the alternative.
Priya Mehta
CTO & Co-Founder
Priya previously led the data infrastructure team at Meridian Analytics, a transaction data firm serving mid-size banks across the Southeast. She architected the feature engineering pipeline that now powers Lendiro's real-time decisioning — turning raw bank transaction streams into the 47 model inputs that drive every decision. Her focus on latency (median <1 second in production) is a direct response to her experience watching checkout-abandonment caused by slow underwriting at point of sale.
Founding Principles
What we built this on
Credit decisions should be explainable
Every Lendiro decision comes with the factors that drove it — ranked and nameable. This isn't just good engineering practice; it's the only way to support adverse action compliance and build lender trust in a new model. A score that can't be explained shouldn't be trusted.
Alternative data must be used fairly
We use cash-flow signals because they predict creditworthiness — not because they're convenient. Features that could serve as demographic proxies are explicitly excluded. We test for disparate impact on validation data and make those results available to qualified integration partners. Fair lending isn't a checkbox; it's a constraint we designed around from day one.
Speed matters at the point of sale
A credit decision that takes 30 seconds is a UX failure at checkout. Our production latency target is sub-second median, because we've seen what decision latency does to conversion rates at BNPL platforms. The model has to be both accurate and fast — that's a harder engineering problem, and it's the one we solved.
Where We Are
Dallas, Texas — a deliberate choice
We're headquartered in Dallas because it puts us inside one of the densest regional bank and credit union ecosystems in the United States. Texas is home to 26 state-chartered banks and 500+ credit unions — many of them mid-size community lenders who bear the thin-file problem acutely but have been locked out of the cash-flow decisioning tools that only enterprise vendors have offered. That's our market. Being here matters.
We also value being in a timezone that works for both East and West Coast fintech partners — and the lower operating cost of Dallas lets us stay capital-efficient while we build.
Contact
Dallas, TX 75201
Partnership inquiries and API access requests: fill in the form or email us directly. We respond within one business day.