About
Hello, I’m Nripesh.
I’m an engineer who builds the systems fintech depends on: the pipelines that have to be right every time, the models that decide whether money moves, and the data layers everything else is built on.
The path here
I studied mathematics and statistics at Grinnell College, with a detour through the Budapest Semesters in Mathematics. I started out in data-science consulting, building predictive analytics for Fortune 500 retailers, where I learned to turn a vague business problem into something a model can actually answer.
In 2021 I joined Chipper Cash, a cross-border payments company, as a data scientist. The job was supposed to be analytics. It quickly became infrastructure. I led the company’s move to dbt and designed the core financial data models that still power its analytics, dashboards, and internal tools, and I ended up running the data-transformations practice that more than fifteen engineers build on.
From there the work moved steadily closer to the things that cost real money. As a tech lead on risk and growth I designed and shipped fraud-detection systems: a model that scores every new user for fraud risk, real-time transaction scoring, account-takeover defenses. Today, as Head of Risk Intelligence and Automations, I own fraud, compliance, and risk-data systems across seven markets, leading a small, AI-first team that has been replacing third-party vendors with in-house systems we fully understand and control.
What I’ve built
Most of my favorite work has the same shape: take something slow, manual, and vendor-dependent, and turn it into a system that is fast, owned, and observable. A compliance platform that replaced a six-figure vendor contract. An onboarding-fraud model that blocks thousands of fraudulent referrals a day. An in-house identity stack (document verification, liveness, sanctions screening) that retired roughly $1.4M a year in vendor fees. A pipeline that reads partner fraud reports, understands them with an LLM, and acts in seconds instead of half an hour.
How I think about building
- Get the data layer right first. Everything downstream inherits its quality.
- Prefer systems you can open up. A vendor black box you cannot inspect is a liability dressed up as a convenience.
- Automate the judgment, not just the clicks. The value is in encoding the decision, not scripting the busywork.
- A noisy alert is worse than no alert. Every false positive spends trust you do not get back.
- Write it down. Explaining a system clearly is also how you find its flaws.
Outside the work
I think a lot about risk and uncertainty, which spills over into chess and poker. I follow football closely and recently fell in love with pickleball. I read broadly and eclectically, more flâneur than scholar. And I write: essays on the systems behind fintech and the craft of building, and, increasingly, on the books and ideas I cannot stop turning over.