Company
Hi, I'm Anat, Founder of FinOptima. A simple yet uncomfortable truth inspired me to start this company: fraudsters collaborate more effectively than financial institutions do.
Growing up in Kherson, Ukraine, a warzone nowadays, instability and constant change shaped my childhood. This experience wired me to think in terms of patterns, resilience, and human behavior. Which is exactly what fraud is about.
My father worked in intelligence, KGB intelligence, to be exact. So while I grew up in the chaos that was the birth of a new nation after the fall of the Soviet Union, he was always preparing me to overcome any obstacle.
“You don't have to be the smartest – just the one who doesn't stop.”
— My father, after a failed math test
That moment stuck with me. And while I didn't know it at the time, that upbringing gave me a unique lens, learning the psychology of fraud long before I ever stepped into a boardroom.
I started my first business at 19, helping people move across borders, solving high-stakes problems like language, documents, and access. I later moved to the US and worked across finance: commercial real estate, investment banking, private equity and corporate development. These paths taught me how systems often fail people, and how institutions operate, scale, and manage risk. But the gaps frustrated me over-complexity, fragmentation, and worst of all, a slow adaptation to emerging threats.
The real inflection point came during my Master's in FinTech at NYU Stern. I conducted research with over 70+ banks and fraud leaders, and one thing became clear: financial institutions don't necessarily lack tools, they lack the connections between them. Every bank and credit union had multiple vendors across identity, voice, and transactions, but none of them worked in unison. Meanwhile, fraudsters were operating in coordinated networks, sharing data and evolving faster than any single institution could keep up with.
And thus, FinOptima was born.
We've built a collaborative fraud intelligence layer that allows financial institutions to share signals without revealing sensitive data. Instead of isolated detection, our interoperative system monitors live interactions in real time, actually keeping pace with evolving fraud techniques, not reacting to them after the fact. We're shifting the model from siloed protection to collective intelligence.
Our goal is simple: to give smaller and mid-sized financial institutions the same level of defense sophistication as the largest banks – minus the complexity.