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From Cricket Fields to Credit Scores: The Personal Journey of Anshuman Chowdhury
Home > Top Stories > From Cricket Fields to Credit Scores: The Personal Journey of Anshuman Chowdhury
Global Banking & Finance Review®
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Photo Courtesy of: Anshuman Chowdhury
Some careers begin in boardrooms. Others start with a bat and a ball. For Anshuman Chowdhury, the early years revolved around cricket grounds in India, chasing precision, control, and rhythm. He never imagined that his real calling would unfold far from the pitch, inside the code of systems most people never see. But the threads were always there: focus, intuition, and a desire to help others win.
Over time, that instinct turned technical. He studied engineering, became a full-stack developer, and moved into product leadership at some of the world’s largest tech companies. At Visa, Amazon, and Meta, he led high-stakes product launches across global platforms. Then, life changed. A family death, a layoff, and a long, difficult period of reflection forced him to step back. As he grappled with uncertainty, he began reaching out to people he didn’t know—across cultures, communities, and continents—listening closely to their needs. Again and again, he encountered the same theme: some of the world’s most complex and ambiguous problems were affecting nearly half the global population, and traditional systems were failing them. That’s when the first outline of A3Z AI began to take shape.
A3Z AI was not born out of a corporate directive or a market gap discovered in a strategy session. It emerged from thousands of conversations. Chowdhury didn’t start by building. He listened. He spoke with Uber drivers in the remote suburbs of the US and UK, real estate agents in Bangalore, and young athletes from the Caribbean, India, and even the United States. No matter where they were from, he kept hearing the same story: financial systems were shutting people out.
“I met so many people who weren’t irresponsible or unqualified,” he says. “They just didn’t have the right kind of paperwork. And every ‘no’ felt like the world saying they didn’t belong.”
That kind of exclusion didn’t feel technical. It felt personal. Chowdhury had worked on systems that served billions, but now he wanted to build one that recognized the billion people who had been left behind. A3Z AI became his answer. The platform began with a question: What if trust came first? What if credit scoring were based not on historical debt, but on current behavior and contextual reliability?
The company’s behavioral credit model pulls from nontraditional signals about how people manage money daily, how often they meet obligations, and how they behave in financially unstable environments. It does not require a traditional credit file to evaluate someone’s potential. In early pilots, the algorithm achieved four times the approval rate of bureau-only models, offering new access to people who had been repeatedly denied by conventional banks.
Success for Chowdhury does not mean scaling up alone. Throughout his career, he has mentored over 50 startup founders and product managers, helping others find their footing in fintech, property tech, artificial intelligence, and web-based commerce. His style of mentoring is direct, informal, and grounded in his own setbacks.
He does not deliver lectures or write manifestos. He listens, asks difficult questions, and helps people think clearly through ambiguity. His favorite tool is not a framework but a phrase: “You won’t always have clarity, but you can stay kind.” The advice has echoed in Slack threads, coaching calls, and investor pitches from Delhi to Palo Alto.
His support goes far beyond pep talks. He shares metric models developed at Meta, deployment playbooks tested at Visa, and go-to-market plans fine-tuned through years of hard lessons. But he never positions himself as a guru. He insists that building trust, whether with users, teams, or partners, is the real product.
That mindset is baked into A3Z AI’s rollout. While the pilots initially began in proptech, Anshuman ultimately pivoted—refocusing on the deeper problem he wanted to solve: building trust at a foundational level. Fintech is the current focus, with plans to expand quickly into proptech and sports. Chowdhury’s team has developed a modular architecture that allows partners to assess creditworthiness and identity with minimal friction—without subjecting users to invasive data practices.
Personal experience shaped every decision Chowdhury made after 2020. The loss of a close family member left him raw. Being laid off from Meta stripped away his safety net. But instead of pulling inward, he turned those setbacks into direction. He began documenting conversations, sketching out data models that responded to what people needed rather than what institutions preferred.
“It felt like everything I’d done before — the algorithms, the launches, the user flows — were pointing me toward this,” he says. “I’d been part of massive systems. Now I wanted to build one for people who never even got a login.”
That kind of ambition rarely makes headlines. It involves slow work, late nights, and many rewrites. Chowdhury’s approach is methodical. He builds prototypes, pressure-tests logic, and insists on explainability in every model. He filed a provisional patent in 2025 for A3Z’s dignity-first algorithm, not for marketing advantage, but to protect the idea that credit scoring can respect its users.
The result is a company with modest revenue but growing traction. Pilots are running with partners in India, Kenya, the United States, and the United Kingdom. A3Z is attracting attention from regulators, NGOs, and technologists interested in responsible artificial intelligence, identity access, and inclusion.
But for Chowdhury, the goal is simpler. He wants a young athlete in Lagos to access travel funds. A single mother in Mumbai is trying to secure her first lease. A bright student to qualify for a loan without a guarantor, while preserving their parents’ dignity. He wants people to be seen as more than the paperwork they lack. His work isn’t about legacy. It’s about clearing a path for those still waiting outside the gate.
A credit score is a numerical representation of a person's creditworthiness, based on their credit history, including payment history, amounts owed, and length of credit history.
Financial inclusion refers to efforts to ensure that individuals and businesses have access to useful and affordable financial products and services, including banking, loans, and insurance.
Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems, which can perform tasks such as learning, reasoning, and problem-solving.
Mentorship is a relationship in which a more experienced or knowledgeable person helps to guide a less experienced or knowledgeable person, often in a professional context.
Fintech, or financial technology, refers to the integration of technology into offerings by financial services companies to improve their use of financial services.
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