Saurav's Profound AI Rep
Saurav's view on product decisions shows how he tests the problem before committing to a build.
Saurav Mahapatra
Edges
Shaping Fraud Control Systems
Saurav shapes fraud products around the operating choices that make a model useful: what it scores, where controls apply, and how legitimate customers retain access. At Tide, he led the product design for APP fraud controls and rebuilt a legacy risk engine around fresher patterns and broader signals. His work connects model outputs to due diligence, progressive access, review flows, and measurable detection quality.
Spotted in 2 Stories
Market-Specific Risk Design
Saurav adapts risk products to the signals, regulations, and product constraints of each market. At Tide, he used local business-registration signals in Germany, category controls in France, and an India-specific heuristic model rather than reusing UK logic. The result is a risk approach that matches the available evidence and the customer experience of each product.
Spotted in 2 Stories
Sequencing Product Investments
Saurav sequences product investment by testing the underlying problem before committing teams to large builds. At Flipkart, he reframed separate homepages into targeted discovery modules. At Tide, he prioritized an India-specific risk model over reusing a poorly fitting UK model. He uses user behavior, model performance, strategic importance, and engineering scope to make the trade-off explicit.
Spotted in 2 Stories
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Saurav Mahapatra
About Me
Saurav Mahapatra is a product leader with experience across fintech, risk, and e-commerce. He builds data-informed products that balance fraud controls with a usable customer experience.
At Tide, he leads risk products for KYC, shaping fraud strategy, ML risk engines, and onboarding controls across the UK and newer European markets.
He led an APP fraud risk model and its operating controls, contributing to fraud volume falling from about £15 million to about £5.5 million over a year.
At Flipkart, he led homepage work that used cohort behavior and experimentation to improve discovery, engagement, and conversion.
Saurav Mahapatra
I start by asking whether we really need this build, then test the assumption behind it.”
Saurav Mahapatra
On product decisions