Investments

The problem

There is a very large universe of mutual fund schemes and listed equities in India, and most investors choose between them with little more than past returns and a friend's opinion. A product that shows everyone the same list of top funds ignores the one thing that matters most: the same fund can be right for one person and reckless for another. MAHIR Invest, a SEBI-registered investment advisory firm, wanted recommendations matched to each investor. The challenge was to do that without overwhelming people, and without hiding risk behind jargon.

How I approached it

I started by studying the Indian mutual fund and equity advisory landscape: how competitors present recommendations, what SEBI norms require, and where investors lose trust. That research shaped a roadmap built on quality and transparency rather than feature count. From there I defined the recommendation experience around four inputs, the investor's risk capacity, risk appetite, time horizon and financial goals, so that every suggestion could be traced back to something the investor had actually told us.

I wrote the PRDs and user stories with compliance in mind, covering suitability, disclosures and how risk is communicated, so each recommendation arrives with its rationale and risk context rather than just a name and a return number. Working daily with engineers, designers and research analysts, I ran sprint planning and stand-ups to keep delivery predictable.

The outcome

The personalized recommendation platform went from requirements to launch with compliance-aware, predictable delivery every sprint. It gives an investor a clear answer to the question they actually have: what fits me, and why?

What it taught me

In a regulated product, trust is the feature. Explaining why something is recommended matters as much as what is recommended.