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Product Manager ยท Hero FinCorp ยท IIM Kozhikode

I build products from the ground up โ€” and the numbers tend to follow.

0โ†’1 builder across B2B merchant platforms, GenAI collections infrastructure, and B2C UPI growth. NBFC-scale, compliance-first, metric-driven.

โ‚น2.34Cr
Annual cost saved
10K+
Partners on platform
1.8X
Dealer revenue YoY
90%
Platform adoption
900K+
YT views built from 0

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From circuit boards to credit decisions

I started as an EVM Engineer at Bharat Electronics Ltd, standardizing workflows across five critical manufacturing operations and cutting defect rates by 33% across 2.2 lakh+ EVMs. I was honored by the Government of Punjab for delivering zero-defect execution during Assembly Elections '22 โ€” work where there was no margin for "close enough."

An MBA at IIM Kozhikode redirected that discipline toward products โ€” including scaling a content platform to 900K+ views and โ‚น2L+ in revenue from scratch, entirely through audience research and growth experimentation.

Today at Hero FinCorp, I own 0โ†’1 product builds across B2B, B2C, and AI-driven collections, in an NBFC environment where every feature has to survive both a growth target and a compliance review.

Ship 0โ†’1, then scale relentlessly
My biggest wins โ€” Merchant App, agentic voice infra, bounce predictor โ€” all started with no existing playbook.
Research before PRD, always
User research and journey mapping before writing a line of PRD โ€” that's how a 30% churn reduction gets found.
Every feature ships with a metric
Adoption, MAU, TAT, cost โ€” if it can't be measured, I haven't finished defining it.

Case studies

B2B Merchant App โ€” 0โ†’1 Platform Launch

0โ†’1 BUILD 10K+ PARTNERS 6 LOBs GENAI
80%
Digital penetration
1.8X
Revenue YoY
4X
DAU growth
+
The Problem

10,000+ distribution partners across six lines of business had no single platform to originate and service loans digitally โ€” operations leaned heavily on offline and manual workflows with no consistent way to track adoption or churn.

My Role

End-to-end product owner โ€” roadmap, PRDs, and shipping โ€” for the 0-to-1 launch of the Merchant App.

Key Decisions
  • Shipped 15+ features across all six LOBs against a single roadmap, preventing fragmentation into six separate builds
  • Built a GenAI document-extraction tool against Vahan APIs to automate RC validation โ€” 60% faster TAT, 20% fewer errors
  • Ran user research and journey mapping with partners to diagnose churn drivers; translated into first-principles PRDs
  • Designed a Rewards & Loyalty program with personalized offers to drive retention, not just acquisition
Outcome

80% digital penetration, 90% adoption, 70% MAU, 30% lower partner churn, dealer revenue 1.8X YoY, DAU up 4X, 80% lower query volume, 50% better FTR via GenAI servicing chatbot.

B2B Merchant App screenshot

AI-Powered Collections โ€” Agentic Voice & Bounce Prediction

0โ†’1 AGENTIC AI RISK MODELING COST SAVINGS
โ‚น2.34Cr
Annual savings
81%
Cost reduction
15d
Early risk signal
+
The Problem

Collections relied on manual tele-calling at scale, with no early signal on which accounts were likely to bounce โ€” agents were reacting after the fact rather than prioritizing before risk materialized.

My Role

End-to-end product owner for the AI-reimagined collections initiative, from voice automation to risk modeling.

Key Decisions
  • Delivered a 0โ†’1 agentic AI voice infrastructure automating tele-calling operations at scale
  • Built an EMI-bounce predictor using 360ยฐ customer profiling to forecast risk 15 days in advance
  • Engineered smart contact sequencing across omni-channel workflows for precision targeting
Outcome

โ‚น2.34 Cr in annual cost savings (81% reduction), ~20% of collection risk mitigated early, 40% better targeting, 99.99% reach accuracy.

AI Collections dashboard screenshot

B2C Customer App โ€” UPI Launch & Engagement

GTM GROWTH 10L+ USERS UPI
โ‚น10M
Daily GMV
33%
Revenue lift
30%
Organic installs
+
The Problem

UPI was a new surface with no adoption pattern, and organic growth on the broader app was flat without a clear engagement or referral strategy.

My Role

Product owner for UPI launch and the engagement/referral charter, including GTM strategy and metric design.

Key Decisions
  • Driving IPL-linked UPI GTM campaign via Delhi Capitals sponsorship, targeting 1Mn+ transactions
  • Defined success metrics and ran A/B testing for the Engagement Charter, iterating on cohort data
  • Designed referral program for 10L+ users โ€” converting existing users into an acquisition channel
Outcome

โ‚น10M daily GMV and 10K daily transactions in month 1 at >95% success rate; organic installs up 30%; โ‚น1.5 Cr monthly organic growth; 33% revenue increase.

UPI app screenshot

Strategy Internship โ€” Omnichannel Servicing

SERVICING FUNNEL OPTIMIZATION 50+ TOUCHPOINTS
40%
Lower staffing cost
25%
Less call abandon
+
The Problem

Customer servicing leaned heavily on staffed channels with no vernacular support, and 50+ touchpoints across the journey hadn't been audited for friction.

My Role

Strategy intern designing an omnichannel servicing interface and auditing the end-to-end customer journey.

Outcome

โ‚น0.36M+ savings, 40% lower staffing cost, 20% higher acquisition, 10% higher retention, 20% better CSAT, 25% lower call abandonment.

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