07 · Product & Strategy
IndusInd Protect: Bancassurance Product Case Study
Turning insurance inside a bank's app from a one-time transaction into an ongoing protection service.

5
competitors benchmarked
3
personas from 60+ survey responses
15.0
top RICE score: 1-click renewals
Overview
A product case study for IndusInd Protect, an in-app insurance layer covering discovery and comparison, unified policy management, digital claims, and AI-assisted support. Built from primary and secondary research through personas, RICE prioritization, user flows, a clickable prototype, and a phased go-to-market plan.
The problem
The retail insurance experience is fragmented. Customers struggle to understand what they are covered for, manage policies scattered across channels, track renewals, and navigate claims. Engagement effectively stops at purchase, so insurance feels like a one-time transaction rather than an ongoing protection service.
The approach
In-depth interviews and a 60-respondent survey across age, income, and digital-savviness segments mapped the friction, and a benchmark of five competitors (PolicyBazaar, Acko, Digit, ICICI Lombard, SBI General) located the white space: none pairs banking data with insurance in one view, and post-purchase trust weakens at exactly the moment claims begin. Three personas set the brief, RICE scoring replaced gut feeling in ranking the feature set, and the winning journeys were mapped into wireframes and a clickable prototype. A go-to-market plan sequences the rollout along the technology adoption lifecycle.
Highlights
- ▪Product vision: make protection something customers feel every month, not something they buy once and forget, by turning the bank's existing knowledge of their life into proactive coverage
- ▪Positioning built on the asset digital-only insurers cannot copy: branch relationship managers reframed as a named claims concierge tied to the existing banking relationship
- ▪RICE ranking put a centralized policy repository with 1-click renewals first at 15.0, well ahead of the conversational AI assistant at 1.40, inverting the obvious AI-first instinct
- ▪Life-event triggers (vehicle loan, home purchase, upcoming travel) generate pre-filled quotes, removing the search and form-filling steps entirely
- ▪Gamified Protection Score and Policy Health Check surface coverage gaps rather than waiting for the customer to discover them
- ▪Omnichannel claims: AI assistant for routine queries, escalation to a named relationship manager for the final mile, with real-time status tracking
- ▪42-month go-to-market split into an initiation stage (launch, validate, build trust) and an expansion stage (scale markets, strengthen distribution, drive mass adoption)
Stack
Primary & secondary research · Personas & problem statements · RICE prioritization · Wireframes & prototype · GTM strategy