RSelf-directed research2 min read
Designing an AI-first financial ecosystem for India's next 100M users.
A trust-first AI co-pilot that guides financial decisions without taking control — built on ethnographic research into how India actually relates to money.
- Role
- Strategy & Research
- Scale
- 100M+ target users
- Approach
- Trust-first AI
- Year
- 2025
Challenge
AI is moving from assisting banking apps to mediating money decisions, which makes trust — not capability — the design constraint.
Strategy
I ran a 72-participant behavioural study through a 10-lens ethnographic framework to map where people want AI to act and where they want to stay in control.
Results
A validated set of trust-first principles for AI-led financial products.
overview
Overview
As AI moves from novelty to infrastructure, financial services in India are heading toward a moment where AI won't just assist a banking app — it will mediate financial decisions directly. That shift raises a harder design question than usability: when should an AI act on someone's behalf, and when should it simply inform?
This research initiative explored how AI should integrate into financial decision-making for the next 100M Indians coming online — not by digitising existing banking processes, but by starting from how people actually think about and relate to money.
research
Research
The study combined behavioural research with a structured ethnographic framework to understand money as a cultural and psychological subject, not just a transactional one.
- 72 users interviewed across a cross-section of financial behaviours and comfort levels with digital tools.
- A 10-lens ethnographic framework examining India's relationship with money through historical, cultural, psychological, and technological dimensions.
- Mental model mapping to understand how users actually conceptualise financial decisions, rather than how banking products assume they do.
principles
Design principles
The central design tension was trust versus control: users wanted AI's help interpreting their finances, but were wary of AI acting autonomously with their money. Understanding exactly where that line sits, and for whom, became the core design input.
- AI trust dynamics — mapping when users want AI to act versus when they want to stay in control of the final decision.
- Validated concept design — bridging aspirational product thinking with grounded, tested user feedback rather than designing for a hypothetical ideal user.
- Core principle: the AI's role is guidance, not control — surfacing insight and options, never silently acting on someone's behalf.
outcome
Outcome
The result is a set of validated design principles for AI-integrated financial products — grounded in how people in India actually relate to money, not in how a global fintech template assumes they do.