The Honest Answer: How Mastercard Made Its Data Work for Refugees
After millions of Ukrainian refugees arrived in Poland, Mastercard built a free tool called Where to Settle. It combined anonymised transaction data with government statistics to give each refugee a personalised shortlist of cities where they could realistically afford to live. The mechanism: use proprietary spending data to answer a hard human question, not to run an ad. This case is one of the patterns inside jugnu's Kosh.
The tension it resolves
Mastercard holds vast data about where money actually flows, but brands rarely share that intelligence with the people whose spending created it in the first place.
The challenge it solved for Mastercard: How can a payments brand use its proprietary data to do something concretely useful for people in crisis, in a way that builds genuine trust rather than just brand sentiment?
The mechanism
Aggregate proprietary transaction data with open government statistics, then surface the output as a personalised, anonymous decision tool that answers a specific life question without collecting sensitive user data.
After nearly 10 million Ukrainian refugees crossed into Poland and major cities became overcrowded, Mastercard built a free digital tool called 'Where to Settle'. It combined Mastercard's anonymised transaction data with figures from the Polish Central Statistical Office to show refugees the cost of living across Polish cities of different sizes. Refugees filled in an anonymous form about their situation and needs, and the tool returned a personalised shortlist of the most promising places to build a new life.
Where this applies in India
This principle sits closest to any Indian business that processes transactions or usage at scale and quietly holds a map of real behaviour. A fintech or UPI payments player could use merchant transaction patterns to help first-time migrants in a new city find affordable neighbourhoods before they commit to renting. A telecom provider could surface which micro-markets actually have reliable data speeds for gig workers choosing where to base themselves. A logistics or quick-commerce platform could show new small retailers which pin codes have genuine unmet demand, based on order data rather than guesswork.
FAQ
What is the Where to Settle pattern?
Aggregate proprietary transaction data with open government statistics, then surface the output as a personalised, anonymous decision tool that answers a specific life question without collecting sensitive user data.
Which brand proved it works?
Mastercard, in financial services (Poland). jugnu's Kosh tracks 327 such patterns across Indian and global brands.
How do I apply this to my brand?
Run your brand challenge through jugnu. It diagnoses the tension underneath your problem, checks whether this pattern fits it, and builds ideas on the patterns that do.
This is the story. Every Kosh card also carries a transfer layer: the consumer insight underneath, the principle that moves across categories, and the boundary conditions where it breaks. jugnu applies that layer to your brand when it builds ideas.
Wondering if this pattern fits your challenge? Run it through jugnu and find out.
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