No single test is foolproof. Imagine a detective solving a murder case. They never rely on a single piece of evidence — not just the fingerprints, not just the CCTV footage, not just the witness testimony. It’s when multiple independent pieces of evidence align — the DNA matches, the phone records place the suspect at the scene, and the financial transactions show motive — that they can build a solid case. Each piece strengthens the others. It’s a classic case of triangulation.
In lending, we can apply this principle by cross-referencing multiple data points to establish the authenticity of a claim. Let’s take the case of personal loans, a segment that has had rapid growth. Here are a few facts: 14% of borrowers falsify employment status on loan applications, 12.2% of Early Payment Default rate are linked to suspicious employment pattern, 18% of applicants use disposable emails effectively worthless.
Traditional verification involves calling HR departments or requiring multiple documents, creating friction in the customer journey.
Smart triangulation offers a better way. By using just data inputs of an applicant a phone number and company email you can cross-reference multiple independent signals:
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Is the employment record active in EPFO?
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Does the company email domain match the claimed employer?
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Does the phone number’s age and usage pattern suggest legitimacy?
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Is the company email domain ownership sketchy?
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Is the company email available and accessible?
Each signal alone can be faked, but faking all signals simultaneously, making them perfectly consistent, is exponentially harder.
Triangulation can apply across loan products. For business loans, triangulating GST returns with bank statements and supplier invoices can flag revenue inflation. For vehicle loans, cross-referencing chassis numbers with insurance databases and can prevent multiple financing.
