Trustingsocial

Real-time application-moment risk signals derived from computer vision on borrower onboarding: the Vision Score (a 0-100 score) computed from biometric and behavioural signals captured during loan or account application, sold as an independent present-moment risk read that complements historical bureau scores. The underlying asset is an accumulated corpus of onboarding biometric captures (selfie/video frames, liveness and document images) joined to the resulting risk score AND, crucially, to downstream loan performance flowing back from lender clients — a score-to-realised-default paired dataset at application granularity, in a market where most borrowers are thin-file. Market context cited in the company's own analysis (belonging to the national bureau, NOT to this company): the CIC database at 66 million borrowers and 413 million tradelines, consumer loan NPL of 5.4% vs 3.1% for the banking system overall, consumer loans of ₱3.4 trillion in H1 2025 (+21.2% YoY), and ₱853 billion of BNPL/personal-loan-app bookings in 2024.

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Coverage

Universe, instruments and categories.

Industry: Non-Bank CreditApplication Software
Instruments: equities
Categories: Alternative

Dataset card

Type: not stated
Format: Multimodal — biometric image/video frames and onboarding telemetry with derived numeric scores (Vision Score 0-100, model features) plus tabular application/score/outcome records; delivered as a live score via API into lender decisioning stacks rather than as bulk files
Volume: Not published for this entity. Bounding inference: the market it scores into is large and fast-growing (BNPL and personal-loan apps booked ₱853 billion in 2024; consumer loans ₱3.4 trillion in H1 2025), so an active application-scoring vendor plausibly processes millions of applications per year, each leaving an onboarding capture, a Vision Score and — where clients feed performance back — an outcome. Request Philippine application volume, biometric capture count, and how many applications have a linked repayment outcome.
Users: N/A — B2B scoring API serving lenders; no consumer user base (the consumers it observes are applicants on its clients' funnels). Philippine client count not published. Bounding inference: a local arm of a multi-country alternative-credit group, order of dozens of lender/fintech/BNPL clients (inferred from an 18-person Taguig team plus the group's regional footprint). Request Philippine client count and monthly scoring volume.
History: 5 years
Update frequency: not stated
Growth: Active — current-cycle thought leadership published against BSP Second Semester 2025 data, a live product page for the Vision Score, and an active Philippines-specific site with a marketing automation stack; content arguing a market gap (double-digit consumer delinquency despite wide bureau coverage) is a demand-creation motion typical of an expanding vendor.
Launched: not stated
Delivery: not stated
Entity mapping: not stated
Sample: not stated
Point-in-time: not stated
Licence: not stated

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