Trusting Social

Trusting Social

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Trusting Social is the Vietnamese AI company whose credit-scoring models help banks in emerging Asia assess borrowers without traditional credit files.

Overview

Founded by data scientists with roots in Vietnam and Singapore, Trusting Social builds machine-learning credit models from telco, behavioral and alternative data, letting lenders score first-time borrowers accurately. Its platform supports consumer lending at scale for banks across Southeast Asia and India, powering millions of credit decisions. The company’s models are designed for financial inclusion โ€” extending credit safely to people legacy scoring cannot evaluate.

Key Features

  • Alternative-data credit scoring for thin-file borrowers
  • Telco and behavioral data modeling at population scale
  • Real-time decisioning APIs for lending flows
  • Portfolio monitoring and collections optimization
  • Bank-grade deployment across Asian markets
  • Financial-inclusion mission with measurable impact

Pricing

Trusting Social partners with financial institutions under commercial agreements priced by decision volume and scope.

Who Is It For

Banks and lenders in Southeast Asia and India that want to grow consumer credit safely among underserved segments.

Use Cases

Trusting Social serves lenders extending credit to underserved segments.

  • Scoring first-time borrowers from alternative data
  • Real-time lending decisions at scale
  • Portfolio monitoring and collections optimization

Getting Started

Financial institutions partner through a structured onboarding: data integration, model calibration and parallel testing before live decisions.

Results to Expect

More approved good borrowers at controlled risk โ€” measurable financial inclusion with portfolio performance to match.

Implementation and Support

Partner onboarding includes data integration, model calibration and parallel testing so lenders validate decisions before live risk exposure.

Limitations to Keep in Mind

Alternative-data models require regulatory acceptance per market, and performance depends on data-sharing agreements.

What Users Say

Lenders report approving more good borrowers at controlled risk in thin-file segments.

Who Gets the Most Value

Consumer lenders across Southeast Asia and India pursuing inclusive growth.

Final Thoughts

Excluding thin-file borrowers is easy and costly. Trusting Social’s alternative-data scoring expands the lendable population without reckless risk. For Asian lenders pursuing growth with discipline, parallel testing will make the case quickly.

Bottom Line

Alternative-data scoring grows the lendable population responsibly. Lenders in emerging Asia should run parallel tests and let performance data decide.

FAQ

Is Trusting Social free to use?

No. Trusting Social works with financial institutions commercially through partnership agreements.

Does Trusting Social offer an API?

Yes โ€” scoring and decisioning are delivered through APIs integrated into lenders’ origination systems.

How does Trusting Social compare to alternatives?

Against bureau scores, Trusting Social’s alternative-data models approve more good borrowers with controlled risk in emerging markets.

๐Ÿš€ Visit Trusting Social Official Site

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