Credit Scoring Engine · Risk API

FinOS Credit ScoringExpand the data universe beyond bureau — score thin-file applicants accurately in under 500ms.

AI-powered credit scoring — real-time risk assessment from multi-source data, delivered via API for banks, lenders and fintech partners.

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ML MODELeCreditScore< 500msCIC BureauBank DataBehavioralAlt Data750SCORECredit Score OutputRisk ClassificationReal-time · API · Gini > 0.65
One API · instant credit decision
Bureau DataCIC Vietnam
Bank HistoryWith consent
AI/ML ModelGini > 0.65
Credit Score0 – 1000 range
Risk BandLow · Med · High

Key Features

Aggregate richer data, score in real time, monitor drift — and stay explainable for regulators.

01

Multi-Source Data Aggregation

  • Credit bureau data (CIC Vietnam)
  • Transaction history (with user consent)
  • Behavioral and alternative data
  • Social and digital footprint signals
02

Real-Time Scoring Engine

  • Sub-500ms score delivery
  • Score + risk band + explanatory factors
  • Configurable scoring models per lender
03

AI/ML Models

  • Gradient boosting + neural network ensemble
  • Continuous model retraining on new data
  • Explainable AI — reason codes per decision
04

Decisioning Rules Engine

  • Layered rules on top of model score
  • A/B testing for credit policies
  • Champion/challenger model comparison
05

Monitoring & Drift Detection

  • Score distribution monitoring
  • Model performance dashboards
  • Alerts for population shift
06

Regulatory Compliance

  • Explainability for adverse action notices
  • Fair lending monitoring

How It Works

From applicant identifier to credit decision in one API round-trip.

01
INPUT

Submit

Lender sends applicant identifier (CCCD, phone) via API.

02
AI

Aggregate

Credit Scoring queries data sources (with consent).

03
KNOWLEDGE

Score

AI models compute score and risk band.

04
SENTIMENT

Apply Rules

Decisioning rules applied on top of model score.

05
HANDOFF

Return

Score + recommendation + reason codes returned via API.

06
ANALYTICS

Decide

Lender makes the final credit decision.

Use Cases

Consumer Lending

The Challenge

Manual credit assessment for personal loans takes days, with underwriters reviewing paper documents and calling references — driving applicant drop-off rates above 40% in Vietnam’s digital lending market. Slow decisions also inflate operational cost per loan while borrowers simply choose a faster competitor.

How eCreditScore Helps

eCreditScore aggregates CIC bureau data, bank-statement signals and behavioural indicators in a single API call, returning a score, risk band and reason codes in under 500ms — enabling lenders to deliver a fully automated decision at the moment of application. The decisioning rules engine lets credit teams configure policy guardrails without engineering involvement, so approval strategies can be tuned in hours not sprints.

Business Impact
< 2 secEnd-to-end credit decision from application submission to approve/decline
↓ 40%Reduction in manual underwriting touchpoints per application
24/7Automated decisioning available around the clock, including outside branch hours

Frequently Asked Questions

Yes — reason codes are returned per decision and the model supports adverse action notices.

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