softtrust.ai

Smarter Lending Decisions. Lower Risk.
Faster Turnaround.

Accelerate your credit lifecycle with intelligent, AI/ML-driven credit risk evaluation — from application intake to post-disbursement monitoring.

What Is AI Credit Risk Analysis?

AI Credit Risk Analysis is an end-to-end intelligent system that automates credit evaluation and scoring using advanced Machine Learning, Optical Character Recognition (OCR), and decisioning logic. It enables faster, more accurate, and bias-free loan processing for banks and financial institutions.

Whether you're evaluating salaried professionals or self-employed individuals across India, the USA, Mexico, or the UAE — our system adapts to your risk policies, regulatory frameworks, and document requirements.

How It Works – Intelligent Workflow

1. Application Intake

Accepts both online and offline applications through portal, app, or physical branch.

Validates identity, income, and credit history through APIs and document cross-checking.

Based on the score, the system flags applications as Auto-Approve, Manual Review, or Reject.

2. Document Upload & Extraction (OCR)

Converts structured and unstructured documents into usable data formats.

Uses LightGBM-based ML engine to compute a dynamic creditworthiness score.

Monitors repayment behavior, bounce patterns, and risk shifts in real time.

What Powers the AI Engine?

This is not black-box AI — it's explainable, accurate, and designed for real-world lending.

What Does It Evaluate?

Pre & Post Disbursement Risk Control
Before Disbursement
Risky profiles are
flagged early
01
Officers see “Go / Review / Stop” signals
02
Faster turnaround and lower error rates
03
After Disbursement
Monitors delays and
missed EMIs
01
Dynamic risk scoring for proactive recovery
02
Ensures full loan lifecycle compliance
03

Key Benefits for Banks & NBFCs

Accessible across devices with intuitive interfaces.

Reduce TAT from days to minutes

Eliminate human error in risk evaluation

Data-driven, explainable outputs

Stay alert to shifts in borrower behavior

Ideal Use Cases