Credit Scoring Automation for National Lending Provider

Customer:
Major Consumer Credit Institution

Business Challenge:

Manual or outdated scoring models slowed down application approvals.
Legacy systems lacked transparency and adaptability to changing risk policies.
Customer experience was hindered by long processing times and inconsistent decisions.

ESI LABS Objective:

Automate and improve credit scoring accuracy and speed, while maintaining full explainability and compliance with regulatory frameworks

Solution Delivered:

- Implementation of a rules-based credit scoring engine integrated into the lending workflow.
- Use of machine learning models for behavioral analysis, combined with deterministic BRMS logic for transparency.
- Custom configuration of:
  - Score Calculation Engine: Generates explainable risk grades using hundreds of variables.
  - Decision Rules Layer: Applies organization-specific lending criteria, thresholds, and exceptions.

Duration: 5 months
Phases: Requirements Gathering → Modeling → Integration → Compliance Testing → Rollout

Results Achieved:

Achieved intelligent price governance with transparent, explainable logic

85%

of applications processed in real time

35%

reduction in approval cycle time

40%

Reduce manual reviews

Conclusion:

ESI LABS helped this financial organization build a modern, explainable credit scoring engine that increased speed, improved consistency, and met high compliance standards—creating value for both customers and the business.

VP of Risk and Analytics, National Lending Provider

Our legacy credit scoring processes were a bottleneck. ESI LABS delivered a system that’s fast, explainable, and adaptable. We now process 85% of applications in real time, with full transparency. It’s a major leap in both customer experience and regulatory alignment.

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