Client: A FinTech Startup Specializing in Lending Services
Industry: Financial Services
Service: AI & Machine Learning – Predictive Analytics
Challenge
The startup lacked a robust system to assess credit risk in real-time, relying instead on static credit reports. They needed an AI-powered engine that could provide smarter, faster decisions to reduce loan default rates.
Solution
CVK Global Tech built and deployed a real-time machine learning model using Amazon SageMaker and custom Python-based data pipelines.
- Aggregated and cleaned multi-source customer data (transactional, behavioral, credit history)
- Built classification models using XGBoost and Random Forest for credit risk scoring
- Deployed models on AWS SageMaker with a REST API endpoint
- Integrated model with the client’s loan origination system
- Set up model monitoring and retraining triggers using SageMaker Pipelines
Results
- 24% reduction in loan default rates within 90 days
- 60% improvement in approval speed, from 3 hours to under 30 minutes
- Model accuracy reached 92% on test data, updated weekly
- Improved customer satisfaction and reduced manual reviews
“Their AI team brought technical depth and clarity. Our platform is now smarter, and our decision-making is faster and more reliable.”
— Founder & CEO, FinTech Client
