Global Structured Finance Ltd (GSF) provides loan eligibility evaluation for banks, trusts, credit unions, and private lenders. Expertise includes cash flow analysis, Treasury balance sheet management, liquidity risk analysis, and hedge effectiveness analysis.

Opportunity:

They aimed to develop an AI-centric platform that can evaluate loans, assess credit risks, manage assets and liabilities, and generate reports.

Approach:

AutoML technology has been used to develop an AI-driven web platform. A Django backend and Angular front end were used to implement the solution. It also involves developing Machine Learning (ML) algorithms using H2O AutoML to calculate the Probability of Default (PD), Expected Loss (EL), Loan Given Default (LGD) for loan portfolios and many other ML models for other portfolios like ALM, FP & A. Tableau was used to develop Vintage curve reporting and all other reports.

Measurement metrics:

Vector Analytics is a web-based tool that allows the financial institutions to identify and reduce the default risk with greater accuracy than current default prediction tools by up to 15-20%

Results:

Financial institutions have converted fragmented, manual loan analysis workflow processes to automated reporting and analytics by implementing Auto Machine Learning algorithms. Auto Machine Learning has helped the company grow its customers, allowing it to efficiently generate revenues for the company. In addition, reduce the loss by lowering default customers and increasing the intake of eligible customers.

“Sound knowledge of the team helped build perfect Ai product.” – Global Structured Finance LTD