FUND MASTER

Fund Master - Financial Parameters page
Fund Master - Loan Status Predition Page
Fund Master - Workflow

Inspiration

Interaction between customer and Relationship Officer and finally customer getting to know approval chances of a loan is a time consuming process.It takes a week– a month for at least knowing whether we are capable of receiving the applied loan. Inspiration came from the thought of reducing this time frame to minutes.

What it does

Borrower can use FUNDMASTER to know his/her chances of approving the loan by submitting the financial ratio parameters along with the basic data such as Loan Amount, Collateral Value etc. This is done by learning previous approved/declined loan application status and financial ratios of past customer applications and finally, system will predict chances of the loan approval in minutes.

How we built it

Currently we tried to consume 3 APIs from FFDC (Parties-B2E, Financial Spreads-B2E and Financial Ratios-B2E). Parties API was used to create a new entity. Financial Spreads API consumed the financial parameters provided and finally used these parameters to calculate financial ratios. These Financial Ratios were consumed by Financial Ratios API and plotted back in FFDC. This financial ratio data set was fed to an AI/ML engine, which did a comparison study and predicted the loan application status. K Nearest Neighbour algorithm was used for the same.

Challenges we ran into

Dataset preparation is one challenge we ran into. Financial Spreads availability in FFDC would give more enhancement to the status prediction in Fund Master