Fortified – 411: Assisting in managing loans whilst analysing, detecting false and synthetic identities and predicting any potential loan frauds

Abstract

"The increasing rate at which bank loses its profitability and liquidity due to various reasons which contribute to loan fraud is alarmingly high. This eventually poses a threat on the asset quality, survival of banks and the whole economy of the country. Extensive research and literature findings revealed that increasing Non-performing Assets in Sri Lanka can be due to poor credit appraisal methods, poor management of credit facilities, inappropriate structuring, and wrong selection of borrower by the bank and mis-management of funds, poor equity contribution, diversion of funds and poor managerial knowledge by the customers and other environmental causes such as government policies, taxation laws and changes in consumer behavior. Thus, this research combines historical loan data based on machine learning to forecast and predict fraud by discovering hidden patterns and enable banks to take timely actions to the Non-Performing Assets."