Data Science Use Cases for Lifestyle Banking

From International Center for Computational Logic

Data Science Use Cases for Lifestyle Banking

Talk by Boontawee (Meng) Suntisrivaraporn
Abstract: Traditional banking concerns itself with risk understanding, credit underwriting, cash need, liquidity, etc. Data science and machine learning have proved useful in banking businesses to mitigate risk while targeting the right customers with cash need. In this talk, we will explore a lifestyle side of banking that goes beyond the traditional realm and delves more into alternative signals to customers needs. We will see example data science use cases that have been successfully implemented in banking business at Siam Commercial Bank.