Machine learning application in loan default prediction

AK Tiwari - JournalNX, 2018 - neliti.com
JournalNX, 2018neliti.com
Abstract   In Todays world, most of world population has access to banking services.
Consumers has increased many fold in last few years. For the banks, risks related to bank
loans has increased especially after The Great Recession (2007–2012) and job threats due
to automation and advancement in technologies like artificial intelligence (AI). At the same
time technological advancement enabled companies to gather and save huge data which
represent the customer's behavior and the risks around loan. Data Mining is a promising …
Abstract
  In Todays world, most of world population has access to banking services. Consumers has increased many fold in last few years. For the banks, risks related to bank loans has increased especially after The Great Recession (2007–2012) and job threats due to automation and advancement in technologies like artificial intelligence (AI). At the same time technological advancement enabled companies to gather and save huge data which represent the customer's behavior and the risks around loan. Data Mining is a promising area of data analysis which aims to extract useful knowledge from tremendous amount of complex data sets  Non-Performing Assets (NPA) is the top most concerns of banks. The NPA list is topped by PIIGS (Portugal, Italy, Ireland, Greece and Spain) countries
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