Many credit scoring techniques have been used by banks to build credit scorecards. Among them, logistic regression model is the most commonly used in the banking industry. In the banking industry, logistic regression, linear regression, linear programming and classification tree have been used to develop credit scorecard systems. Logistic regression is the most commonly used […]
Logistic Regression in Credit Risk Analytics Read More »
The finance and banking sector is one of the most data-rich industries in the world, generating vast amounts of data on a daily basis. The traditional banking institutions have been collecting customer data for decades, but with the emergence of fintech companies, the competition has become more intense, and banks are increasingly turning to data
Data Analytics in Finance and Banking Sector Read More »
Banking analytics is the use of machine learning techniques and artificial intelligence in customer data to make decisions in banking domain. Banking analytics is a management tool that gives insight on current performance and highlights areas where there is scope of improvement. This will help banks make informed decisions, prevent errors, and improve efficiency. Benefits
Banking Analytics – The Way Banks Do Business Read More »