Digital Risk Management: Credit Scoring Scorecard with Excel and Python

In today's digital world, customers not only expect their shopping activity can be done online, they also demand their financial transactions also be done online and as quick as possible. Thus, financial institutions have to keep developing themselves following the latest developments in technology.

For the credit lending division, it is crucial that they already moving from manual process and start implementing digital and automatic Credit Scoring, to determine potential users who are eligible for loans. Digitalization also unlocks new opportunity to utilize data that typically not used to assess loan eligibility. Thus, for traditional financial institutions to be able to survive in the digital environment, they need to know the framework of digital risk management and best practices in implementing Credit Scoring.

After completion of this program, participants will be better able to:

• Understand the concept of digital credit risk management and the use of Credit Scoring
• Identify appropriate data, as well as the use of alternative data, to be used to determine credit risk
• Formulate statistical framework to build Credit Scoring model
• Develop Credit Scoring with logistic regression using Excel and Python
• Transform the model into credit scorecard
• Implement best practices in digital Credit Scoring to determine loan approval