Data Science in Banking
The banking sector is a data intensive industry, with massive piles of paper work ranging from customer details, transaction receipts to credit data. Data Science has emerged as a required skill and necessary technology for risk management in the Banking sector.
So how do banks apply data science to ensure risk management and strategic operational success? How has data science helped the banking industry move from standard and traditional ways of data management and operations?
In collaboration with Afterwork Fellowship we have organized a couple of events to give you a closer look at Data Science in Banking.
To kick us off on this first event of the series here are the topics and presenters:
Credit Scoring with Python: Sharon Omwega -Data Scientist at Absa Bank
Customer Churn and Management: Donna Naishorwa-Data Scientist at Absa Bank
Loan Delinquencies: Chris Orwa-Lead Data Scienctist at I&M Bank
Don't miss out!!! RSVP here: https://bit.ly/33XmeLm to attend.
Reach out to us on firstname.lastname@example.org if you have any questions.