We’re giving away 1,500 DJI Tello drones. Enter to win ›
Get the code
By Alexis Chretienne, Yann Kindelberger, Nora Kissari | Published August 1, 2018
AnalyticsAPI ManagementDatabasesSystemsCloudHybrid CloudFinance
Machine learning is transforming all areas of business, including the way in which financial institutions and other industries are approaching tighter compliance requirements and risk management. This developer journey shows you how machine learning on IBM z/OS is deployed for a financial risk model to determine customer credit worthiness. You’ll learn how the results are displayed using an API, enabling you to incorporate the data into business applications.
Financial institutions need to continually weigh the risks of their transactions, and they determine their risk level through credit scoring. Leading up to the 2008-09 financial crisis, almost all large banks used credit scoring models based on statistical theories; that crisis, largely brought about by underestimating risk, proved the need for better accuracy in their scoring. The combination of increased requirements and the development of advanced new technologies has given rise to a new era: credit scoring using machine learning.
Machine Learning for IBM z/OS gives organizations the ability to quickly ingest and transform data. They can now create, deploy, and manage high quality self-learning behavioral models, using large corporate data sets residing on IBM Z. This risk assessment and management takes place securely in place and in real time, and helps financial institutions more accurately determine credit worthiness and other business needs.
In this developer journey, you will use a financial risk management model that’s been designed and deployed in a large banking system to approve or deny a loan according to input parameters. You will discover and test a financial risk management API and then create and extend a financial risk management application based on Machine Learning on z/OS. By completing the journey, you’ll discover how machine learning can be used in applications to deliver accurate financial risk management.
Ready to put this code pattern to use? Complete details on how to get started running and using this application are in the README.
September 26, 2018
October 16, 2017
March 12, 2018
Back to top