01 - 02 May, 2019 | Sydney, Australia

Clayton Howes


11:10 AM Case Study Banner: Leveraging Machine Learning to Predict Credit Risk and Improve Customer Experience and Outcomes

This session will explore the value of data and how it can be used to improve risk prediction in customer loan applications. Where traditional credit perspectives have incorrectly valuated risk of default, Clayton will discuss the implementation of AI and open banking strategies in MoneyMe’s loan processes to improve customer experience in today’s digital age.

  • Better decision making through data-driven strategies
  • Assessing the use of machine learning to improve customer experience
  • Creating meaning from the early use of Comprehensive Credit Reporting: Moneyme’s case study on digital integration of CCR, its advantages and indicative results

Check out the incredible speaker line-up to see who will be joining Clayton.

Download The Latest Agenda