How to build models that move quickly through validation and audit

Financial Service Institutions (FSI) on average have fewer than 10 machine learning models in production. Banks, Insurers and Asset Managers have arguably seen the least innovation over the last decade compared to other parts of the economy due to regulatory requirements, legacy technologies and long release cycles. In this discussion focused on credit risk analytics, we will demonstrate how a unified data analytics platform brings a more transparent and structured approach to commercial data science in Finance, complying with audit and regulation whilst reducing model lifecycle process from 12 months to a few weeks.

Antoine Amend, Technical Director - Financial services @Databricks