Case Study: Moody’s Analytics achieves 6X faster model deployment and halves development cycles with Domino Data Lab

Driving Customer Value and Efficiency by Transforming Model Development and Deployment

Moody’s Analytics, a leading provider of data, models and software to the financial services industry, needed a more cost-effective way to deliver customized risk models to clients at scale. Its global data science teams faced limited access to elastic compute, a linear (slow) development-to-deployment workflow, and tool silos that hampered collaboration, reproducibility, and knowledge retention — all of which increased time and cost to get models into customers’ hands.

By adopting the Domino data science platform on AWS, Moody’s centralized model development, deployment, monitoring and collaboration while letting teams use their preferred tools (R, Python, SAS, Jupyter, etc.). The result: model development cycles fell from nine months to four, models reached production up to 6× faster, monitoring capability increased fourfold, institutional knowledge and compliance improved, and customers received tailored, iterated solutions (e.g., faster beta testing and deployment of the Financial Statement Quality Checker and RiskCalc templates) with lower cost and higher ROI.

Moody’s Analytics

Jacob Grotta

Managing Director of Risk and Finance Analytics