Moody’s supplies expertise and tools—including data, models, software, and professional services—that help companies grow efficiently and manage financial risk. The firm supports thousands of organizations across a range of industries and geographies as they navigate increasingly complex global markets. Moody’s is a subsidiary of Moody’s Corporation, which reported $4.2 billion in revenues in 2017 and operates in 41 countries.
A pioneer in financial modeling, Moody’s has established a competitive advantage by creating analytics based on unique financial data sets and applying them to solve clients’ business challenges. The firm has developed a large portfolio of models covering everything from small business to large bank credits, and deploys its models in software delivered on-premise, in the cloud, or as software-as-a-service (SaaS).
By centralizing some of its data science projects on Domino, Moody’s has dramatically increased the efficiency of model development, and expanded its ability to build collaborative models with clients and partners. To make this transformation, Moody’s needed to accelerate the pace of model development and the number of iterations they could make on models under development. They’ve accomplished this with Domino, reducing end-to-end model development cycles. For example, in its first experience using Domino, Moody’s reduced an estimated nine-month project to four months. The firm has also increased its model monitoring capability by four times using Domino.
Moody’s has been a long-time leader in financial modeling, and over time its models have been widely adopted and have become vital to many firms. To stay at the forefront of an industry that runs on models, Moody’s saw an opportunity to customize its offerings to satisfy particular clients’ needs, profiles, and objectives. The company had already been successful with a services-based model whereby Moody’s consultants build custom models for clients in the field, but this business model is expensive, both for Moody’s and its customers, especially at a large scale. Moody’s sought a more cost-effective approach to development and delivery of these customized models, in order to serve its customers more effectively.
Key challenges for Moody’s in transitioning their customized model delivery services offering into a product included:
“Working with Domino gives us the ability to fully leverage our core strengths of working with financial data, building analytics, and applying those to our customers’ businesses. ”
Jacob Grotta
General Manager of Banking Operating Unit at Moody’s
Moody’s first considered building a solution in-house that would expedite model development and delivery. However, advanced capabilities within the Domino data science platform would be able to accomplish the company’s objectives while allowing internal teams to remain focused on modeling – their core capability – instead of systems development. “Working with Domino gives us the ability to fully leverage our core strengths of working with financial data, building analytics, and applying those to our customers’ businesses,” Grotta said.
Several Domino capabilities made its data science platform the most attractive option:
Moody’s has deployed Domino to build new models and to monitor, manage, and enhance existing models once they’ve gone into production. Domino runs on AWS, allowing users access to the enterprise-scale platform without concerns about their security or location.
Moody’s serves its customers better today because the company can deliver models that perform well and are custom-built for each customer’s business – and can tweak them rapidly to ensure they continue to deliver more value after each iteration. The end-to-end process from model development to deployment into production has been reduced by more than half, from nine months to four. They’ve improved ROI by streamlining model development and deployment. The centralized platform and automated tracking has also enhanced transparency, preserved institutional knowledge, and improved compliance.
“With Moody’s know-how and workflow, coupled with Domino and AWS infrastructure, we have been able to accelerate model development, which means information gets into the hands of our clients who need it faster,” Grotta said. “Our customers are excited because their needs are going to be answered in new ways that would previously have been impossible.”
Two examples demonstrate the impact Moody’s has achieved with Domino:
With Domino, Moody’s can efficiently deliver customized models for risk and other analytics that help run large-scale enterprises, and cost-effectively deploy them according to customer preferences on-premise, in the cloud, or as SaaS.
“We’ve been able to standardize the data, the know-how, and the ways of collaborating amongst ourselves and with our customers so that they can see the work we're doing as we do it,” Grotta said. “Domino accelerates our speed to delivery, providing a much faster and better return on our modeling investment.”
