Analytics Stories: A Case Study from Fannie Mae

As I indicated in my last case study regarding competing on analytics, Thomas H. Davenport believes “business processes are among the last remaining points of differentiation.” For this reason, Davenport contends that businesses that create a sustainable right to win use analytics to “wring every last drop of value from their processes”. For financial services, the mission critical areas needing process improvement center are around improving the consistency of decision making and making the management of regulatory and compliance more efficient and effective.

Why does Fannie Mae need to compete on analytics?

Fannie MaeFannie Mae is in the business of enabling people to buy, refinance, or rent homes. As a part of this, Fannie Mae says it is all about keeping people in their homes and getting people into new homes. Foundational to this mission is the accurate collection and reporting of data for decision making and risk management. According to Tracy Stephan at Fannie Mae, their “business needs to have the data to make decisions in a more real time basis. Today, this is all about getting the right data to the right people at the right time”.

Fannie Mae claims when the mortgage crisis hit, a lot of the big banks stopped lending and this meant that Fannie Mae among others needed to pick up the slack. Their action here, however, caused the Federal Government to require them to report monthly and quarterly against goals that the Federal Government set for it. “This meant that there was not room for error in how data gets reported”. In the end, Fannie Mae says three business imperatives drove it’s need to improve its reporting and its business processes:

  1. To ensure that go forward business decisions were made consistently using the most accurate business data available
  2. To avoid penalties by adhering to Dodd-Frank and other regulatory requirements established for it after the 2008 Global Financial Crisis
  3. To comply with reporting to Federal Reserve and Wall Street regarding overall business risk as a function of: data quality and accuracy, credit-worthiness of loans, and risk levels of investment positions.

Delivering required Fannie Mae to change how it managed data

AnalyticsGiven these business imperatives, IT leadership quickly realized it needed to enable the business to use data to truly drive better business processes from end to end of the organization. However, this meant enabling Fannie Mae’s business operations teams to more effectively and efficiently manage data. This caused Fannie Mae to determine that it needed a single source of truth whether it was for mortgage applications or the passing of information securely to investors. This need required Fannie Mae to establish the ability to share the same data across every Fannie Mae repository.

But there was a problem. Fannie Mae needed clean and correct data collected and integrated from more than 100 data sources. Fannie Mae determined that doing so with its current data processes could not scale. And as well, it determined that its data processes would not allow it to meet its compliance reporting requirements. At the same time, Fannie Mae needed to deliver more proactive management of compliance. This required that it know how critical business data enters and flows through each of its systems. This includes how data was changed by multiple internal processing and reporting applications. As well, Fannie Mae leadership felt that this was critical to ensure traceability to the individual user.

The solution

analyticsPer its discussions with business customers, Fannie Mae’s IT leadership determined that it needed to get real time, trustworthy data to improve its business operations and to improve its business processes and decision making. As said, these requirements could not be met with its historical approaches to integrating and managing data.

Fannie Mae determined that it needed to create a platform that was high availability, scalable, and largely automating its management of data quality management.  At the same time, the platform needed to provide the ability to create a set of business glossaries with clear data lineages. Fannie Mae determined it needed effectively a single source of truth across all of its business systems. According to Tracy Stephan, IT Director, Fannie Mae, “Data quality is the key to the success of Fannie Mae’s mission of getting the right people into the right homes. Now all our systems look at the same data – that one source of truth – which gives us great comfort.” To learn more specifics about how Fannie Mae improved its business processes and demonstrated that it is truly “data driven”, please click on this video of their IT leadership.

Related links

Solution Brief: The Intelligent Data Platform

Related Blogs
Thomas Davenport Book “Competing On Analytics”
Competing on Analytics
The Business Case for Better Data Connectivity
The CFO Viewpoint upon Data
What an enlightened healthcare CEO should tell their CIO?

Twitter: @MylesSuer

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