AFTAs 2014: Best Analytics Initiative—Fannie Mae

fannie-mae-best-analytics-initiative
Nathan Den Herder, Stéphane Matteau, and Roman Chwyl

The term “analytics” has gotten sexy in recent years. It’s even being used in TV commercials to sell mainstream products. In the capital markets, if you aren’t talking analytics then you are likely lost in the woods.

In a tough category that included entrants from Citi, Deutsche Bank, ITG, and Morgan Stanley, Fannie Mae’s Vega Analytics initiative separated itself thanks to its collaboration with IBM and its big-data toolset.

The Vega Analytics initiative was designed to improve the firm’s loan origination and securitization processes in the post-financial crisis marketplace. Because Fannie Mae is the top source of liquidity in the US secondary mortgage market, its decisions about which assets to purchase play a central role in continuing the recovery of the residential housing sector and its future health.

In November 2013, Fannie Mae began the Vega project, the goal being to develop a comprehensive set of analytics tools for collateral valuation and risk management. After examining other providers, the government-sponsored entity selected Hadoop MapReduce technology from IBM.

Fannie Mae was already using Platform Symphony to scale and accelerate its traditional analytics, but tapped IBM’s Platform Symphony Advanced Edition grid software for its big-data analytics platform. The team working on the project released the Vega suite of tools in April 2014. The tools analyze thousands of electronic documents daily, flagging items that need additional review or data. This has helped Fannie Mae to improve its financial risk and fraud analytics capabilities.

Because duplicity can indicate fraudulent activity, the system can identify appraisals with images that are duplicates, or images submitted before in other appraisals.

The team working on the project released the Vega suite of tools in April 2014. The tools analyze over 20,000 electronic documents daily, flagging items that need additional review or data. This has helped Fannie Mae to improve its financial risk and fraud analytics capabilities.

Several major banks have adopted Vega analytics, Fannie Mae says, with more planned in the first quarter of this year. By identifying and removing bad loans prior to securitization, banks can accelerate the process and improve the quality of their assets and hold less capital in reserve, thus helping their trading and loan operations.

In light of its near-collapse, Fannie Mae has aggressively invested in new, innovative tools in order to better handle the swings and changes of a rapidly evolving market. And for its part, the mortgage giant notes that this is a continuing project, so look for additional functionality over the course of 2015.

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