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GCN : July 2014
BIG DATA Data is the raw material with which investigators deal. The challenge for them often is not so much getting data---there is more of it being produced and stored by govern- ment today than ever before---but mak- ing sense of it. The inspector general's office at the U.S. Postal Service has developed its own system to analyze data and visual- ize results, identifying high- value targets for potential fraud investigations. The core of the Risk Assessment Data Reposi- tory (RADR) is a suite of models that merge data from a variety of sources and score it on the likeli- hood of fraud. The resulting hotspots are displayed on a geographic in- terface. Armed with this analy- sis, examiners can proactively launch investigations rather than waiting to receive reports of wrong- doing. The concept is not new. OIG investi- gators have been analyzing data on Ex- cel spreadsheets for years. What RADR brings to the game are the data models that automate analysis for specific types of fraud and display results, letting in- vestigators drill down for details where suspicious trends are shown, said Bryan Jones, deputy assistant inspector general for analytics. "Once you have the data and have modeled it, if you ask a different ques- tion of it you get a different answer," Jones said. "We ask a lot of different questions depending on what we're look- ing for." The results of the system are positive, Jones said, but not easy to quantify. Most of the return on investment comes in cost avoidance. "When the investigators use our tools it takes them fewer hours to work a case," he said. And early detec- tion can reduce the amount of fraud. There also are concrete returns in the form of recovery of funds. The analytics tool lets investigators prioritize high-val- ue cases so that the average amount of money recovered on a case now is about $1 million. Overall, RADR more than pays for itself each year, Jones said. RADR was developed in-house, using the subject matter and technical experts within the OIG working with a contrac- tor to develop algorithms. "We knew what we wanted and we used the skill sets we had," Jones said. "We didn't want to spend a lot on it." Work on the project began in 2009, and it took about nine months to build the first model, which examines worker compensation records for fraud. "We ap- proached it like a small business," Jones said. "We didn't have a lot of money or resources, so we went for what would give us the biggest return." RADR went live in October 2011. The healthcare model was the first to go into production and is the most mature of the four models now in use. The model pulls together data---both historical and current---from within USPS and from outside sources such as the Labor De- partment. The OIG analytics team used the historical data to "train" the model on what fraud indicators to look for. Factors in- cluding frequency of claims, fre- quency of treatments, amount of payments and the length of claims payments are scored ac- cording to risk. Using geographic information sys- tem software from Esri, results are dis- played on a map that depicts high-risk cases---those that have several high-risk factors---as red hotspots. Medium-risk cases are displayed in yellow. The size of the spot reflects the relative value of the case in dollar amount, so investigators can quickly prioritize a case both by risk and value. The interface is Web-based, so investi- gators can query data from anywhere. "It gives every investigator the chance to be proactive," Jones said. • The U.S. Postal Service has developed its own system to analyze data and visualize results, identifying targets for potential fraud investigations In-house analytics tool maps fraud at USPS BY WILLIAM JACKSON 28 GCN JULY 2014 • GCN.COM The Risk Assessment Data Repository gives every investigator the chance to be proactive. -- BRYAN JONES, USPS DEPUTY ASSISTANT INSPECTOR GENERAL FOR ANALYTICS