The American Recovery and Reinvestment Act of 2009 (Recovery Act) created the Recovery Board composed of Inspectors General to promote accountability by overseeing recovery-related funds. The board was to do so, in part, by providing the public with easily accessible information. The Recovery Act appropriated $84 million for the Recovery Board to carry out its duties and set a termination date of September 30, 2013, for its oversight activities. The act provided the Recovery Board with the following specific powers and functions: audit and review spending on its own or in collaboration with federal OIGs; issue subpoenas to carry out audit and review responsibilities; refer instances of fraud, waste, and mismanagement to federal OIGs; hold public hearings and compel testimony through subpoenas; enter into contracts with public agencies and private entities; review whether there are sufficient and qualified personnel overseeing Recovery Act funds; and make recommendations to federal agencies on measures to prevent fraud, waste, and mismanagement of Recovery Act funds. To fulfill its mandate under the Recovery Act, the Recovery Board utilized data analytics to carry out its oversight responsibilities and increase accountability. Data analytics is a term typically used to describe a variety of techniques that can be used to analyze and interpret data to, among other things, help identify and reduce fraud, waste, and abuse. Specifically, predictive analytic technologies can be used to identify potential fraud and errors before payments are made, while other techniques, such as data mining and data matching of multiple databases, can identify fraud or improper payments that have already been awarded, thus assisting agencies in recovering these dollars. In October 2009, the Recovery Board established the ROC to analyze the use of Recovery Act funds by employing data analytics, specifically to provide predictive analysis capability to help oversight entities focus limited government oversight resources, based on risk indicators such as programs previously identified as high-risk, high-dollar-value projects, past criminal history of key parties involved in a project, and tips from citizens; and in-depth fraud analysis capability using public information to identify relationships between individuals and legal entities. The ROC served as a centralized independent repository of tools, methods, and expertise for identifying and mitigating fraud, waste, and mismanagement of Recovery Act funds and the associated parties through the use of such predictive and other analytic technologies. The Recovery Board’s assets supporting the ROC include human capital, hardware, data sets, and software. (See fig. 1 for a description of the ROC’s assets.) Subsequent legislation expanded the Recovery Board’s mandate to include oversight of other federal spending, including those funds appropriated for purposes related to the effects of Hurricane Sandy. In addition to expanding its authority, the legislation extended the termination date of the Recovery Board from September 30, 2013, to September 30, 2015. Figure 2 illustrates the timeline of legislation authorizing the Recovery Board and any corresponding appropriations. As we reported in our July 2015 testimony describing the progress made in the initial implementation of the DATA Act, the ROC has provided significant analytical services to its clients, including many OIGs, in support of their antifraud and other activities. Specifically, on the basis of the ROC’s client-service performance data that we reviewed, as part of the ROC’s analysis supporting investigations and audits, the ROC researched roughly 1.7 million entities associated with $36.4 billion in federal funds during fiscal years 2013 and 2014 at the request of various OIGs and other entities. As described below, examples of such research include Appalachian Regional Commission OIG audits of high- risk grantees and Department of Homeland Security OIG oversight of debris-removal contracts following Hurricane Sandy. The largest single user of ROC assistance over this time was the Appalachian Regional Commission OIG in fiscal year 2012 and the Department of Homeland Security OIG in fiscal years 2013 and 2014 (see fig. 3). The ROC developed specialized data-analytic capabilities to better ensure federal spending accountability. Since January 2012—after the Recovery Board’s mandate was expanded to address federal funds beyond those authorized by the Recovery Act—over 50 federal OIGs and agencies have asked for assistance from the center. Two major tools the ROC used on behalf of the OIGs included (1) link analysis and (2) unstructured text mining: Link analysis assists analysts in making connections by visually representing investigative findings. Link-analysis charts visually depict how individuals and companies are connected, what awards an entity has received, and how these actors may be linked to any derogatory information obtained from multiple data sets. Such tools, when combined with enhanced Geographic Information System capabilities, enable ROC analysts to conduct geospatial analysis by displaying data from multiple data sets on maps to help them make linkages and discover potential problems. (See figs. 4 and 5 for an example of link analysis and two visualizations of the data.) Although link analysis can be applied to a wide range of subjects, the ROC often applied this tool to issues that involved law-enforcement-sensitive data that the Recovery Board had authority to handle. The figure below shows an example of a request made by a federal agency to investigate Subject Company 1 as a delinquent federal debtor. Analysis by the ROC included checking entities identified against relevant events and associations, which include debarments, criminal history, and other factors. The initial review of Subject Company 1 determined that it was the recipient of an award under the Recovery Act totaling $6.4 million from a federal government agency. Further review of this company determined that it was not registered in the System for Award Management and had not previously received any federal awards. ROC analysts identified a news article that explained that this company had been created as a joint venture between Subject Company 2 and an individual, Subject 1. Analysis of Subject Company 2 revealed that four of its employees were previously indicted for fraud in 2006 and three of them were placed on the Excluded Parties List System, debarring them from receiving federal contracts. As part of the same analysis as in figure 4, the ROC determined Subject 1 was listed as the Registered Agent of 42 companies with vague names in a variety of industries. Geospatial analysis, represented in figure 5 below, determined that 15 of the companies were registered at the individual’s home address in Florida. The other 27 companies were registered in Gary, Indiana, at the same address as Subject Company 1. Geospatial analysis identified the address as a vacant lot in an industrial area. In another example, the Environmental Protection Agency OIG used the ROC’s data visualizations of a link analysis that identifies relationships among entities involved in activities such as collaborating to commit fraud. An Environmental Protection Agency OIG official said that the visualization of these relationships made it easier for juries to understand how entities had collaborated in wrongdoing. The ROC’s unstructured/structured text mining tools were developed to proactively identify high-risk entities. This tool uses key words or phrases to rapidly filter through thousands of documents and pinpoint high-risk areas to uncover trends and conduct predictive analysis across agencies, programs, and states and to identify and assign weights to risk factors or concepts. The Appalachian Regional Commission OIG used the results of the ROC’s unstructured text-mining analyses to identify the highest-risk grantees for review by analyzing text from A-133 Single Audit data to search for indications of risk, such as when a material finding was identified in the audit. A Single Audit includes an audit and an opinion on compliance with legal, regulatory, and contractual requirements for major programs as well as the auditor’s schedule of findings and questioned costs. The unstructured text tool could be directed to identify entities such as grantees that had previous negative audit findings and that therefore could represent a higher risk for using grant funding. This approach allowed the Appalachian Regional Commission OIG to better identify grantees subject to risk and facilitate the establishment of risk based priorities to allocate audit and investigative resources. According to a commission OIG official, this allowed the OIG to establish risk-based priorities to allocate audit and investigative resources. In addition to these examples, OIGs highlighted using the ROC’s analytic capabilities to identify fraud, waste, and abuse in federal spending in the following ways: In fiscal year 2013, the Department of Homeland Security OIG submitted 104 entities receiving debris-removal contracts totaling $329 million from 32 cities in New York and New Jersey to the ROC for further research. The ROC analysts’ review was forwarded to the department OIG for appropriate investigative or audit follow-up actions. ROC analysts also provided a risk analysis of these entities to the department OIG for use in planning future audits. Findings submitted to the department OIG included identification of the following: Debris-removal firms whose owners had federal and state tax liens. Firms previously listed on the Excluded Parties List System, indicating potential financial problems. Two companies that received contracts despite having filed for Chapter 7 bankruptcy in December 2010 and having federal tax liens totaling more than $1 million since 2011. Organizations with previous fraudulent activities receiving debris- removal contracts from cities where there was an indication the company heads had relationships with city officials. In part on the basis of these findings, the Department of Homeland Security OIG opened three criminal investigations involving Hurricane Sandy Public Assistance program funds, and the Department of Homeland Security OIG Emergency Management Office conducted four Hurricane Sandy–related audits. The ROC assisted the Department of Housing and Urban Development OIG with information confirming allegations that a loan guarantee specialist had sold HUD-owned properties for less than fair market value to shell companies that he owned and operated, stealing over $843,000 in federal funds. Due in part to the analysts’ efforts, the employee pleaded guilty to wire fraud for his involvement and was sentenced to 26 months in jail. In May 2015, Treasury officials told us that the department did not plan to exercise its discretionary authority to establish a data-analysis center or expand an existing service under the DATA Act.