{"id":32506,"date":"2026-05-08T18:16:08","date_gmt":"2026-05-08T18:16:08","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/32506\/"},"modified":"2026-05-08T18:16:08","modified_gmt":"2026-05-08T18:16:08","slug":"ai-data-exchange-2026-pracs-ken-dieffenbach-on-using-ai-tools-to-stay-a-step-ahead-of-fraudsters","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/32506\/","title":{"rendered":"AI &#038; Data Exchange 2026: PRAC\u2019s Ken Dieffenbach on using AI tools to stay a step ahead of fraudsters"},"content":{"rendered":"<p>\nAlthough Congress created the Pandemic Response Accountability Committee to oversee more than $5 trillion in emergency COVID-19 spending, PRAC is entering a new phase of its oversight work.<\/p>\n<p>PRAC, a coalition of agency inspectors general created in March 2020 under the Coronavirus Aid, Relief and Economic Security (CARES) Act, was originally scheduled to sunset in September 2025. But the pandemic watchdog still remains and is overseeing another broad tranche of funding.<\/p>\n<p>The One Big, Beautiful Bill Act signed into law last year will keep the PRAC operational through 2034 and authorizes the watchdog to oversee spending from the budget reconciliation bill.<\/p>\n<p>Ken Dieffenbach, PRAC\u2019s executive director, said the organization is still deeply involved in pandemic-related investigations, even as it pivots toward a new portfolio. PRAC continues to work with law enforcement agencies and supports over 1,000 cases with about $2.5 billion in potential fraud losses.<\/p>\n<p>Some of the lessons learned about fraud at the height of the COVID-19 pandemic apply to the PRAC\u2019s ongoing work, Dieffenbach said during <a href=\"https:\/\/federalnewsnetwork.com\/cme-event\/exchanges\/federal-news-networks-ai-data-exchange-2026\/\" rel=\"nofollow noopener\" target=\"_blank\">Federal News Network\u2019s AI &amp; Data Exchange 2026<\/a>.<\/p>\n<p>\u201cWe found that during the pandemic, much of the loss could have been mitigated. We\u2019re trying to make sure the right people are aware of those lessons learned so that we cannot be in this place again when, inevitably, there\u2019s another disaster and there\u2019s lots of money that has to get out quickly,\u201d he said.<\/p>\n<p>AI transforms oversight capabilities<\/p>\n<p>PRAC is using artificial intelligence tools to analyze a vast trove of federal spending data and to flag potential fraudulent spending for its team to investigate. Dieffenbach said these emerging tools have been a force multiplier for investigators and auditors.<\/p>\n<p>\u201cWe\u2019re collecting, analyzing and communicating information. What AI allows us to do in that space is incredibly helpful because it does things that human beings couldn\u2019t do as efficiently, as effectively and certainly not as quickly,\u201d he said.<\/p>\n<p>From \u2018pay and chase\u2019 to prevention<\/p>\n<p>One of PRAC\u2019s biggest priorities now is shifting from a reactive model \u2014 often referred to as \u201cpay and chase\u201d \u2014 to a proactive one that stops fraudulent payments before they are made.<\/p>\n<p>\u201cThe ultimate goal of PRAC now is to leverage these tools and this data to give grant officers, contracting officials, perhaps OIG folks, new information so we can pause, stop, do due diligence before the money goes out the door. Because we know once it goes out the door, it\u2019s very cost-prohibitive. We\u2019re never going to get the money back,\u201d Dieffenbach said. \u201cIt\u2019s a very lengthy process to prosecute, so we want to do everything we can to prevent those things on the front end.\u201d<\/p>\n<p>Dieffenbach told <a href=\"https:\/\/oversight.house.gov\/hearing\/curbing-federal-fraud-examining-innovative-tools-to-detect-and-prevent-fraud-in-federal-programs\/\" rel=\"nofollow noopener\" target=\"_blank\">members of the House Oversight and Government Reform Committee<\/a> in January that PRAC has developed an AI-enabled \u201cfraud prevention engine,\u201d trained on over 5 million applications for pandemic-era relief programs, that can review 20,000 applications for federal funds per second and can flag anomalies in the data before payment. He said work on this engine began last summer.<\/p>\n<p>\u201cWe have really focused on how that model can be adapted to a new government program to quickly give new information to decision-makers before money goes out the door,\u201d he said.<\/p>\n<p>While agencies prioritized payment speed above payment integrity in 2020, Dieffenbach said that with today\u2019s tools, they don\u2019t have to choose one over the other.<\/p>\n<p>\u201cWe do have to strike the right balance, but I think it\u2019s kind of a false choice to say, \u2018Either get it out quickly, or you stop and look for fraud.\u2019 You can have both,\u201d he said.<\/p>\n<p>Finding ways to verify information against other agencies\u2019 datasets<\/p>\n<p>To crack down on fraudulent payments, the Trump administration has issued executive orders giving agencies greater access to datasets like the Treasury Department\u2019s Do No Pay files and the Social Security Administration\u2019s Death Master File. But in fraud prevention, agencies still often face legal barriers to sharing data with one another. Dieffenbach said PRAC is getting around this problem through simple yes\/no validations.<\/p>\n<p>\u201cWe said, \u2018Social Security, can you just verify if you ever issued that Social Security number? If you have, does your name match our name? And does your date of birth match our data of birth?\u2019 We weren\u2019t asking them to give us any data \u2014 just tell us yes or no,\u201d he said.<\/p>\n<p>Through this approach, PRAC was able to identify 1.4 million potentially invalid Social Security numbers used to obtain $79 billion in pandemic funding.<\/p>\n<p>\u201cThat was a bit of a demonstration project, if you will, of the fact that a little bit of pre-award vetting, a little bit of verifying that simple kind of question, could have potentially prevented a lot of fraud and prevented the pay and chase,\u201d Dieffenbach said.<\/p>\n<p>Fraudsters evolving alongside AI<\/p>\n<p>While the government is adopting AI to fight fraud, criminals are doing the same \u2014 raising the stakes for oversight agencies.<\/p>\n<p>\u201cThey\u2019re using artificial intelligence against us to create very realistic false documentation,\u201d Dieffenbach said. \u201cThere was a time when in the oversight world when auditors and investigators could look at a receipt or look at a contract or look at a bank statement and say, \u2018That looks like a receipt, a contract or a bank statement.\u2019 Now it\u2019s much, much harder to know if those are valid, if they\u2019re legitimate at all.\u201d<\/p>\n<p>Fraudsters are also using bots and other technologies to overwhelm the weak links in agency programs.<\/p>\n<p>\u201cWe really have to consider the fact that, yes, we can use these tools to give us better insight, but they are using them every day in new ways, and we have to keep up with that,\u201d Dieffenbach said.<\/p>\n<p>Discover more articles and videos now on the<a href=\"https:\/\/federalnewsnetwork.com\/cme-event\/exchanges\/federal-news-networks-ai-data-exchange-2026\/\" rel=\"nofollow noopener\" target=\"_blank\"> AI &amp; Data Exchange event page<\/a>.<\/p>\n<p class=\"article-copyright\">Copyright<br \/>\n                            \u00a9\u00a02026 Federal News Network. All rights reserved. This website is not intended for users located within the European Economic Area.\n                    <\/p>\n","protected":false},"excerpt":{"rendered":"Although Congress created the Pandemic Response Accountability Committee to oversee more than $5 trillion in emergency COVID-19 spending,&hellip;\n","protected":false},"author":2,"featured_media":32507,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[24,20800,20789,25,20801,20802,20803],"class_list":["post-32506","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ai","tag-ai","tag-ai-data-exchange","tag-ai-exchange-2026","tag-artificial-intelligence","tag-ken-dieffenbach","tag-pandemic-response-accountability-committee","tag-prac"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/32506","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=32506"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/32506\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/32507"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=32506"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=32506"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=32506"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}