{"id":984166,"date":"2026-07-23T12:16:10","date_gmt":"2026-07-23T16:16:10","guid":{"rendered":"https:\/\/www.marketnewsdesk.com\/index.php\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\/"},"modified":"2026-07-23T12:16:10","modified_gmt":"2026-07-23T16:16:10","slug":"auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds","status":"publish","type":"post","link":"https:\/\/www.marketnewsdesk.com\/index.php\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\/","title":{"rendered":"Auto Loan Fraud Losses More Than Triple in Key Categories, New TransUnion Analysis Finds"},"content":{"rendered":"<h2>\n Fraudsters are using sophisticated identity schemes, driving larger auto loan losses from fewer incidents<br \/>\n<\/h2>\n<div class=\"mw_release\">\n<p align=\"left\">CHICAGO, July  23, 2026  (GLOBE NEWSWIRE) &#8212; TransUnion (NYSE: TRU) today released new research revealing that despite a decline in incidents across many fraud types, fraud losses in auto lending have increased significantly in recent years. The findings point to a fraud environment impacting dealerships and auto lenders where fewer events drive greater financial losses. Today\u2019s fraudsters have evolved to concentrate on higher-value opportunities throughout the lending lifecycle, especially as new and used vehicle prices reach heightened levels.<\/p>\n<p align=\"left\">Auto lenders are facing substantially higher fraud-related losses across multiple fraud categories. Between Q3 2018 and Q3 2025, losses tied to first-party, third-party and synthetic fraud increased significantly. First-party fraud, which occurs when an individual deliberately provides false information or misrepresents themselves to obtain goods, services or credit, experienced the largest increase. It saw estimated losses rising from $88 million to $323 million\u2014an increase of approximately 267% over the period.<\/p>\n<p align=\"left\">Gaps in fraud detection, especially resolving identities, open the door to large charge-off losses by lenders and dealerships that most often are not found out until weeks or months later and are not recoverable.<\/p>\n<p align=\"left\">\u201cFraudsters are becoming increasingly targeted and efficient,\u201d said Satyan Merchant, senior vice president and automotive and mortgage business leader at TransUnion. \u201cWhile fraud volume remains an important indicator of risk, we are seeing criminals drive significantly higher losses through fewer, more strategic attacks by targeting high-value opportunities and exploiting vulnerabilities across the lending lifecycle. For lenders, effectively managing fraud risk requires a comprehensive view of both frequency and financial impact\u2014not only how often fraud occurs, but also the severity of each incident and its potential effect on the business.\u201d<\/p>\n<table style=\"border-collapse: collapse;margin-left:0px;margin-right:auto;width:99%;border-collapse:collapse\">\n<tr>\n<td colspan=\"3\" style=\"text-align: center;vertical-align: middle;padding-left: 0;padding-right: 0;vertical-align: bottom\">\n            <strong>Auto Lending Fraud Losses Saw Significant Growth Across Multiple Fraud Segments<br \/><\/strong>\n          <\/td>\n<\/tr>\n<tr>\n<td style=\"max-width:34%;width:34%;min-width:34%;border-top: solid black 1pt;border-right: solid black 1pt;border-bottom: solid black 1pt;border-left: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">\n            <strong>Fraud Type<\/strong>\n          <\/td>\n<td style=\"max-width:33%;width:33%;min-width:33%;border-top: solid black 1pt;border-right: solid black 1pt;border-bottom: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">\n            <strong>Q3 2018<\/strong>\n          <\/td>\n<td style=\"max-width:33%;width:33%;min-width:33%;border-top: solid black 1pt;border-right: solid black 1pt;border-bottom: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">\n            <strong>Q3 2025<\/strong>\n          <\/td>\n<\/tr>\n<tr>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;border-left: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">\n            <strong>First-party Fraud<\/strong>\n          <\/td>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">$88 million<\/td>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">$323 million<\/td>\n<\/tr>\n<tr>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;border-left: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">\n            <strong>Third-party Fraud<\/strong>\n          <\/td>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">$18 million<\/td>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">$47 million<\/td>\n<\/tr>\n<tr>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;border-left: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">\n            <strong>Synthetic Fraud<\/strong>\n          <\/td>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">$93 million<\/td>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">$208 million<\/td>\n<\/tr>\n<tr>\n<td colspan=\"3\">Source: TransUnion US consumer credit database<strong><br \/><\/strong><\/td>\n<\/tr>\n<tr>\n<td colspan=\"3\">\u00a0<\/td>\n<\/tr>\n<\/table>\n<p align=\"left\">Third-party fraud, which involves the use of another person\u2019s identity without their knowledge or consent, is a clear example of the divergent trends of incidences and losses. In auto lending, the incidence rate in Q3 2025 was less than half its Q3 2018 level, yet associated losses were 2.6 times higher. Similar trends were observed for other types of fraud. These gaps show how fraudsters are becoming more strategic and executing fewer schemes while targeting larger loan balances and generating greater losses.<\/p>\n<p align=\"left\">Though less common, third-party fraud can produce substantial losses due to the high balances associated with fraudulent auto loans. Some of the largest losses occur among traditionally lower-risk, higher-credit tiers, where fraud incidence is lower, but loss severity is significantly higher.<\/p>\n<p align=\"left\">\n        <strong>A Growing Threat: Credit Washing and Hidden Credit Risk<\/strong>\n      <\/p>\n<p align=\"left\">Beyond traditional fraud activity, lenders are also confronting emerging forms of identity and credit manipulation that can mask underlying risk. Credit washing, in particular, is creating new challenges by artificially enhancing the creditworthiness of some borrowers.<\/p>\n<p align=\"left\">Credit washing conceals critical risk signals and undermines the accuracy of credit-based decisioning. Consumers with suppressed negative tradelines can exhibit risk levels similar to much lower credit tiers despite appearing prime or above prime at origination. In some cases, they are several times more likely to experience early charge-off in the 12 months following origination than borrowers without suppressed credit events.<\/p>\n<table style=\"border-collapse: collapse;margin-left:0px;margin-right:auto;width:100%;border-collapse:collapse\">\n<tr>\n<td colspan=\"5\" style=\"text-align: center;vertical-align: middle;padding-left: 0;padding-right: 0;vertical-align: bottom\">\n            <strong>Charge-off Increases Among Credit Washers Across All Risk Tiers<br \/><\/strong>\n          <\/td>\n<\/tr>\n<tr>\n<td rowspan=\"2\" style=\"border-top: solid black 1pt;border-right: solid black 1pt;border-bottom: solid black 1pt;border-left: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: top\">\n            <strong>Credit Risk Tier at Origination<\/strong>\n          <\/td>\n<td colspan=\"4\" style=\"border-top: solid black 1pt;border-right: solid black 1pt;border-bottom: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;padding-right: 0;vertical-align: bottom\">\n            <strong>Subsequent Percentage Charge-Off in 12 Months Post Auto<br \/>Origination<\/strong>\n          <\/td>\n<\/tr>\n<tr>\n<td colspan=\"2\" style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;padding-right: 0;vertical-align: bottom\">\n            <em>Credit Washer<\/em>\n          <\/td>\n<td colspan=\"2\" style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;padding-right: 0;vertical-align: bottom\">\n            <em>Other Consumers<\/em>\n          <\/td>\n<\/tr>\n<tr>\n<td style=\"max-width:30%;width:30%;min-width:30%;border-right: solid black 1pt;border-bottom: solid black 1pt;border-left: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">\n            <strong>Subprime<\/strong>\n          <\/td>\n<td colspan=\"2\" style=\"max-width:35%;width:35%;min-width:35%;border-bottom: solid black 1pt;padding-right: 0;border-right: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;vertical-align: bottom\">14.8%<\/td>\n<td colspan=\"2\" style=\"max-width:35%;width:35%;min-width:35%;border-bottom: solid black 1pt;padding-right: 0;border-right: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;vertical-align: bottom\">10.3%<\/td>\n<\/tr>\n<tr>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;border-left: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">\n            <strong>Near prime<\/strong>\n          <\/td>\n<td colspan=\"2\" style=\"border-bottom: solid black 1pt;padding-right: 0;border-right: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;vertical-align: bottom\">6.7%<\/td>\n<td colspan=\"2\" style=\"border-bottom: solid black 1pt;padding-right: 0;border-right: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;vertical-align: bottom\">3.6%<\/td>\n<\/tr>\n<tr>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;border-left: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">\n            <strong>Prime<\/strong>\n          <\/td>\n<td colspan=\"2\" style=\"border-bottom: solid black 1pt;padding-right: 0;border-right: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;vertical-align: bottom\">5.6%<\/td>\n<td colspan=\"2\" style=\"border-bottom: solid black 1pt;padding-right: 0;border-right: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;vertical-align: bottom\">1.2%<\/td>\n<\/tr>\n<tr>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;border-left: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">\n            <strong>Prime plus<\/strong>\n          <\/td>\n<td colspan=\"2\" style=\"border-bottom: solid black 1pt;padding-right: 0;border-right: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;vertical-align: bottom\">4.8%<\/td>\n<td colspan=\"2\" style=\"border-bottom: solid black 1pt;padding-right: 0;border-right: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;vertical-align: bottom\">0.4%<\/td>\n<\/tr>\n<tr>\n<td style=\"border-right: solid black 1pt;border-bottom: solid black 1pt;border-left: solid black 1pt;vertical-align: middle;text-align: left;padding-left: 10.0px;vertical-align: bottom\">\n            <strong>Super prime<\/strong>\n          <\/td>\n<td colspan=\"2\" style=\"border-bottom: solid black 1pt;padding-right: 0;border-right: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;vertical-align: bottom\">3.6%<\/td>\n<td colspan=\"2\" style=\"border-bottom: solid black 1pt;padding-right: 0;border-right: solid black 1pt;text-align: center;vertical-align: middle;padding-left: 0;vertical-align: bottom\">0.1%<\/td>\n<\/tr>\n<tr>\n<td colspan=\"5\" style=\"vertical-align: top\">Source: TransUnion US consumer credit database<br \/>Data observation period: 2024 originations sample set<strong><br \/><\/strong><\/td>\n<\/tr>\n<tr>\n<td colspan=\"5\">\u00a0<\/td>\n<\/tr>\n<\/table>\n<p align=\"left\">\u201cCredit washing is one of the more concerning emerging trends because it fundamentally distorts how lenders assess risk,\u201d said Naureen Ali, U.S. head of fraud at TransUnion. \u201cWhen negative credit information is removed or suppressed, consumers can appear more creditworthy than they really are, leading to a higher likelihood of early default.\u201d<\/p>\n<p align=\"left\">In 2025, roughly 5% of U.S. consumers have had charged-off accounts suppressed for atypical reasons, with an estimated $10 billion in debt erased from credit reports, creating disproportionate risk and decisioning blind spots. These findings reinforce the need for lenders to look beyond traditional credit attributes and incorporate deeper identity intelligence into their processes.<\/p>\n<p align=\"left\">Ali continued, \u201cThe goal of fraud solutions like TransUnion&#8217;s suite of fraud solutions is to help lenders and dealers uncover and identify hidden risks. Whether it is credit washing or identity-based fraud, by combining identity verification and linkage analytics, synthetic ID detection, and anomalies on the credit file, TransUnion can help lenders uncover those hidden risks earlier and allow lenders to make more informed lending decisions.\u201d<\/p>\n<p align=\"left\">To learn more about TransUnion\u2019s fraud solutions and how they can help auto lenders uncover identity-related risks, detect fraud earlier and make more informed lending decisions throughout the account lifecycle, please click <a href=\"https:\/\/www.globenewswire.com\/Tracker?data=GnHQBxTYZcpKIHa7NPGkl1V9RBWMbX8z426A7uOLcUoqf033qRur6doLanlf6z_QzhZC_f3ZYNLrZAP9aTh0zK2gupKt-4SdkbPclrmxbj4qvXV62v45ty-GUV_TEo3OG-oT_eectT3t1YCuxR14Ymo_AkWo7adsKS2d3YoYUpi4n_-caIUQTJlnntWbW93AYvpZzQnEXSpcfnboWhAGEaECM0ej12xv2ekNUczCDXI3XseyC3roj2w7zaeYfvz3\" rel=\"nofollow\" target=\"_blank\">here<\/a>.<\/p>\n<p align=\"left\">\n        <strong>About TransUnion (NYSE: TRU) <\/strong>\n      <\/p>\n<p align=\"left\">TransUnion is a global information and insights company with over 13,000 associates operating in more than 30 countries. We make trust possible by ensuring each person is reliably represented in the marketplace. We do this with a Tru<sup>\u2122<\/sup> picture of each person: an actionable view of consumers, stewarded with care. Through our acquisitions and technology investments, we have developed innovative solutions that extend beyond our strong foundation in core credit into areas such as marketing, fraud, risk and advanced analytics. As a result, consumers and businesses can transact with confidence and achieve great things. We call this Information for Good\u00ae \u2014 and it leads to economic opportunity, great experiences and personal empowerment for millions of people around the world.<\/p>\n<p align=\"left\">\n        <a href=\"https:\/\/www.globenewswire.com\/Tracker?data=CBlCwa_vrvoDfDzbIJ1w0lPukKYREGVe80mBzXARkTluUudnVvqPPjDAv64C6Lmz1vV2gzvAkEj7fGrOGbtNelF6O6ATrh6zRA1JisaP8NeItPdcTzhtYk7ecJKc3n-q\" rel=\"nofollow\" target=\"_blank\">http:\/\/www.transunion.com\/business<\/a>\n      <\/p>\n<table style=\"border-collapse: collapse;width:100%;border-collapse:collapse\">\n<tr>\n<td style=\"max-width:13%;width:13%;min-width:13%\">\n            <strong>Contact<\/strong>\n          <\/td>\n<td style=\"max-width:87%;width:87%;min-width:87%\">Dave Blumberg<\/td>\n<\/tr>\n<tr>\n<td>\u00a0<\/td>\n<td>TransUnion<\/td>\n<\/tr>\n<tr>\n<td>\u00a0<\/td>\n<td>\u00a0<\/td>\n<\/tr>\n<tr>\n<td>\n            <strong>E-mail<\/strong>\n          <\/td>\n<td>david.blumberg@transunion.com<\/td>\n<\/tr>\n<tr>\n<td>\u00a0<\/td>\n<td>\u00a0<\/td>\n<\/tr>\n<tr>\n<td>\n            <strong>Telephone<br \/><\/strong>\n          <\/td>\n<td>312-972-6646<\/td>\n<\/tr>\n<\/table>\n<p align=\"left\">\n        <strong><br \/>\n          <br \/>\n        <\/strong>\n      <\/p>\n<p>      <img decoding=\"async\" alt=\"\" class=\"__GNW8366DE3E__IMG\" src=\"https:\/\/www.globenewswire.com\/newsroom\/ti?nf=OTc2NjY1OCM3NzE3MTE2IzIwMDk4NzQ=\" \/><br \/>\n      <br \/>\n      <img decoding=\"async\" alt=\"\" src=\"https:\/\/ml.globenewswire.com\/media\/ZDcwN2IzZmMtZWFjNS00NTk0LThmZTctZTlkMjE2NDA4MzRkLTEwMjE0NDctMjAyNi0wNy0yMy1lbg==\/tiny\/TransUnion.png\" \/>\n    <\/div>\n<div class=\"mw_contactinfo\"><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Fraudsters are using sophisticated identity schemes, driving larger auto loan losses from fewer incidents CHICAGO, July 23, 2026 (GLOBE NEWSWIRE) &#8212; TransUnion (NYSE: TRU) today released new research revealing that despite a decline in incidents across many fraud types, fraud losses in auto lending have increased significantly in recent years. The findings point to a fraud environment impacting dealerships and auto lenders where fewer events drive greater financial losses. Today\u2019s fraudsters have evolved to concentrate on higher-value opportunities throughout the lending lifecycle, especially as new and used vehicle prices reach heightened levels. Auto lenders are facing substantially higher fraud-related losses across multiple fraud categories. Between Q3 2018 and Q3 2025, losses tied to first-party, third-party and synthetic fraud increased significantly. &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/www.marketnewsdesk.com\/index.php\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Auto Loan Fraud Losses More Than Triple in Key Categories, New TransUnion Analysis Finds&#8221;<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-984166","post","type-post","status-publish","format-standard","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Auto Loan Fraud Losses More Than Triple in Key Categories, New TransUnion Analysis Finds - Market Newsdesk<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.marketnewsdesk.com\/index.php\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Auto Loan Fraud Losses More Than Triple in Key Categories, New TransUnion Analysis Finds - Market Newsdesk\" \/>\n<meta property=\"og:description\" content=\"Fraudsters are using sophisticated identity schemes, driving larger auto loan losses from fewer incidents CHICAGO, July 23, 2026 (GLOBE NEWSWIRE) &#8212; TransUnion (NYSE: TRU) today released new research revealing that despite a decline in incidents across many fraud types, fraud losses in auto lending have increased significantly in recent years. The findings point to a fraud environment impacting dealerships and auto lenders where fewer events drive greater financial losses. Today\u2019s fraudsters have evolved to concentrate on higher-value opportunities throughout the lending lifecycle, especially as new and used vehicle prices reach heightened levels. Auto lenders are facing substantially higher fraud-related losses across multiple fraud categories. Between Q3 2018 and Q3 2025, losses tied to first-party, third-party and synthetic fraud increased significantly. &hellip; Continue reading &quot;Auto Loan Fraud Losses More Than Triple in Key Categories, New TransUnion Analysis Finds&quot;\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.marketnewsdesk.com\/index.php\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\/\" \/>\n<meta property=\"og:site_name\" content=\"Market Newsdesk\" \/>\n<meta property=\"article:published_time\" content=\"2026-07-23T16:16:10+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.globenewswire.com\/newsroom\/ti?nf=OTc2NjY1OCM3NzE3MTE2IzIwMDk4NzQ=\" \/>\n<meta name=\"author\" content=\"Newsdesk\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Newsdesk\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.marketnewsdesk.com\\\/index.php\\\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.marketnewsdesk.com\\\/index.php\\\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\\\/\"},\"author\":{\"name\":\"Newsdesk\",\"@id\":\"https:\\\/\\\/www.marketnewsdesk.com\\\/#\\\/schema\\\/person\\\/482f27a394d4fda80ecb5499e519d979\"},\"headline\":\"Auto Loan Fraud Losses More Than Triple in Key Categories, New TransUnion Analysis Finds\",\"datePublished\":\"2026-07-23T16:16:10+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.marketnewsdesk.com\\\/index.php\\\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\\\/\"},\"wordCount\":940,\"image\":{\"@id\":\"https:\\\/\\\/www.marketnewsdesk.com\\\/index.php\\\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.globenewswire.com\\\/newsroom\\\/ti?nf=OTc2NjY1OCM3NzE3MTE2IzIwMDk4NzQ=\",\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.marketnewsdesk.com\\\/index.php\\\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\\\/\",\"url\":\"https:\\\/\\\/www.marketnewsdesk.com\\\/index.php\\\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\\\/\",\"name\":\"Auto Loan Fraud Losses More Than Triple in Key Categories, New TransUnion Analysis Finds - 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Market Newsdesk","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.marketnewsdesk.com\/index.php\/auto-loan-fraud-losses-more-than-triple-in-key-categories-new-transunion-analysis-finds\/","og_locale":"en_US","og_type":"article","og_title":"Auto Loan Fraud Losses More Than Triple in Key Categories, New TransUnion Analysis Finds - Market Newsdesk","og_description":"Fraudsters are using sophisticated identity schemes, driving larger auto loan losses from fewer incidents CHICAGO, July 23, 2026 (GLOBE NEWSWIRE) &#8212; TransUnion (NYSE: TRU) today released new research revealing that despite a decline in incidents across many fraud types, fraud losses in auto lending have increased significantly in recent years. The findings point to a fraud environment impacting dealerships and auto lenders where fewer events drive greater financial losses. Today\u2019s fraudsters have evolved to concentrate on higher-value opportunities throughout the lending lifecycle, especially as new and used vehicle prices reach heightened levels. Auto lenders are facing substantially higher fraud-related losses across multiple fraud categories. 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