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A combination of mass identity data compromise and the increasing abilities of organized fraud rings has created a synthetic identity epidemic that is impacting all markets. Here are the three ways that synthetic identities are generally created: Credit applications and inquiries that result in synthetic credit profile creation or build. Exploitation of the authorized user process designed to take over or piggyback on legitimate credit profiles. Data furnishing schemes that falsify regular credit reporting agency updates. When it comes to fighting synthetic fraud, we all need to be a part of the solution – or we are just a part of the problem. Mitigate synthetic identity fraud >
School’s out, and graduation brings excitement, anticipation and bills. Oh, boy, here come the student loans. Are graduates ready for the bills? Even before they have a job lined up? With lots of attention from the media, I was interested in analyzing student loan debt to see if this is a true issue or just a headline grab. There’s no shortage of headlines alluding to a student loan crisis: “How student loans are crushing millennial entrepreneurialism” “Student loan debt in 2017: A $1.3 trillion crisis” “Why the student loan crisis is even worse than people think” Certainly sounds like a crisis. However, I’m a data guy, so let’s look at the data. Pulling from our data, I analyzed student loan trades for the last four years starting with outstanding debt — which grew 21 percent since 2013 to reach a high of $1.49 trillion in the fourth quarter of 2016. I then drilled down and looked at just student loan trades. Created with Highstock 5.0.7Total Number of Student Loans TradesStudent Loan Total TradesNumber of trades in millions174,961,380174,961,380182,125,450182,125,450184,229,650184,229,650181,228,130181,228,130Q4 2013Q4 2014Q4 2015Q4 2016025M50M75M100M125M150M175M200MSource: Experian (function(){ function include(script, next) {var sc=document.createElement("script");sc.src = script;sc.type="text/javascript";sc.onload=function() {if (++next < incl.length) include(incl[next], next);};document.head.appendChild(sc);}function each(a, fn){if (typeof a.forEach !== "undefined"){a.forEach(fn);}else{for (var i = 0; i < a.length; i++){if (fn) {fn(a[i]);}}}}var inc = {},incl=[]; each(document.querySelectorAll("script"), function(t) {inc[t.src.substr(0, t.src.indexOf("?"))] = 1;});each(Object.keys({"https://code.highcharts.com/stock/highstock.js":1,"https://code.highcharts.com/adapters/standalone-framework.js":1,"https://code.highcharts.com/highcharts-more.js":1,"https://code.highcharts.com/highcharts-3d.js":1,"https://code.highcharts.com/modules/data.js":1,"https://code.highcharts.com/modules/exporting.js":1,"http://code.highcharts.com/modules/funnel.js":1,"http://code.highcharts.com/modules/solid-gauge.js":1}),function (k){if (!inc[k]) {incl.push(k)}});if (incl.length > 0) { include(incl[0], 0); } function cl() {if(typeof window["Highcharts"] !== "undefined"){new Highcharts.Chart("highcharts-79eb8e0a-4aa9-404c-bc5f-7da876c38b0f", {"chart":{"type":"column","inverted":true,"polar":false,"style":{"fontFamily":"Arial","color":"#333","fontSize":"12px","fontWeight":"normal","fontStyle":"normal"}},"plotOptions":{"series":{"dataLabels":{"enabled":true},"animation":true}},"title":{"text":"Student Loan Total Trades","style":{"fontFamily":"Arial","color":"#333333","fontSize":"18px","fontWeight":"bold","fontStyle":"normal","fill":"#333333","width":"792px"}},"subtitle":{"text":"","style":{"fontFamily":"Arial","color":"#666666","fontSize":"16px","fontWeight":"normal","fontStyle":"normal","fill":"#666666","width":"792px"}},"exporting":{},"yAxis":[{"title":{"text":"Number of trades in millions","style":{"fontFamily":"Arial","color":"#666666","fontSize":"16px","fontWeight":"normal","fontStyle":"normal"}},"labels":{"format":""},"type":"linear"}],"xAxis":[{"title":{"style":{"fontFamily":"Arial","color":"#666666","fontSize":"16px","fontWeight":"normal","fontStyle":"normal"},"text":""},"reversed":true,"labels":{"format":"{value:}"},"type":"linear"}],"series":[{"data":[["Total Student Loans",174961380]],"name":"Q4 2013","turboThreshold":0,"_colorIndex":0,"_symbolIndex":0},{"data":[["Total Student Loans",182125450]],"name":"Q4 2014","turboThreshold":0,"_colorIndex":1,"_symbolIndex":1},{"data":[["Total Student Loans",184229650]],"name":"Q4 2015","turboThreshold":0,"_colorIndex":2,"_symbolIndex":2},{"data":[["Total Student Loans",181228130]],"name":"Q4 2016","turboThreshold":0,"_colorIndex":3,"_symbolIndex":3}],"colors":["#26478d","#406eb3","#632678","#982881"],"legend":{"itemStyle":{"fontFamily":"Arial","color":"#333333","fontSize":"12px","fontWeight":"normal","fontStyle":"normal","cursor":"pointer"},"itemHiddenStyle":{"fontFamily":"Arial","color":"#cccccc","fontSize":"18px","fontWeight":"normal","fontStyle":"normal"},"layout":"horizontal","floating":false,"verticalAlign":"bottom","x":0,"align":"center","y":0},"credits":{"text":"Source: Experian"}});}else window.setTimeout(cl, 20);}cl();})(); Over the past four years, student loan trades grew 4 percent, but saw a slight decline between 2015 and 2016. The number of trades isn’t growing as fast as the amount of money that people need. The average balance per trade grew 17 percent to $8,210. Either people are not saving enough for college or the price of school is outpacing the amount people are saving. I shifted the data and looked at the individual consumer rather than the trade level. Created with Highstock 5.0.7Student Loan Average Balance per Trade4.044.043.933.933.893.893.853.85Q4 2013Q4 2014Q4 2015Q4 201600.511.522.533.544.5Source: Experian (function(){ function include(script, next) {var sc=document.createElement("script");sc.src = script;sc.type="text/javascript";sc.onload=function() {if (++next < incl.length) include(incl[next], next);};document.head.appendChild(sc);}function each(a, fn){if (typeof a.forEach !== "undefined"){a.forEach(fn);}else{for (var i = 0; i < a.length; i++){if (fn) {fn(a[i]);}}}}var inc = {},incl=[]; each(document.querySelectorAll("script"), function(t) {inc[t.src.substr(0, t.src.indexOf("?"))] = 1;});each(Object.keys({"https://code.highcharts.com/stock/highstock.js":1,"https://code.highcharts.com/adapters/standalone-framework.js":1,"https://code.highcharts.com/highcharts-more.js":1,"https://code.highcharts.com/highcharts-3d.js":1,"https://code.highcharts.com/modules/data.js":1,"https://code.highcharts.com/modules/exporting.js":1,"http://code.highcharts.com/modules/funnel.js":1,"http://code.highcharts.com/modules/solid-gauge.js":1}),function (k){if (!inc[k]) {incl.push(k)}});if (incl.length > 0) { include(incl[0], 0); } function cl() {if(typeof window["Highcharts"] !== "undefined"){new Highcharts.Chart("highcharts-66c10c16-1925-40d2-918f-51214e2150cf", {"chart":{"type":"column","polar":false,"style":{"fontFamily":"Arial","color":"#333","fontSize":"12px","fontWeight":"normal","fontStyle":"normal"},"inverted":true},"plotOptions":{"series":{"dataLabels":{"enabled":true},"animation":true}},"title":{"text":"Student Loan Average Number of Trades per Consumer","style":{"fontFamily":"Arial","color":"#333333","fontSize":"18px","fontWeight":"bold","fontStyle":"normal","fill":"#333333","width":"356px"}},"subtitle":{"text":"","style":{"fontFamily":"Arial","color":"#666666","fontSize":"16px","fontWeight":"normal","fontStyle":"normal","fill":"#666666","width":"356px"}},"exporting":{},"yAxis":[{"title":{"text":"","style":{"fontFamily":"Arial","color":"#666666","fontSize":"14px","fontWeight":"normal","fontStyle":"normal"}},"type":"linear","labels":{"format":"{value}"}}],"xAxis":[{"title":{"style":{"fontFamily":"Arial","color":"#666666","fontSize":"14px","fontWeight":"normal","fontStyle":"normal"}},"type":"linear","labels":{"format":"{}"}}],"colors":["#26478d","#406eb3","#632678","#982881","#ba2f7d"],"series":[{"data":[["Average Trades per Consumer",4.04]],"name":"Q4 2013","turboThreshold":0,"_colorIndex":0},{"data":[["Average Trade per Consumer",3.93]],"name":"Q4 2014","turboThreshold":0,"_colorIndex":1},{"data":[["Average Trade per Consumer",3.89]],"name":"Q4 2015","turboThreshold":0,"_colorIndex":2},{"data":[["Average Trades per Consumer",3.85]],"name":"Q4 2016","turboThreshold":0,"_colorIndex":3}],"legend":{"floating":false,"itemStyle":{"fontFamily":"Arial","color":"#333333","fontSize":"12px","fontWeight":"bold","fontStyle":"normal","cursor":"pointer"},"itemHiddenStyle":{"fontFamily":"Arial","color":"#cccccc","fontSize":"18px","fontWeight":"normal","fontStyle":"normal"},"layout":"horizontal"},"credits":{"text":"Source: Experian"}});}else window.setTimeout(cl, 20);}cl();})(); The number of overall student loan trades per consumer is down to 3.85, a decrease of 5 percent over the last four years. This is explained by an increase in loan consolidations as well as the better planning by students so that they don’t have to take more student loans in the same year. Lastly, I looked at the average balance per consumer. This is the amount that consumers, on average, owe for their student loan trades. Created with Highstock 5.0.7Balance in thousands ($)Quarterly $USD Debt per ConsumerQ4 Student Loan TrendsAverage Student Loan Debt Balance per Consumer27,93427,93429,22629,22630,52330,52332,06132,061Q4 2013Q4 2014Q4 2015Q4 201605,00010,00015,00020,00025,00030,00035,000Source: Experian (function(){ function include(script, next) {var sc=document.createElement("script");sc.src = script;sc.type="text/javascript";sc.onload=function() {if (++next < incl.length) include(incl[next], next);};document.head.appendChild(sc);}function each(a, fn){if (typeof a.forEach !== "undefined"){a.forEach(fn);}else{for (var i = 0; i < a.length; i++){if (fn) {fn(a[i]);}}}}var inc = {},incl=[]; each(document.querySelectorAll("script"), function(t) {inc[t.src.substr(0, t.src.indexOf("?"))] = 1;});each(Object.keys({"https://code.highcharts.com/stock/highstock.js":1,"https://code.highcharts.com/adapters/standalone-framework.js":1,"https://code.highcharts.com/highcharts-more.js":1,"https://code.highcharts.com/highcharts-3d.js":1,"https://code.highcharts.com/modules/data.js":1,"https://code.highcharts.com/modules/exporting.js":1,"http://code.highcharts.com/modules/funnel.js":1,"http://code.highcharts.com/modules/solid-gauge.js":1}),function (k){if (!inc[k]) {incl.push(k)}});if (incl.length > 0) { include(incl[0], 0); } function cl() {if(typeof window["Highcharts"] !== "undefined"){Highcharts.setOptions({lang:{"thousandsSep":","}});new Highcharts.Chart("highcharts-0b893a55-8019-4f1a-9ae1-70962e668355", {"chart":{"type":"column","inverted":true,"polar":false,"style":{"fontFamily":"Arial","color":"#333","fontSize":"12px","fontWeight":"normal","fontStyle":"normal"}},"plotOptions":{"series":{"dataLabels":{"enabled":true},"animation":true}},"title":{"text":"Average Student Loan Balance per Consumer","style":{"fontFamily":"Arial","color":"#333333","fontSize":"18px","fontWeight":"bold","fontStyle":"normal","fill":"#333333","width":"308px"}},"subtitle":{"text":"","style":{"fontFamily":"Arial","color":"#666666","fontSize":"16px","fontWeight":"normal","fontStyle":"normal","fill":"#666666","width":"792px"}},"exporting":{},"yAxis":[{"title":{"text":"Balance numbers are in thousands ($)","style":{"fontFamily":"Arial","color":"#666666","fontSize":"16px","fontWeight":"normal","fontStyle":"normal"}},"labels":{"format":"{value:,1f}"},"reversed":false}],"xAxis":[{"title":{"style":{"fontFamily":"Arial","color":"#666666","fontSize":"16px","fontWeight":"normal","fontStyle":"normal"},"text":"Balance in thousands ($)"},"labels":{"format":"{value:}"},"type":"linear","reversed":true,"opposite":false}],"series":[{"data":[["Average Balance per Consumer",27934]],"name":"Q4 2013","turboThreshold":0,"_colorIndex":0},{"data":[["Average Balance per Consumer",29226]],"name":"Q4 2014","turboThreshold":0,"_colorIndex":1},{"data":[["Average Balance per Consumer",30523]],"name":"Q4 2015","turboThreshold":0,"_colorIndex":2},{"data":[["Average Balance per Consumer",32061]],"name":"Q4 2016","turboThreshold":0,"_colorIndex":3}],"colors":["#26478d","#406eb3","#632678","#982881"],"legend":{"itemStyle":{"fontFamily":"Arial","color":"#333333","fontSize":"12px","fontWeight":"bold","fontStyle":"normal","cursor":"pointer"},"itemHiddenStyle":{"fontFamily":"Arial","color":"#cccccc","fontSize":"18px","fontWeight":"normal","fontStyle":"normal"}},"lang":{"thousandsSep":","},"credits":{"text":"Source: Experian"}});}else window.setTimeout(cl, 20);}cl();})(); Here we see a growth of 15 percent over the last four years. At the end of 2016, the average person with a student loan balance had just over $32,000 outstanding. While this is a large increase, we should compare it with other purchases: This balance is no more than a person purchasing a brand-new car without a down payment. While we’re seeing an increase in overall outstanding debt and individual loan balances, I’m not yet agreeing that this is the crisis the media portrays. If students are educated about the debt that they’re taking out and making sure that they’re able to repay it, the student loan market is performing as it should. It’s our job to help educate students and their families about making good financial decisions. These discussions need to be had before debt is taken out, so it’s not a shock to the student upon graduation.
There’s a new crew coming of age. Enter Generation Z. Gen Z — those born between the mid-1990s and the early 2000s — makes up one-quarter of the U.S. population. By 2020, they’ll account for 40% of all consumers. The oldest members of this next cohort — 18- to 20-year-olds — are coming of age. Here are some insights on how this initial segment of Gen Z is beginning to use credit. Credit scores averaged 631 in 2016. Debt levels — consisting largely of bankcards and auto and student loans — are low, with an average debt-to-income ratio of just 5.7%. Average income is $33,800. This generation is being raised in an era of instant, always-on access. They expect a quick, seamless and customized mobile experience. You have just 8 seconds to capture their attention. Webinar: A First Look at Gen Z and Credit
The State of Credit Unions 2017 In the financial services universe, there is no shortage of players battling for consumer attention and share of wallet. Here’s a look at how one player — credit unions — has fared over the past two years compared to banks and online lenders: Personal loans grew 2%, but online lenders and finance companies still own 51% of this market. Card originations at credit unions increased 18%, with total credit limits on newly originated cards approaching $100 billion in Q1 2017. Mortgage market share rose 7% for credit unions, while banks lost share to online lenders. Auto originations increased 25% for credit unions to 1.93 million accounts in Q1 2017. Whether your organization is a credit union, a financial institution or an online lender, a “service first” mentality is essential for success in this highly competitive market. The State of Credit Unions 2017
Mitigating synthetic identities Synthetic identity fraud is an epidemic that does more than negatively affect portfolio performance. It can hurt your reputation as a trusted organization. Here is our suggested 4-pronged approach that will help you mitigate this type of fraud: Identify how much you could lose or are losing today to synthetic fraud. Review and analyze your identity screening operational processes and procedures. Incorporate data, analytics and cutting-edge tools to enable fraud detection through consumer authentication. Analyze your portfolio data quality as reported to credit reporting agencies. Reduce synthetic identity fraud losses through a multi-layer methodology design that combats both the rise in synthetic identity creation and use in fraud schemes. Mitigating synthetic identity fraud>
The creation of synthetic identities (synthetic id) relies upon an ecosystem of institutions, data aggregators, credit reporting agencies and consumers. All of which are exploited by an online and mobile-driven market, along with an increase in data breaches and dark web sharing. It’s a real and growing problem that’s impacting all markets. With significant focus on new customer acquisition and particular attention being paid to underbanked, emerging, and new-to-country consumers, this poses a large threat to your onboarding and customer management policies, in addition to overall profitability. Synthetic identity fraud is an epidemic that does more than negatively affect portfolio performance. It can hurt your reputation as a trusted organization and expose institutions, like yours, as paths of lesser resistance for fraudsters to use in the creation and farming of synthetic identities. Here is a suggested four-pronged approach to mitigate this type of fraud: The first step is knowing your risk exposure to synthetic identity fraud. Identify how much you could lose or are losing today using a targeted segmentation analysis to examine portfolios or customer populations. Next, review your front- and back-end identity screening operational processes and procedures and analyze that information to ensure you have industry best practices, procedures and verification tools deployed. Then incorporate data, analytics and some of the industry’s cutting edge tools. This enables you to perform targeted consumer authentication and identify opportunities to better capture the majority of fraud and operational waste. Lastly, ensure your organization is part of the solution – not the problem. Analyze your portfolio data quality as reported to credit reporting agencies and then minimize your exposure to negative compliance audit results and reputational risk. Our fraud and identity management consultants can help you reduce synthetic identity fraud losses through a multilayer methodology design that combats the rise in synthetic identity creation and use in fraud schemes.
Subprime vehicle loans When discussing automotive lending, it seems like one term is on everyone’s lips: “subprime auto loan bubble.” But what is the data telling us? Subprime auto lending reached a 10-year record low for Q1. The 30-day delinquency rate dropped 0.5% from Q1 2016 to Q1 2017. Super-prime share of new vehicle loans increased from 27.4% in Q1 2016 to 29.12% in Q1 2017. The truth is, lenders are making rational decisions based on shifts in the market. When delinquencies started going up, the lending industry shifted to more creditworthy customers — average credit scores for both new and used vehicle loans are on the rise. Read more>
Summer spending A study by Experian and Edelman Berland noted that travelers relied heavily on credit for vacation purchases last year — with many planning to charge more than half of their vacation expenses this summer. Of those surveyed about their 2015 summer purchases: 86% spent money on a summer vacation in 2015. $2,275 was spent per person, with $1,308 of that being credit card purchases. 35% hadn’t saved in advance. 61% spent more than they planned. Summer brings vacations and credit card use. By identifying consumer credit trends like these, you can target new customers and identify balance transfer opportunities. Learn more>
Analyzing credit scores and card balances According to a study by VantageScore® Solutions LLC, consumers with credit scores between 601 and 650 carry the largest credit card bills, at more than $10,000 — nearly 2x that of the average consumer. Other key findings include: Those with the highest scores have the largest total credit limit ($46,735), compared with just $2,816 for those with the lowest scores. The average credit card holder has $29,197 in credit lines, with an average balance of $5,720. Those with scores between 701 and 750 use an average of 27% of their available credit versus 47% for those with scores between 651 and 700. The study reinforces the importance of staying current on the latest credit trends to best identify areas of opportunity and adjust lending strategies accordingly. Make better decisions >
Identity theft is frustrating. Not just for people, but for businesses too. According to our recent survey, many Americans are unknowingly engaging in risky behaviors online. Some of the insights that cause concern include: U.S. adults have large digital footprints, storing an average of 3.4 types of personally identifiable information (PII) online. Half don’t think they’re likely to ever experience identity theft because they believe poor credit makes them unappealing targets. A quarter have shared their credit card number or PIN with friends and family. When fraudsters capture your customers’ PII, it impacts them as well as your business. That’s just one of many reasons why you should be helping your customers protect their information. PII security tips for your customers >
Experian’s ID Fraud Tracker, a quarterly analysis of fraud rates across consumer financial products, found that British families who are struggling financially — about 4 million people — are increasingly becoming prime targets of financial fraud. The research performed on data from 2014 to 2016 in the United Kingdom also revealed: There has been a 203% increase in the total number of fraudulent credit applications over the past two years. Current account, credit card and loan fraud were the most common types of credit products fraudsters applied for in other people’s names, making up 94% of the total. 35% of all third-party fraud came from households with high salaries and large disposable incomes. Fraud’s increasing around the world. We all have a responsibility to be vigilant and take measures to protect our business and customers, online and offline. Protect your customers >
Credit reports provide a wealth of information. But did you know credit attributes are the key to extracting critical intelligence from each credit report? Adding attributes into your decisioning enables you to: Improve acquisition strategies and implement policy rules with precision. Segment your scored population for more refined risk assessment. Design more enticing offers and increase book rates. Attributes can help you make more informed decisions by providing a more granular picture of the consumer. And that can make all the difference when it comes to smart lending decisions. Video: Making better decisions with credit attributes
Although the average mortgage rate was more than 4% at the end of the first quarter*, Q1 mortgage originations were nearly $450 billion — a 5% increase over the $427 billion a year earlier. As prime homebuying season kicks off, lenders can stay ahead of the competition by using advanced analytics to target the right customers and increase profitability. Revamp your mortgage and HELOC acquisitions strategies>
Experian and Creative Strategies share survey results about Apple’s AirPods, Google Home, Amazon Echo and Echo Dot for consumer behavior with voice devices.
During our recent webinar, Detect and Prevent: The current state of e-commerce fraud, Julie Conroy, Aite Group research director, shared 5 key trends relating to online fraud: Rising account takeover fraud. Targeting of loyalty points. Growing global transactions. Frustrating false declines. Increasingly mobile consumers. Fraud is increasing. Be prepared. Protect your business and customers with a multilayered approach to fraud prevention. For more trends and predictions, watch the webinar recording.