Credit Lending
The economic expansion just passed the eight-year mark, and consumer credit defaults across mortgages, bankcards and auto loans are at pre–financial crisis levels. More specifically: The first-mortgage default rate dropped 4 basis points from May to 0.60%. The bankcard default rate experienced its first drop in 9 months, with a decrease of 4 basis points bringing it to 3.49%. Auto loan defaults decreased 3 basis points from the previous month to 0.82%. With inflation at 1% to 2%, debt service levels close to record lows, and disposable income increasing and supporting spending growth, consumers are in good financial shape nationally. Lenders should take this opportunity to review and adjust their acquisition strategies accordingly. Can your originations platform capitalize on this?
CFPB and credit invisibles A recent study by the Consumer Financial Protection Bureau (CFPB) found that American consumers establish credit differently depending on their economic background. The study revealed that: Consumers in lower-income areas are 240% more likely to become credit visible due to negative information, such as a debt in collection. Those in higher-income areas become credit visible in a more positive way. For example, these consumers are 30% more likely to become credit visible through the use of a credit card. The percentage of consumers transitioning to credit visibility due to student loans more than doubled in the last 10 years. Policymakers can make it easier for consumers to become more credit visible by clearly defining the term alternative data and supporting the use of alternative data sources that meet legal and societal standards for accuracy, validity, predictability and fairness. Learn more >
Historical data that illustrates lower credit card use and increases in payments is key to finding consumers whose credit trajectory is improving. But positive changes in consumer behavior—especially if it happens slowly over time—don’t necessarily impact a consumer’s credit score. And many lenders are missing out on capturing new business by failing to take a closer look. It’s easy to categorize consumers by their credit score alone, but you owe it to your bottom line to investigate further: Are the consumer’s overall payments increasing? Is his credit card utilization decreasing? Are the overall card balances remaining consistent or declining? Could the consumer be within your credit score guidelines within a month or two? And most importantly, could a competitor acquire the consumer a month or two after you declined him? Identifying new customers who previously used credit responsibly is relatively easy since they typically have rich credit profiles that may include a mortgage and numerous types of credit accounts. But how do you evaluate consumers who may look identical? Trended data and attributes provide insight into whether a consumer is headed in the right direction: With more than 613 trended attributes available for real-time decisioning and for batch campaigns, Experian trends key factors that provide the insight needed for lenders to lend deeper without sacrificing credit quality. Looking at trended data and attributes is critical for portfolio growth, and credit line increases based on good credit behavior is a must for lenders for two reasons. First, you’ve already spent the money acquiring the consumer and you should not waste the opportunity to maximize returns. Second, competition is fierce; another lender could reward the consumer for great credit behavior they’ve displayed with your company. Be there first, be consistent, or be left behind. Use Experian’s Payment Stress Attributes and Short-term Utilization Attributes in custom scores or swap-set strategies in order to find quality customers who may be worthy of line increases or other attribute credit terms. Look to trended data to swap in consumers who may fall within a few points under your credit score guidelines, and reward your existing customers before another lender does. Near-prime consumers of today are the prime consumers of tomorrow.
1 in 10 Americans are living paycheck to paycheck Financial health means more than just having a great credit score or money in a savings account. It includes being able to manage daily finances, save for the future and weather a financial shock. Here are some facts about Americans’ financial health: 46% of Americans are struggling financially. Roughly 31% of nonretired adults have no retirement savings or pension. Approximately 50% are unprepared for a financial emergency, and about 1 in 5 have no savings set aside to cover unexpected emergencies. It’s never too late for people to achieve financial health. By providing education on money management, you can drive new opportunities for increased engagement, loyalty and long-term revenue streams. Why financial health matters >
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 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 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 $USD Debt per ConsumerQ4 Student Loan TrendsAverage Student Loan Debt Balance per Consumer27,93427,93429,22629,22630,52330,52332,06132,061Q4 2013Q4 2014Q4 2015Q4 201605,00010,00015,00020,00025,00030,00035,000Source: Experian (function(){ function include(script, next) {var sc=document.createElement(\"script\");sc.src = script;sc.type=\"text/javascript\";sc.onload=function() {if (++next < incl.length) include(incl[next], next);};document.head.appendChild(sc);}function each(a, fn){if (typeof a.forEach !== "undefined"){a.forEach(fn);}else{for (var i = 0; i 0) { include(incl[0], 0); } function cl() {if(typeof window[\"Highcharts\"] !== \"undefined\"){Highcharts.setOptions({lang:{\"thousandsSep\":\",\"}});new Highcharts.Chart(\"highcharts-0b893a55-8019-4f1a-9ae1-70962e668355\", {\"chart\":{\"type\":\"column\",\"inverted\":true,\"polar\":false,\"style\":{\"fontFamily\":\"Arial\",\"color\":\"#333\",\"fontSize\":\"12px\",\"fontWeight\":\"normal\",\"fontStyle\":\"normal\"}},\"plotOptions\":{\"series\":{\"dataLabels\":{\"enabled\":true},\"animation\":true}},\"title\":{\"text\":\"Average Student Loan Balance per Consumer\",\"style\":{\"fontFamily\":\"Arial\",\"color\":\"#333333\",\"fontSize\":\"18px\",\"fontWeight\":\"bold\",\"fontStyle\":\"normal\",\"fill\":\"#333333\",\"width\":\"308px\"}},\"subtitle\":{\"text\":\"\",\"style\":{\"fontFamily\":\"Arial\",\"color\":\"#666666\",\"fontSize\":\"16px\",\"fontWeight\":\"normal\",\"fontStyle\":\"normal\",\"fill\":\"#666666\",\"width\":\"792px\"}},\"exporting\":{},\"yAxis\":[{\"title\":{\"text\":\"Balance numbers are in thousands ($)\",\"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.
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
Millennials have long been the hot topic over the course of the past few years with researchers, brands and businesses all seeking to understand this large group of people. As they buy homes, start families and try to conquest their hefty student loan burdens, all will be watching. Still, there is a new crew coming of age. Enter Gen Z. It is estimated that they make up ¼ of the U.S. population, and by 2020 they will account for 40% of all consumers. Understanding them will be critical to companies wanting to succeed in the next decade and beyond. The oldest members of this next cohort are between the ages of 18 and 20, and the youngest are still in elementary school. But ultimately, they will be larger than the mystical Millennials, and that means more bodies, more buying power, more to learn. Experian recently took a first look at the oldest members of this generation, seeking to gain insights into how they are beginning to use credit. In regards to credit scores, the eldest Gen Z members sported a VantageScore® of 631 in 2016. By comparison, younger Millennials were at 626 and older Millennials were at 638. Given their young age, Gen Z debt levels are low with an average debt-to-income at just 5.7%. Their tradelines largely consist of bankcards, auto and student loans. Their average income is at $33.8k. For their total annual plastic spend, data reveals this oldest group of Gen Z spent about $9.5k, slightly more than the younger Millennials who came in at roughly $9k. Surprisingly, there was a very small group of Gen Z already on file with a mortgage, but this figure was less than .5%. Auto loans were also small, but likely to grow. Of those Gen Z members who have a credit file, an estimated 12% have an auto trade. This is just the beginning, and as they age, their credit files will thicken, and more insights will be gained around how they are managing credit, debt and savings. While they are young today, some studies say they already receive about $17 a week in allowance, equating to about $44 billion annually in purchase power in the U.S. Factor in their influence on parental or household purchases and the number could be closer to $200 billion! For all brands, financial services companies included, it is obvious they will need to engage with this generation in not just a digital manner, but a mobile manner. They are being raised in an era of instant, always-on access. They expect a quick, seamless and customized mobile experience. Retailers have 8 seconds or less — err on the side of less — to capture their attention. In general, marketers and lenders should consider the following suggestions: Message with authenticity Maintain a long-term vision Connect them with something bigger Provide education for financial literacy and of course Keep up with technological advances. Learn more by accessing our recorded webinar, A First Look at Gen Z and Credit.
Call it big data, smart data or evidence-based decision-making. It’s not just the latest fad, it’s the future of how business will be guided and grow. Here are a few telling stats that show data is exploding and a new age is upon us: Data is growing faster than ever before, and we’re on track to create about 1.7 megabytes of new information per person every second by 2020. The social universe—which includes every digitally connected person—doubles in size every two years. By 2020, it will reach 44 zettabytes or 44 trillion gigabytes, according to CIO. In 2015, more than 1 billion people used Facebook and sent an average of 31.25 million messages and viewed 2.77 million videos each minute. More than 100 terabytes of data is uploaded daily to the social channel. By 2020, more than 6.1 billion smartphone users will exist globally. And there will be more than 50 billion smart connected devices in the world, all capable of collecting, analyzing and sharing a wealth of data. More than one-third of all data will pass through or exist in the cloud by 2020. The IDC estimates that by 2020, business transactions on the internet—business-to-business and business-to-consumer—will reach 450 billion per day. All of this new data means we’ll be looking at a whole new set of possibilities and a new level of complexity in the years ahead. The data itself is of great value, however, lenders need the right automated decisioning platform to store, collect, quickly process and analyze the volumes of consumer data to gain accurate consumer stories. While lenders don’t necessarily need to factor in decisioning on social media uploads and video views, there is an expectation for immediacy to know if a consumer is approved, denied or conditioned. Online lenders have figured out how to quickly capture and understand big data, and are expected to account for $122 billion in lending by 2020. This places more pressure on banks and credit unions to enhance their technology to cut down on loan approval times and move away from various manual touch points. Critics of automated decisioning solutions used in lending cite compliance issues, complacency by lenders and lack of human involvement. But a robust platform enables lenders to improve and supplement their current decisioning processes because it is: Agile: Experian hosts our client’s solutions and decisioning strategies, so we are able to make and deploy changes quickly as the needs of the market and business change, and deliver real-time instant decisions while a consumer is at the point of sale. A hosted environment also means reduced implementation timelines, as no software or hardware installation is required, allowing lenders to recognize value faster. A data work horse: Internal and external data can be pulled from multiple sources into a lender’s decisioning model. Lenders may also access an unlimited number of scores and attributes—including real-time access to credit bureau data—and integrate third-party data sources into the decisioning engine. Powerful: A robust decision engine is capable of calculating numerous predictive attributes and custom scoring models, and can also test new strategies against current decision models or perform “what if” simulations on historical data. Data collection, storage and analysis are here to stay. As will be the businesses which are savvy enough to use a solution that can find opportunities and learnings in all of that complex data, quickly curate the best possible actions to take for positive outcomes, and allow lenders and marketers to execute on those recommendations with the click of a button. To learn more about Experian’s decisioning solutions, you can additionally explore our PowerCurve and Attribute Toolbox solutions.
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>
How do credit unions stack up in a pack filled with heavy-hitting banks and aggressive online lenders? Do credit scores, debt levels and utilization rates look different between credit union members and non-credit union members? Where is the greatest concentration of credit unions in the country? Experian took a deep dive into the data and performance surrounding the credit union universe in their first-ever “State of Credit Unions” report, featuring insights utilizing data from both 2015 and 2017. What did the analysis reveal? “In general, we saw credit unions continuing to increase their auto lending market share, but we also saw them growing their member relationships and increasing market share in mortgage, personal loan and bankcard,” said Michelle Cocchiarella, the Experian analyst who pulled the data. A few of the key data points include: Credit union auto originations increased from 1.54M new accounts in Q1 2015 to 1.93M in Q1 2017 – a 25% increase. And not only did originations rise dramatically in this space, but credit unions topped banks, captives and other finance sources. Credit union auto market share rose 5% between Q1 2015 and Q1 2017, while bank market share declined by 4%. Credit unions also saw growth in the personal loan arena, with market share rising 2% between Q1 2015 and Q1 2017. Still, with the rise of online lenders, that sector saw a 7% increase during the same period. Banks declined by 5%. While most bankcards are opened with banks, credit unions did experience an 18% increase in bankcard originations from Q1 2015 to Q1 2017. Market share rose 1% between Q1 2015 and Q1 2017 for credit unions in the bankcard space. Banks reign with market share at 96%. Credit union mortgage market share rose 7% between Q1 2015 and Q1 2017. Banks declined by 4%. “Collectively, the credit union space is enjoying remarkable membership and loan growth,” said Scott Butterfield, principal of Your Credit Union Partner, a consulting agency to credit union leaders. “However, this bountiful experience is not enjoyed at all credit unions. The financial services environment has never been more competitive. The best credit unions are relentless at investigating a better way to find and serve more members, and as such, are seeing great growth.” For the complete results, including insights on how credit union members with at least one trade compare to non-credit union members, access the report on our credit union insights page.
When discussing automotive lending, it seems like one term is on everyone’s lips: “subprime auto loan bubble.” There’s always someone who claims that the bubble is bursting. But a level-headed look at the data shows otherwise. According to our Q1 2017 State of the Automotive Finance Market report, 30-day delinquencies dropped and subprime auto lending reached a 10-year record low for Q1. The 30-day delinquency rate dropped from 2.1 percent in Q1 2016 to 1.96 percent in Q1 2017, while the total share of subprime and deep-subprime loans dropped from 26.48 percent in Q1 2016 to 24.1 percent in Q1 2017. The truth is, lenders are making rational decisions based on shifts in the market. When delinquencies started to go up, the lending industry shifted to more creditworthy customers. This is borne out in the rise in customers’ average credit scores for both new and used vehicle loans: The average customer credit score for a new vehicle loan rose from 712 in Q1 2016 to 717 in Q1 2017. The average customer credit score for a used vehicle loan rose from 645 in Q1 2016 to 652 in Q1 2017. In a clear indication that lenders have shifted focus to more creditworthy customers, super prime was the only risk tier to grow for new vehicle loans from Q1 2016 to Q1 2017. Super-prime share moved from 27.4 percent in Q1 2016 to 29.12 percent in Q1 2017. All other risk tiers lost share in the new vehicle loan category: Prime — 43.36 percent, Q1 2016 to 43.04 percent, Q1 2017. Nonprime — 17.83 percent, Q1 2016 to 16.96 percent in Q1 2017. Subprime — 10.64 percent, Q1 2016 to 10.1 percent in Q1 2017. For used vehicle loans, there was a similar upward shift in creditworthiness. Prime and super-prime risk tiers combined for 47.4 percent market share in Q1 2017, up from 43.99 percent in Q1 2017. At the low end of the credit spectrum, subprime and deep-subprime share fell from 34.31 percent in Q1 2016 to 31.27 percent in Q1 2017. The upward shift in used vehicle loan creditworthiness is likely caused by an ample supply of late model used vehicles. Leasing has been on the rise for the past several years (and is at 31.06 percent of all new vehicle financing today). Many of these leased vehicles have come back to the market as low-mileage used vehicles, perfect for CPO programs. Another key indicator of the lease-to-CPO impact is the rise in used vehicle loan share for captives. In Q1 2017, captives had 8.3 percent used vehicle loan share, compared with 7.2 percent in Q1 2016. In other findings: Captives continued to dominate new vehicle loan share, moving from 49.4 percent in Q1 2016 to 53.9 percent in Q1 2017. 60-day delinquencies showed a slight rise, going from 0.61 percent in Q1 2016 to 0.67 percent in Q1 2017. The average new vehicle loan reached a record high: $30,534. The average monthly payment for a new vehicle loan reached a record high: $509. For more information regarding Experian’s insights into the automotive marketplace, visit https://www.experian.com/automotive.
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 >
The 1990s brought us a wealth of innovative technology, including the Blackberry, Windows 98, and Nintendo. As much as we loved those inventions, we moved on to enjoy better technology when it became available, and now have smartphones, Windows 10 and Xbox. Similarly, technological and modeling advances have been made in the credit scoring arena, with new software that brings significant benefits to lenders who use them. Later this year, FICO will retire its Score V1, making it mandatory for those lenders still using the old software to find another solution. Now is the time for lenders to take a look at their software and myriad reasons to move to a modern credit score solution. Portfolio Growth As many as 70 million Americans either have no credit score or a thin credit file. One-third of Millennials have never bothered to apply for a credit card, and the percentage of Americans under 35 with credit card debt is at its lowest level in more than 25 years, according to the Federal Reserve. A recent study found that Millennials use cash and debit cards much more than older Americans. Over time, Millennials without credit histories could struggle to get credit. Are there other data sets that provide a window into whether a thin file consumer is creditworthy or not? Modern credit scoring models are now being used in the marketplace without negatively impacting credit quality. For example, VantageScore 3.0 allows for the scoring of 30 million to 35 million more people consumers who are typically unscoreable by other traditional generic credit models. VantageScore 3.0 does this by using a broader, deeper set of credit file data and more advanced modeling techniques. This allows the VantageScore model to more accurately predict unique consumer behaviors—is the consumer paying his utility bill on time?—and better evaluate thin file consumers. Mitigate Risk In today’s ever-changing regulatory landscape, lenders can stay ahead of the curve by relying on innovative credit score models like VantageScore. These models incorporate the best of both worlds by leaning on innovative scoring analytics that are more inclusive, while providing marketplace lenders with assurances the decisioning is both statistically sound and compliant with fair lending laws. Newer solutions also offer enhanced documentation to ease the burden associated with model risk management and regulatory compliance responsibilities. Updated scores Consumer credit scores can vary depending on the type of scoring model a lender uses. If it\'s an old, outdated version, a consumer might be scored lower. If it\'s a newer, more advanced model, the consumer has a better shot at being scored more fairly. Moving to a more advanced scoring model can help broaden the base of potential borrowers. By sticking to old models—and older scores—a sizable number of consumers are left at a disadvantage in the form of a higher interest rate, lower loan amount or even a declined application. Introducing advanced scoring models can provide a more accurate picture of a consumer. As an example, for many of the newest consumer risk models, like FICO Score 9, a consumer’s unpaid medical collection agency accounts will be assessed differently from unpaid non-medical collection agency accounts. This isn\'t true for most pre-2012 consumer risk score versions. Each version contains different nuances for increasing your score, and it’s important to understand what they are. Upgrading your credit score to the latest VantageScore credit score or FICO solution is easier than you think, with a switch to a modern solution taking no longer than eight weeks and your current business processes still in place. Are you ready to reap the rewards of modern credit scoring?
Today is a great day for Experian and our automotive clients. We’ve been working with String Automotive for several years, and have now taken the next step in our relationship, as String Automotive has become part of the Experian family. In today’s generally flat new-car market, successful dealers need the perfect mix of data and market intelligence to drive more sales, cultivate deeper customer relationships and develop new ways of better conquesting customers from their competition. String Automotive’s Dealer Positioning System, matched with our own information and data-driven insights, provides our automotive dealer clients with an ideal solution to grow their businesses. It is the only platform to combine dealership website analytics and inventory information with automotive market, consumer demographic and purchasing behavior data. Simply put, it takes the pulse of each dealership’s local market and guides dealers to make the most profitable, proactive decisions for every store and unique situation. This powerful analytics solution simplifies choices like how to spend marketing dollars and where to target conquesting efforts by letting market and dealership data drive decisions. What’s the bottom line? The Dealer Positioning System increases profitability across the dealership. It’s one thing to hear that message from us, but we also hear of the benefits from our clients. Paul Schnell, digital marketing director at Wilsonville Toyota in Oregon, had this to say: \"There is no \'I wonder if...\' with the Dealer Positioning System®. Now it is, \'I know it and I can act on it today’. Their latest tools give us zip-code-level intelligence that\'s just not available at the dealer level any other way. We are micro-targeting the perfect message with the perfect vehicle to the perfect prospect.\" For more information on Experian or our other automotive products and services, please visit www.experian.com/automotive. For more information about String Automotive and the Dealer Positioning System, please visit http://stringautomotive.com/Dealer_Positioning_System.
Weekend getaways, beach vacations and summer camp are all part of the beauty of summer. But they can come with a hefty price tag, and many consumers delay payment by placing summer fun costs on a credit card. In a recent study by Experian and Edelman Berland, travelers rely heavily on credit for vacation purchases and unexpected costs, and many charge more than half of their vacation this summer. A whopping 86 percent spent money on a summer vacation in 2016—an average of $2,275 per person with $1,308 of that amount on credit card spending. And 35 percent of those surveyed had not saved in advance. Even consumers who budgeted for vacation typically accrue unexpected costs. Sixty-one percent of those who set a budget ended up spending more than they planned. Accumulated debt doesn’t bode well for consumers. In the first quarter of 2016, consumers had an average of $3,910 in credit card debt, according to Experian data. That\'s $44 less than in the fourth quarter of 2015, but up $142 year over year. Overspending on vacation puts consumers in a more hazardous position to rack up debt during the holiday season and carry even higher balances into 2017 and beyond. Many consumers who are overspending consolidate summer debt, and proactive lenders can take advantage of that activity by making timely offers to consumers in need. At the same time, reactive lenders may feel the pain as balances transfer out of their portfolio. By identifying consumers who are likely to engage in card-to-card balance transfers, lenders can prepare for these consumer bankcard trends. Insights can then be used to acquire new customers and balances through prescreen campaigns, while protecting existing balances before they can transfer out of an existing loan portfolio. Lenders can also use tools to estimate a consumer’s spend on all general purpose credit and charge cards over the past year, and then target high-spending consumers with customized offers. With Memorial Day and the end-of-the-school-year fast approaching, card balances are likely already on the rise. Now is the time for lenders to prepare.
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