Credit Lending
Fraudsters invited into bank branches The days of sending an invitation in the mail have for the most part gone by the wayside. Aside from special invitations for weddings and milestone anniversaries, electronic and email invitations have become the norm. However, one major party planner has refused to change practices — banks inviting fraudsters into their banking centers. As a fraud consultant I have the privilege of meeting many banking professionals, and I hear the same issues and struggles over and over again. It’s clear that the rapid increase of fraudulent account-opening applications are top of mind to many. What the executives making policy don’t realize is they’re facing fraud because they’re literally inviting the fraudsters into their branches. Think I’m exaggerating? Let me explain. I often encounter bank policymakers who explain their practice of directing a suspicious person into a banking center. Yes, many banks still direct applicants who cannot be properly verified over the phone or online into their banking center to show proof of identity. Directing or inviting criminals into your bank instead of trying to keep them out is an outdated, high-risk practice — what good can possibly come of it? The argument I typically hear from non-fraud banking professionals: “The bad guys know that if they come into the bank we will have them on film.” Other arguments include that the bad guys are not typically bold enough to actually come into the banking center or that their physical security guards monitor high-traffic banking centers. But often that is where bank policies and employee training ends. Based on my years of experience dealing with banks of all sizes, from the top three global card issuers to small regional banks, let me poke a few holes in the theory that it is a good deterrent to invite perpetrators into your banking center. Let’s role-play how my conversation goes: Me: “When an underwriter with limited fraud training making the decision to direct a suspicious applicant into a banking center, what is the policy criteria to do so?” Bank policymaker: (typical response) “What do you mean?” Me: “What high-risk authentication was used by the underwriter to make the decision to extend an invitation to a high-risk applicant to come into the banking center? If the applicant failed your high-risk authentication questions and you were not able to properly identify them, what authentication tools do the branch managers have that the underwriters do not?” Bank: “Nothing, but they can usually tell when someone is nervous or seems suspicious.” Me: “Then what training do they receive to identify suspicious behaviors?” (You guessed it …) Bank: “None.” (I then switch to the importance of customer experience.) Me: “How do you notify the banking center in advance that the suspicious applicant was invited to come in to provide additional verification?” Bank: “We do not have a policy to notify the banking center in advance.” Me: “What is considered acceptable documentation? And are banking center employees trained on how to review utility statements, state ID cards, drivers’ licenses or other accepted media?“ Bank: “We do not have a list of acceptable documentation that can be used for verification; it is up to the discretion of the banking center representative.” Me: “How do you ensure the physical safety of your employees and customers when you knowingly invite fraudsters and criminals into your banking center? How do you turn down or ask the suspicious person to leave because they do not have sufficient documentation to move forward with the original application for credit? If a suspicious person provides your employee with a possible stolen identification card, is that employee expected to keep it and notify police or return it to the applicant? Are employees expected to make a photocopy of the documentation provided?” The response that I usually receive is, “I am not really sure.” I hope by now you are seeing the risk of these types of outdated practices on suspicious credit applications. The fact is that technology has allowed criminals to make fairly convincing identification at a very low cost. If employees in banking centers are not equipped, properly trained, and well-documented procedures do not exist in your fraud program — perhaps it’s time to reconsider the practice or seek the advice of industry experts. I have spent two decades trying to keep bad guys out of banks, but I can’t help but wonder — why do some still send open invitations to criminals to come visit their bank? If you are not yet ready to stop this type of bad behavior, at the very least you must develop comprehensive end-to-end policies to properly handle such events. This fraud prevention tactic to invite perpetrators into banks was adopted long before the age of real-time decisions, robust fraud scores, big data, decision analytics, knowledge-based authentication, one-time passcodes, mobile banking and biometrics. The world we bank in has changed dramatically in the past five years; customers expect more and tolerate less. If a seamless customer experience and reducing account-opening and first-party fraud are part of your strategic plan, then it is time to consider Experian fraud solutions and consulting.
Time heals countless things, including credit scores. Many of the seven million people who saw their VantageScores drop to sub-prime levels after suffering a foreclosure or short sale during the Great Recession have recovered and are back in the housing market. These Boomerang Buyers — people who foreclosed or short sold between 2007 and 2014 and have opened a new mortgage — will be an important segment of the real estate market in the coming years. According to Experian data, through June 2016 roughly 800,000 people had boomeranged, with Los Angeles, Phoenix, and Sacramento housing the most buyers. Some analysts believe more than three million Americans will become eligible for a home over the next three years. Are potential Boomerang Buyers a great opportunity to boost market share or a high risk for a portfolio? Early trends are positive. The majority of Boomerang Buyers who opened mortgages between 2011 and June 2016 are current on their debts. An Experian study revealed more than 29 percent of those who short sold have boomeranged, and just 1.5 percent are delinquent on their mortgage —falling below the national average of 2.8 percent. This group is also ahead of or even with the national average for delinquency on auto loans (1.2 percent vs. the national average of 2.2 percent), bankcards (3 percent vs. 4.3 percent) and retail (even at 2.7 percent). For those Boomerang Buyers who had foreclosed, the numbers are also strong. More than 12 percent have boomeranged, with just 3 percent delinquent on their mortgage. They also match or are below national average delinquency rates on auto loans (1.9 percent) and bankcards (4.1 percent), and have a slightly higher delinquency rate for retail (3.5 percent). Due to their positive credit behaviors, Boomerang Buyers also have higher VantageScores than before. On average, the overall non-boomerang group’s credit score sunk during a foreclosure but went up 10 percent higher than before the foreclosure, and Boomerang Buyers rose by nearly 14 percent. For people who previously had a prime credit score, their number dropped by nearly 5 percent, while those who boomeranged returned to the score they had prior to the foreclosure. By comparison, the overall non-boomerang and boomerang group saw their credit score drop during a short sale and increase more than 11 percent from before the short sale. For people who previously had prime credit, they dropped 2 percent while those who boomeranged were almost flat to where they were before the short sale. Another part of the equation is the stabilized housing market and relatively low loan-to-value (LTV) limits that lenders have maintained. In the past, borrowers most often strategically defaulted on their mortgages when their LTV ratios were well over 100 percent. So as long as lenders maintain relatively low LTV limits and the housing market remains strong, strategic default is unlikely to re-emerge as a risk.
Experian estimates card-to-card consumer balance transfer activity to be between $35 and $40 billion a year, representing a sizeable opportunity for proactive lenders seeking to grow their revolving product line. This opportunity, however, is a threat for reactive lenders that only measure portfolio attrition instead of working to retain current customers. While billions of dollars are transferred every year, this activity represents only a small percentage of the total card population. And given the expense of direct marketing, lenders seeking to capitalize on and protect their portfolio from balance transfer activity must leverage data insights to make more informed decisions. Predicting a consumer’s future propensity to engage in card-to-card balance transfers starts with trended data. A credit score is a snapshot in time, but doesn’t reveal deep insights about a consumer’s past balance transfer activity. Lenders that rely only on current utilization will group large populations of balance revolvers into one bucket – and many of these individuals will have no intention of transferring to another product in the near future. Still, balance transfer activity can be identified and predicted by utilizing trended data. By analyzing the spend and payment data over time to see when one (or multiple) trade’s payment approximately matches another trade’s spend, we have the logic that suggests there has been a card-to-card transfer. What most people don’t realize is that trended data is difficult to work with. With 24 months of history on five fields, a single trade includes 120 data points. That’s 720 data points for a consumer with six trades on file and 72,000,000 for a file with 100,000 records, not to mention the other data fields in the file. It’s easy to see why even the most sophisticated organizations become paralyzed working with trended data. While teams of analysts get buried in the data, projects drag, costs swell, and eventually the world changes as rates climb and fall. By the time the analysis is complete, it must be recalibrated. But there is a solution. Experian has developed powerful predictions tools that combine past balance transfer history, historical transfer amounts, current trades carried and utilized, payments, and spend. Combined, these data fields can help identify consumers who are most likely to transfer a balance in the future. With Experian’s Balance Transfer Index the highest scoring 10 percent of consumers capture nearly 70 percent of total balance transfer dollars. Imagine the impact on ROI of reducing 90 percent of the marketing cost of your next balance transfer campaign and still reaching 70 percent of the balance transfer activity. Balance transfer activity represents a meaningful dollar opportunity for growth, but is concentrated in a small percentage of the population making predictive analytics key to success. Trended data is essential for identifying those opportunities, but financial institutions must assess their capabilities when it comes to managing the massive data attached. The good news is that regardless of financial institution size, solutions now exist to capture the analytics and provide meaningful and actionable insights to lenders of all sizes.
The pendulum has swung again. The great recession brought a glacial freeze to access to capital. The thaw brought rapid, frictionless underwriting with an almost obsessive focus on growth and customer experience. Enter Marketplace Lenders and their more “flexible” approach to credit risk assessment. While much good has come from this evolution in financing, new challenges have surfaced – especially as it pertains to fraud prevention and credit risk management. Stacking has emerged as a particularly knotty problem in the small business lending space. Applicants have the opportunity to apply for and be approved for multiple loans in a matter of days or even hours. Technology allows for underwriting that is at least somewhat automated and depositing often occurs within hours of approval. The speed of fulfillment is a boon for small businesses. However, it also makes it possible to be approved and draw down funds on multiple loans in quick succession. Core underwriting metrics, such as debt-to-income ratios and cashflow, are unreliable in the face of ratcheting debt from concurrent online business loans. This situation occurs because the window between the approval of the loan and delivery of the funds is much shorter than the timeframe to report the loan to credit reporting agencies and other third-party data suppliers. Not all lenders report small business loans, further compounding the problem. Lenders’ risk and pricing strategies are hamstrung in the face of stacking, whether intentional on the part of the small business or not. If a struggling small business applies for credit and receives multiple loan offers, should we rely on their ability to resist the temptation to accept them all and use the funds wisely? No. The burden rests squarely on the credit provider to proactively address the problem. Technology-enabled frictionless underwriting underpins the online consumer loan space and facilitates a similar, yet subtly different stacking problem. There are a large number of loan providers, with a spectrum of risk appetites and pricing strategies. This all but ensures that a consumer has access to additional loans at an ever-increasing interest rate. The underlying assumption, among the more mainstream, lower-rate providers, is that the consumer is disclosing all of their obligations – including any recent loans. Although reporting in the consumer space is more robust and timely, it is still possible for an applicant to quickly access and draw funds on several loans within a very short timeframe, making it difficult for loan providers to get a full and complete picture of their capacity to repay the loan. The situation is further complicated by lenders at the higher risk, higher rate end of the market whose business models are structured to allow for, and perhaps even encourage, stacking by the consumer. Fortunately, there are a number of steps lenders can take to improve the situation: Contribute credit data to the credit reporting agencies. Know your customer, their industry, their market and underwrite appropriately. Develop a tailored underwriting approach that achieves a balance between frictionless customer experience and prudent credit and risk assessment. All applicants are not equal, and some require additional scrutiny and more time to underwrite. Understand the drivers and indicators of stacking. The latter point is worth emphasizing. The time to address stacking is prior to funding. This requires the lender to anticipate, identify and pre-empt stackers. There is no 100 percent foolproof remedy. However, lenders can stack (pun-intended) the odds in their favor. For example, if an existing loan has a high balance and is delinquent, might that be an indicator of a propensity to stack? What if the business owner has applied for multiple loans, resulting in multiple inquiries, over a 45-day period? A proactive, data-driven anti-stacking strategy can yield positive results, reducing delinquency and losses. In combination with consistent comprehensive reporting to the bureaus, it can go a long way toward reducing the risk posed by this largely invisible threat.
As credit behavior and economic conditions continue to evolve, using a model that is validated regularly can give lenders greater confidence in the model’s performance. VantageScore Solutions, LLC validates all its models annually to promote transparency and support financial institutions with model governance. The results of the most recent validation demonstrate the consistent ability of VantageScore® 3.0 to accurately score more than 30 million to 35 million consumers considered unscoreable by other models — including 9.5 million Hispanic and African-American consumers. The findings reinforce the importance of using advanced credit scoring models to make more accurate decisions while providing consumers with access to fair and equitable credit. >> VantageScore Annual Validation Results 2016 VantageScore® is a registered trademark of VantageScore Solutions, LLC
A recent national survey by Experian revealed opportunities for businesses to build relationships with future homebuyers before they’re ready to obtain a loan. Insights include: 35% of future buyers said they don’t know what steps to take to qualify for a larger loan 75% of future buyers are not preapproved for a home loan 29% of those surveyed would purchase a more expensive home if they had better credit and could qualify for a larger loan A large portion of near-future homebuyers are millennials. Building relationships with this generation now will benefit financial institutions in the future. >> White paper: Building lasting relationships with millennials
All customers are not created equally – at least when it comes to one’s ability to pay. Incomes differ, financial circumstances vary and economic challenges surface. Lost job. Totaled car. Unplanned medical bills. Life happens. Research conducted by a recent Bankrate study revealed just 38 percent of Americans said they could cover an unexpected emergency room visit or a $500 car repair with available cash in a checking or savings account. It’s a scary situation for individuals, and also a source of stress for the lender expecting payment. So what are the natural moments for a lender to assess “ability to pay?” Moment No. 1: When prepping for a prescreen campaign and at origination. Many lenders leverage an income estimation model, designed to give an indication of the customer’s capacity to take on additional debt by providing an estimation of their annual income. Within the model, multiple attributes are used to calculate the income, including: Number of accounts Account balances Utilization Average number of months since trade opened Combined, all of these insights determine a customer’s current obligations, as well as an estimation of their current income, to see if they can realistically take on more credit. The right models and criteria on the front-end – whether used when a consumer applies for new credit or when a lender is executing a prescreen campaign to acquire new customers – minimizes the risk for default. It’s a no-brainer. Moment No. 2: When a customer is already on your books. As the Bankrate study mentioned, sudden life events can send some customers’ lives into a financial tailspin. On the other hand, financial circumstances can change for the better too. Aggressively paying down a HELOC, doubling down on a mortgage, or wiping out a bankcard balance could signal an opportunity to extend more credit, while the reverse could be the first signs of payment stress. Attaching triggers to accounts can give lenders indications on what to do with either scenario, helping to grow a portfolio and protect it. Moment No. 3: When an account goes south. While a lender hates to think any of its accounts will plummet into collections, sometimes, it’s inevitable. Even prime customers fall behind, and suddenly financial institutions are faced with looking at collections strategies. Where should they place their bets? You can’t treat all delinquent customer equally and work the accounts the same way. Collection resources can be wasted on customers who are difficult or impossible to recover, so it’s best to turn to predictive analytics and a collections scoring strategy to prioritize efforts. Again, who has the greatest ability to pay? Then place your manpower on those individuals where you can recover the most dollars. --- Assessing one’s ability to pay is a cornerstone to the financial services business. The quest is to find the sweet spot with a combination of application data, behavioral data and credit risk scoring analytics.
His car, more than 10 years old and not worth salvaging, was in the shop again. Time to invest in something new – or at least “new-ish.” He headed to a local dealership, selected a practical model and applied for financing. “We can’t give you a loan,” said the manager. “Your income is not high enough, but perhaps if you bring in a co-signer ...” Denied. Her college degree hung on the wall of her childhood bedroom. In the months since she celebrated graduation with family and friends, she landed a job, but not one providing enough income to cover rent, a car payment and her hefty student loan payments. “I didn’t realize my payments would be so high,” said the woman. “I don’t know how I’ll ever climb out from under this debt and start my life.” Stalled. His attempt at applying for a bankcard, much needed to begin the journey of establishing credit in the country, was met with failure. “We can’t find any credit history on you,” says the lender. “Try again in the future.” Invisible. These stories are all too common in America. A lack of financial education, coupled with a few poor choices, can derail an individual’s financial trajectory. More light has certainly been shone on the topic of financial education and the importance of making smart credit decisions from a young age, but there is no nationwide financial education program offered in schools, and many parents feel ill-equipped to handle the task. Consider a few of these numbers: 71 percent of college grads recently surveyed by Experian said they did not learn about credit and debt management in college, giving their schools an average grade of “C” when it comes to preparing them to manage credit and debt after college The latest \"State of Credit\" revealed the average debt per consumer is $29,093 39 percent of newlyweds say credit scores is a source of stress in their marriage Money management is tough, and we expect people to just figure it out. But clearly, that’s not working. So we need to think about the world of credit differently. As Experian says, we need to treat it as a skill. We need to practice and learn and adjust. As you get better at credit, it opens doors, creates opportunities, and enables people to live the lives they wish to live. Suddenly, you can get the car loan, move out, have access to credit cards, and manage it all responsibly. In other words, you claim financial health. On the other hand, if you don’t work at this skill, a lack of financial health ensues. Unruly amounts of debt, irregular income and sporadic savings create stress, resentment and pain. Increasingly, more financial institutions are boosting efforts to educate about credit. Schools are exploring curriculum to talk finances and inject real-life money management scenarios into everyday lessons. Millennials are seeking transparency around credit transactions. The more financially healthy consumers we have in this country, building credit skills, means overall economies will grow. So yes, financial health matters. It matters to individuals, to lending institutions, to retailers and to communities big and small. Building those credit skills is essential. Your health depends on it.
Trend: a general direction in which something is developing or changing. Last Update: January 2019 As a lender, it’s important to understand a consumer’s credit behavior and whether it is improving or deteriorating over time. Sure, you can pull a credit score at any moment, but it is merely a snapshot. Knowing a consumer’s credit information at a single point in time only tells part of the story. Two consumers can have the same credit score, but one consumer’s score could be moving up while another’s could be moving down. In order to understand the whole story, lenders need the ability to leverage trended data to assess a consumer’s credit behavior over time. Experian’s Trended Data is comprised of five fields of historical payment information over a 24-month period. It includes: Balance Amount Original Loan / Limit Amount Scheduled Payment Amount Actual Payment Amount Last Payment Date By analyzing historical payment information, lenders can determine if a consumer is consistently paying more than the minimum payment, has a demonstrated ability to pay and shows no signs of payment stress. It can conversely identify if a consumer is making only minimum payments and has increasing payment stress. Knowing how a consumer uses credit, or pays back debt over time, can help lenders offer the right products and terms to increase response rates, determine up-sell and cross-sell opportunities, prevent attrition, identify profitable customers, avoid consumers with payment stress and limit loss exposure. Using a consumer’s historical payment information provides a more accurate assessment of future behavior, which in turn helps effectively manage changes in risk, predicts in-the-market timing or balance transfer activity, and provides additional insight for other lending strategies. There is a catch though. In order for lenders to extract the benefits of trended data, they need to be able to analyze an enormous amount of data. Five fields of data across 24 months on every trade is huge and can be difficult for lenders with limited analytical resources to manage. For example, a single consumer with 10 trades on file would have upwards of 1,200 data points to analyze. Multiply that by a file of 100,000 consumers and you are now dealing with over 120,000,000 data points. Additionally, if lenders utilize the trended data in their underwriting processing and intend to use it to decline consumers, they will need to create their own adverse action reason codes to communicate to the consumer. Not all lenders are equipped to take on this level of effort. Still, there are solutions to assist lenders with managing and unlocking the power of trended data. Experian’s pre-calculated solutions utilizing trended data allow even the smallest lenders to leverage the most cutting-edge solutions in near plug-and-play environments to quickly and effectively action on the benefits of trended data, minus the hassles of analyzing it. Trended data, and the solutions built from it, allow lenders to effectively predict where a consumer is going based on where they’ve been. And really, that can make all the difference when it comes to smart lending decisions. Get Started Today
According to a national survey by Experian, college students may be receiving their degrees, but their financial management knowledge still needs some schooling. The survey reveals some troubling data about recent graduates: Average student loan debt is $22,813 31% have maxed out a credit card 39% have accepted credit card terms and conditions without reading them Learning to manage debt and finances properly is key to young adults’ future financial success. Since students aren’t receiving credit and debt management education in college, they need to educate themselves proactively. Credit education resources are available on Experian\'s Website. >> Experian College Graduate Survey Report
Experian cited in Mobile Fraud Management Solutions report from Forrester as having the most capabilities and one of the highest estimated revenues in total fraud management
Experian consultant offers his recap from attending a half-day event hosted at The White House called the “FinTech Summit” largely focused on how government agencies can tap into the innovation, in which new firms are offering small-business owners and consumers faster forms of loans and digital payments. Federal regulators have been studying the industry to determine how it can be regulated while still encouraging innovation.
Part four in our series on Insights from Vision 2016 fraud and identity track It was a true honor to present alongside Experian fraud consultant Chris Danese and Barbara Simcox of Turnkey Risk Solutions in the synthetic and first-party fraud session at Vision 2016. Chris and Barbara, two individuals who have been fighting fraud for more than 25 years, kicked off the session with their definition of first-party versus third-party fraud trends and shared an actual case study of a first-party fraud scheme. The combination of the qualitative case study overlaid with quantitative data mining and link analysis debunked many myths surrounding the identification of first-party fraud and emphasized best practices for confidently differentiating first-party, first-pay-default and synthetic fraud schemes. Following these two passionate fraud fighters was a bit intimidating, but I was excited to discuss the different attributes included in first-party fraud models and how they can be impacted by the types of data going into the specific model. There were two big “takeaways” from this session for me and many others in the room. First, it is essential to use the correct analytical tools to find and manage true first-party fraud risk successfully. Using a credit score to identify true fraud risk categorically underperforms. BustOut ScoreSM or other fraud risk scores have a much higher ability to assess true fraud risk. Second is the need to for a uniform first-party fraud bust-out definition so information can be better shared. By the end of the session, I was struck by how much diversity there is among institutions and their approach to combating fraud. From capturing losses to working cases, the approaches were as unique as the individuals in attendance This session was both educational and inspirational. I am optimistic about the future and look forward to seeing how our clients continue to fight first-party fraud.
On June 2, the Consumer Financial Protection Bureau (CFPB) proposed a rule aimed at “payday lending” that will apply to virtually all lenders, with request for comments by Sept. 14. Here is a summary of the basic provisions of the proposed rule. However, with comments, the proposal is more than 1,300 pages in length, and the proposed rule and examples are more than 200 pages long. It is necessary to review the details of the proposed rule to understand its potential impact on your products and processes fully. You may wish to review your current and future offerings with your institution’s counsel and compliance officer to determine the potential impact if major provisions of this proposed rule are finalized by the CFPB. Coverage The proposal generally would cover two categories of loans. First, the proposal generally would cover loans with a term of 45 days or less. Second, the proposal generally would cover loans with a term greater than 45 days, provided that they have an all-in annual percentage rate greater than 36 percent and either are repaid directly from the consumer’s account or income or are secured by the consumer’s vehicle. Ability to repay For both categories of covered loans, the proposal would identify it as an abusive and unfair practice for a lender to make a covered loan without reasonably determining that the consumer has the ability to repay the loan. Or if the lender does not determine if the consumer can make payments due, as well as meet major financial obligations and basic living expenses during and for 30 days after repayment. Lenders would be required to verify the amount of income that a consumer receives, after taxes, from employment, government benefits or other sources. In addition, lenders would be required to check a consumer’s credit report to verify the amount of outstanding loans and required payments. “Safe Harbor” The proposed rule would provide lenders with options to make covered loans without satisfying the ability-to-repay and payment notice requirements, if those loans meet certain conditions. The first option would be offering loans that generally meet the parameters of the National Credit Union Administration “payday alternative loans” program, where interest rates are capped at 28 percent and the application fee is no more than $20. The other option would be offering loans that are payable in roughly equal payments with terms not to exceed two years and with an all-in cost of 36 percent or less, not including a reasonable origination fee, so long as the lender’s projected default rate on these loans is 5 percent or less. The lender would have to refund the origination fees any year that the default rate exceeds 5 percent. Lenders would be limited as to how many of either type of loan they could make per consumer per year. Outstanding loans The proposal also would impose certain restrictions on making covered loans when a consumer has — or recently had — certain outstanding loans. These provisions are extensive and differ between short- and long-term loans. For example: Payday and single-payment auto title: If a borrower seeks to roll over a loan or returns within 30 days after paying off a previous short-term debt, the lender would be restricted from offering a similar loan. Lenders could only offer a similar short-term loan if a borrower demonstrated that their financial situation during the term of the new loan would be materially improved relative to what it was since the prior loan was made. The same test would apply if the consumer sought a third loan. Even if a borrower’s finances improved enough for a lender to justify making a second and third loan, loans would be capped at three in succession followed by a mandatory 30-day cooling-off period. High-cost installment loans: For consumers struggling to make payments under either a payday installment or auto title installment loan, lenders could not refinance the loan into a loan with similar payments. This is unless a borrower demonstrated that their financial situation during the term of the new loan would be materially improved relative to what it was during the prior 30 days. The lender could offer to refinance if that would result in substantially smaller payments or would substantially lower the total cost of the consumer’s credit. Payments Furthermore, it would be defined as an unfair and abusive practice to attempt to withdraw payment from a consumer’s account for a covered loan after two consecutive payment attempts have failed, unless the lender obtains the consumer’s new and specific authorization to make further withdrawals from the account. The proposal would require lenders to provide certain notices to the consumer before attempting to withdraw payment for a covered loan from the consumer’s account unless exempt under one of the “safe harbor” options. Registered information systems Finally, the proposed rule would require lenders to use credit reporting systems to report and obtain information about loans made under the full-payment test or the principal payoff option. These systems would be considered consumer reporting companies, subject to applicable federal laws and registered with the CFPB. Lenders would be required to report basic loan information and updates to that information. The proposed regulation may be found here.
According to the most recent State of the Automotive Finance Market report, the total balance of open automotive loans increased 11.1% in Q1 2016, reaching $1.005 trillion — up from $905 billion in Q1 2015. This is the first time on record that automotive loans have passed the $1 trillion mark. The report also revealed that subprime loan volumes experienced double-digit growth and overall delinquencies remained low. With more consumers relying on financing, lenders should monitor credit and delinquency trends in order to adjust strategies accordingly. >>Webinar: Hear about the latest consumer credit trends
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