Debt & Collections
Top states for billing and shipping e-commerce fraud With more than 13 million fraud victims in 2015, assessing where fraud occurs is an important layer of verification for e-commerce. Experian® analyzed millions of e-commerce transactions from 2015 to identify fraud attack rates across the United States. With the switch to chip-enabled credit card transactions and possible growth of card-not-present fraud, online businesses should utilize advanced fraud solutions to monitor their riskiest locations and prevent losses. >> View the Experian map to see 2015 e-commerce attack rates for all states
It’s hard to remember a world without online lenders. Today, fintech players continue to pop up, making it easier to cross-shop loans and land instant approvals. Gone are the days of lengthy applications and waiting to hear if you’ve scored the latest credit line or personal loan. Consumers, especially with top-tier credit, can easily seek lower monthly payments or consolidate another loan with a cash-out option. Whatever the need, there’s a lender ready to serve. Strike that. There’s actually two or three lenders waiting to serve you. In fact, a recent Experian data pull revealed an increasing share of personal loan balances is actually going to lenders outside of the traditional banks and credit union space (they still own the lion’s share of the business). In 2013 (Q4), these more non-traditional lenders had 15.36 percent of personal loan balances. In Q4 of 2015, that number increased to 27.26 percent. The personal loan business today is just over $222.9 billion in outstanding balances. As the competition heats up, lenders will need to diversify, stand out and provide more value to consumers. Those that engage with new, value-added services, and deliver timely, personalized needs-based messages will capture the greatest share of the market. Here is a sampling of ways to draw consumers in and deliver the value they seek in a financial institution: Be Transparent Lending Club, one of the original peer-to-peer lenders and currently the biggest in terms of dollars funded, continues to grow by providing consumers and investors with transparency, good loan terms and speed. Prosper, on the other hand, recently acquired an app that allows their customers to track spending, budget and monitor their credit. They plan to leverage this technology in the near future and offer it to customers and investors for free. Research reveals Millennials especially are looking to tech and free services to manage their personal finances. A recent Experian survey focused on Millennials and credit revealed 48 percent have used free financial services, like Mint, to manage their finances. Additionally, 57 percent use on average three financial apps. Know Your Customers Payoff uses survey data to segment their customers into roughly 10 financial personalities based on how they use and think about their debt. These personality types are used to tailor marketing messages and customer service conversations about how to improve their financial situation. Their site features a quiz, Discover the Secrets of Your Financial Personality, helping consumers and Payoff understand more about trends attached to spending, saving and managing money. Offer Solutions for Debt Consolidation Even after consumers consolidate debt and pay it off successfully, unforeseen expenses, unexpected life events, evolving spending habits and the increasing cost-of-living expenses mean there will always be a market for debt consolidation solutions. Understanding consolidation credit account behavior is mandatory for lenders looking to stand out and stay ahead of the consolidation needs of consumers. Having visibility to consumers’ interest rates, revolving loan balances and the remaining months on existing loans provides unique ways to segment and engage clients with need-based offers. Consumer-tailored messages during the prospecting, acquisition and account management stages of the relationship sets the stage for repeat business. The research is clear. Individuals are willing to switch brands if they feel a different provider will better meet their needs. Lenders – in both the traditional and fintech spaces – should not expect many chances when it comes to getting it right with consumers. Fail to keep them engaged and you’ll fail to keep them. Period. Learn more about identifying profitable consolidation candidates, check out Experian’s annual Vision Conference in May.
Every portfolio has a set of delinquent customers who do not make their payments on time. Truth. Every lender wants to collect on those payments. Truth. But will you really ever be able to recover all of those delinquent funds? Sadly, no. Still, financial institutions often treat all delinquent customers equally, working the account the same and assuming eventually they’ll get their funds. The sentiment to recover is good, but a lot of collection resources are wasted on customers who are difficult or impossible to recover. The good news? There is a better way. Predictive analytics can help optimize the allocation of collection resources by identifying the most effective accounts to prioritize to your best collectors, do not contact and proceed to legal actions to significantly increase the recovery of dollars, and at the same time reduce collection costs. I had the opportunity to recently present at the annual Debt Buyer Association’s International Conference and chat with my peers about this very topic. We asked the room, “How many of you are using scoring to determine how to work your collection accounts?” The response was 50/50, revealing many of these well-intentioned collectors are working themselves too hard, and likely not getting the desired returns. Before you dive into your collections work, you need to respond to two questions: Which accounts am I going to work first? How am I going to work those accounts? This is where scoring enters the scene. A scoring model is a statistical algorithm that assigns a numerical expression based on known information to predict an unknown future outcome. You can then use segmentation to group individuals with others that show the same behavior characteristics and rank order groups for collection strategies. In short, you allow the score to dictate the collection efforts and slope your expenses based on the propensity and expected amount of the consumer to pay. This will inform you on: What type, if any, skip trace tactic you should use? If you should purchase additional data? What intensity you should work the account? With scoring, you will see different performances on different debts. If you have 100 accounts you are collecting on, you’ll then want to find the accounts where you will have the greatest likelihood to collect, and collect the most dollars. I like to say, “You can’t get blood from a stone.” Well the same holds true for certain accounts in your collections pile. Try all you like, but you’ll never recoup those dollars, or the dollars you do recoup will be minimal. With a scoring strategy, you can establish your “hit list” and find the most attractive accounts to collect on, and also match your most profitable accounts with your best collectors. My message to anyone managing a collections portfolio can be summed up in three key messages. You need to use scoring in your business to optimize resources and increase profits. The better data that goes into your model will net you better performance results. Get a compliance infrastructure in place so you can ensure you are collecting the right way and stay out of trouble. The beauty of scores is they tell you what to do. It will help you best match resources to the most profitable accounts, and work smarter, not harder. That’s the power of scoring.
A recent Experian survey shows a growing concern over identity theft and tax fraud. 42% of consumers are concerned that someone could access their personal data through their tax return, compared with 35% in 2014 and 38% in 2015 28% of consumers have been a victim or know someone who has been a victim of tax fraud Tax season is a busy time of year for identity thieves. While consumers should take steps to protect themselves, businesses also need to employ ID theft protection solutions in order to safeguard consumer information. >> Identify and prevent multiple types of fraud
According to a recent Experian Marketing Services study, 36% of companies interact with customers in five or more channels.
The new year has started, the champagne bottles recycled. Bye-bye holidays, hello tax season. In fact, many individuals who are expecting tax refunds are filing early to capture those refunds as soon as possible. After all, a refund equates to so many possibilities – paying down debt, starting a much-needed home improvement project or perhaps trading up for a new vehicle. So what does that mean for lenders? As consumers pocket tax refunds, the likelihood of their ability to make payments increases. By the end of February 2014, more than 48 million tax refunds had been issued according to the IRS – an increase of 5.6 percent compared to the same time the previous year. As of Feb. 28, the average refund in 2014 was $3,034, up 3 percent compared to the average refund amount for the same time in 2013. To capitalize on this time period, introducing collection triggers can assist lenders with how to manage and collect within their portfolios. Aggressively paying down a bankcard, doubling down on a mortgage payment or wiping out a HELOC signal to the lender a change in positive behavior, but without a trigger attached, it can be hard to pinpoint which customers are shifting from their status quo payments. Experian actually offers around 100 collection triggers, but lenders do not need all to seek out the predictive insights they require. A “top 20” list has been created, featuring the highest percentages in lift rates, and population hit rates. Experian has done extensive analysis to determine the top-performing collection triggers. Among the top 15 to 20 triggers, the trigger hit rate ranged from 2 to 8 percent on an average client’s total portfolio, taking into consideration liquidation rates, average percent of payment lifts, lift in liquidation rates over the baseline liquidation, percent of overall portfolio that triggered, percent of overall portfolio that triggered only on the top-selected triggers, and percent of volume by trigger on the total customers that had a trigger hit. With that said, it is essential to implement the right strategy that includes a good mixture of the top-performing triggers. The key is diversifying and balancing trigger selection and setting triggers up during opportune times. Tax season is one of those times. Some of the top-ranked triggers include: Closed-Zero Balance Triggers: This is when a consumer’s account is reported as closed after being delinquent for a certain number of days. Specifically, the closed-zero balance trigger after being delinquent for 120 days has the highest percent of payment lift over an average payment that you would receive from a customer (at a 710 percent lift rate). These triggers are good indicators the consumer is showing positive improvement, thus having a higher likelihood for collections. Paid Triggers: This is when a consumer’s account is reported as paid after being delinquent, in collections, etc. Five of the top 20 triggers are paid triggers. These triggers have good coverage and a good balance between high lift rates (100 percent to 500 percent) and percent of the triggered population. These triggers are also good indicators the consumer is showing positive improvement, thus having a higher likelihood for collections. Inquiry Triggers: This is when a consumer is applying for an auto loan, mortgage loan, etc. The lift rates for these triggers are lowest within the Top 20, but on the other hand, these triggers have the highest hit rates (up to a 33 percent hit rate). These triggers are good indicators consumers are seeking to open additional lines of credit. Home Equity Loan Triggers: These triggers indicate the credit available on a consumer’s home equity loan. They are specifically enticing to collectors due to the fact that home equity lines of credit are usually larger than your average credit on your bank card. The larger the line of credit, the more you are able to potentially collect. To learn more about collection triggers, visit https://www.experian.com/consumer-information/debt-collection.html
A recent Experian survey found that while consumers are getting better about protecting their information on a regular basis, many do not take the same precautions when traveling. According to the survey, 1 in 5 consumers has had an item with sensitive information lost or stolen while traveling, and 39% have experienced identity theft while traveling or know someone who has. Organizations can protect themselves and customers by using innovative fraud-detection tools designed to reduce potential losses while preserving the customer experience. >> Video: The reputational impact of fraud and identity theft
With more than one-third of customers interacting with a single business in five or more channels and more than 85 percent of consumers using online or mobile to conduct business, omnichannel fraud prevention has become a necessity. Implementing a layered approach to authentication and integrating device intelligence into the process to associate a consumer with a known device are critical components of a fraud mitigation strategy. In addition to providing another layer of validation, verifying a customer through his or her device makes it easier for the customer to interact with the business and is a huge benefit to the overall customer experience. Perspective paper: Protecting the customer experience - The impact of fraud on the customer relationship
Gift cards are the most requested gift item and have been for the last eight years. Merchants love gift cards because they take up very little space and the recipient often ends up spending more than the value of the gift card.
The experience of being a victim of data breaches has created a shift in consumer behavior and attitude over the past year. A recent Ponemon Institute study found that more than one-third of consumers ignored data breach notification letters, taking no action to protect themselves against fraud. To combat data breach fatigue, companies should communicate with customers sincerely and avoid treating the notification process as a compliance issue. Notification letters should include an apology, a clear explanation of what happened and why, and steps consumers can take to protect themselves from fraud. 2015 Data Breach Industry Forecast
While marketers typically spend vast amounts of money to increase customer acquisitions, fraud prevention can undercut those efforts. According to a recent 41st Parameter® study, average card-not-present declines represent 15 percent of all transactions; however, one to three percent of those declined transactions turn out to be false positives, equating to 1.2 billion dollars in lost revenue annually. Marketers can avoid unnecessary declines and create a seamless customer experience by communicating campaign plans to the fraud-risk team early on and coordinating marketing and fraud-prevention efforts. Download Experian’s latest fraud prevention report. Report: Holiday Marketing & Fraud
This is the third post in a three-part series. Experian® is not a doctor. We don’t even play one on TV. However, because of our unique business model and experience with a large number of data providers, we do know data governance. It is a part of our corporate DNA. Our experiences across our many client relationships give us unique insight into client needs and appropriate best practices. Note the qualifier — appropriate. Just as every patient is different in his or her genetic predispositions and lifestyle influences, every institution is somewhat unique and does not have a similar business model or history. Nor does every institution have the same issues with data governance. Some institutions have stabile growth in a defined footprint and a history of conservative audit procedures. Others have grown quickly through aggressive acquisition marketing plans and unique channels and via institution acquisition/merger, leading to multiple receivable systems and data acquisition and retention platforms. Experian has provided valuable services to both environments many times throughout the years. As the regulatory landscape has evolved, lenders/service providers demand a higher level of hands-on experience and regulatory-facing credibility. Most recently, lenders have required assistance on the issues driven by mandates coming from the Comprehensive Capital Analysis and Review (CCAR), Office of the Comptroller of the Currency (OCC) and the Consumer Financial Protection Bureau (CFPB) bulletins and guidelines. Lenders are best served to begin their internal review of their data governance controls with a detailed individual attribute audit and documentation of findings. We have seen these reviews covering fewer than 200 attributes to as many as more than 1,000 attributes. Again, the lender/provider size, analytic sophistication and legacy growth and IT issues will influence this scope. The source and definition of the attribute and any calculation routines should be fully documented. The life cycle stage of attribute acquisition and usage also is identified, and the fair lending implication regarding the use of the attribute across the life cycle needs to be considered and documented. As part of this comprehensive documentation, variances in intended definition and subsequent design and deployment are to be identified and corrective action guidance must be considered and documented for follow-up. Simultaneously, an assessment of the current risk governance policies, processes and documentation typically is undertaken. A third party frequently is leveraged in this review to ensure an objective perspective is maintained. This initiative usually is a series of exploratory reviews and a process and procedures assessment with the appropriate management team, risk teams, attribute design and development personnel, and finally business and end-user teams, as necessary. From these interviews and the review of available attribute-level documentation, documents depicting findings and best practices gap analysis are produced to clarify the findings and provide a hierarchy of need to guide the organization’s next steps: A more recent evolution in this data integrity ecosystem is the implication of leveraging a third party to house and manipulate data within client specifications. When data is collected or processed in “the cloud,” consistent data definitions are needed to maintain data integrity and to limit operational costs related to data cleansing and cloud resource consumption. Maintaining the quality of customer personal data is a critical compliance and privacy principle. Another challenge is that of maintaining cloud-stored data in synchronization with on-premises copies of the same data. Delegation to a third party does not discharge the organization from managing risk and compliance or from having to prove compliance to the appropriate authorities. In summary, a lender/service provider must ensure it has developed a rigorous data governance ecosystem for all internal and external processes supporting data acquisition, retention, manipulation and utilization: A secure infrastructure includes both physical and system-level access and control. Systemic audit and reporting are a must for basic compliance standards. If data becomes corrupted, alternative storage, backup or other mechanisms should be available to protect the information. Comprehensive documentation must be developed to reveal the event, the causes and the corrective actions. Data persistence may have multiple meanings. It is imperative that the institution documents the data definition. Changes to the data must be documented and frequently will lead to the creation of a new data attribute meeting the newer definition to ensure that usage in models and analytics is communicated clearly. Issues of data persistence also include making backups and maintaining multiple archive copies. Periodic audits must validate that data and usage conform to relevant laws, regulations, standards and industry best practices. Full audit details, files used and reports generated must be maintained for inspection. Periodic reporting of audit results up to the board level is recommended. Documentation of action plans and follow-up results is necessary to disclose implementation of adequate controls. In the event of lost or stolen data, appropriate response plans and escalation paths should be in place for critical incidents. Throughout this blog series, we have discussed the issues of risk and benefits from an institution’s data governance ecosystem. The external demands show no sign of abating. The regulators are not looking for areas to reduce their oversight. The institutional benefits of an effective data governance program are significant. Discover how a proven partner with rich experience in data governance, such as Experian, can provide the support your company needs to ensure a rigorous data governance ecosystem. Do more than comply. Succeed with an effective data governance program.
According to a recent 41st Parameter® study, 85 percent of consumers use online or mobile channels to conduct business.
This is the first of a two part blog about the state of auto lending in the U.S. In 2014, auto lending has received increased media attention. Unlike other forms of consumer lending, auto lending has been booming. This lending has powered spending and has been an important driver of the economic recovery. However, as auto lending has increased, subprime lending has advanced as well. Many analysts now are predicting as a result of the increased volumes, auto delinquencies will eventually rise. Some have even drawn a corollary to the increase in subprime mortgage lending and its resulting impact on the Great Recession. Regulators and rating agencies have weighed in on the subject too. The principal banking regulator, Office of the Comptroller of the Currency (OCC) noted recently, “The OCC sees signs that credit risk is now building after a period of improving credit quality and problem loan clean-up.” In particular, the OCC pointed out how its examiners have observed a “loosening of standards and increased layering of risk in the indirect auto market.” (Semiannual Risk Perspective, Spring 2014) The OCC’s primary points regarding auto lending risk are: Longer loan terms, Increasing advance rates with resulting higher LTVs, Originating loans to borrowers with lower credit scores, A larger average loss per vehicle. Nevertheless, the OCC notes, “The results have yet to show large-scale deterioration at the portfolio level, but signs of increasing risk are evident.” Standard and Poor issued a report regarding Finance companies (and bonds created by securitized auto lending) called Subprime Auto Loan Performance: The Best is Behind Us. In that, S&P states that, “In our opinion, we’re at a turning point with respect to subprime auto loan performance, similar to where we were in 2006.” In order to examine auto lease and loan trends, Experian IntelliView data was reviewed which provides a quarterly update of U.S. lending trends based on credit bureau data including originations, outstanding loans and lines, credit performance trends, segmented by product and other characteristics. Auto Loans and Lease Originations Auto lending originations versus other consumer credit products were studied to highlight trends, before and after the recession, by looking at metrics beginning with the first quarter of 2006. The Experian IntelliView data on slide 2 shows quarterly acquisition volumes for auto, bankcards, mortgages, home equity loans, HELOCs and personal loans using an index based on originations during this time. (Student loans were not examined because much of this lending is made by government backed organizations.) Auto lending volume reached its low point much earlier than the other products (at the end of 2008-Q4) and returned to pre-recession levels by the second quarter of 2011. In the 2nd quarter of 2014, auto originations continued to grow, and are now more than 60% over 2006 levels. Home lending volume has dipped. First mortgages have a volatile origination pattern based on periods of refinance activity, but volume in the most recent quarters has been down at least 40% off the 2006 volumes. Meanwhile, second mortgage (home equity loans and HELOCs) have practically collapsed since 2009, although HELOCs have shown some rebound in the last year. Of the other credit product originations, only bankcards have reached its pre-recession quantity. Auto lending naysayers are neglecting key facts from Experian Decision Analytics The end of 2008 was a critical juncture because auto originations were at their lowest level as seen in slide 3 showing the growth in auto loan and lease acquisition volumes by type of financial institution. All loans and lease volumes have now increased by 140%. Additionally, the end of 2008 saw GMAC- a large Captive Auto finance company form Ally Bank. The data shows that only at Q1 2009 can this shift be reflected confidently. Furthermore, examinations of developments from this time period ensure a consistent position when considering type of financial institution. Finance companies actually have seen the largest increase in volume at 289% since this time, while Banks (135%), Credit Unions (121%) and Captive Auto finance (99%) volumes have also at least doubled. Near-prime and subprime lending have witnessed substantial origination growth since 2006 as reflected in slide 5 shows the volume trends by credit grade. However, prime and super-prime lending has grown faster. Deep-subprime lending is still at about the same level as 2006. Therefore, originations today have a lower proportion of non-Prime commitments than the period prior to the recession. Examining volumes since the trough of the recession presents a different (but logical) perspective. For example, subprime lending volumes have increased almost 193% since the end of 2008, and near-prime volumes have grown 175%, a rate higher than the total overall growth (140%). In the recession, auto lending volume slowed, specifically for non-prime credit grades. Lenders restricted access to riskier customers (but not super-prime, which actually held steady). It is logical that the volume of riskier credit grades would grow faster as the economy recovers, and lending returns to normal conditions. The proportion of volume by lending type for each financial institution in the second quarter of 2014 is represented in slide 6 and finance companies are now writing about 58% of the deep- subprime paper and 37% of near-prime (up from 33% and 23% respectively in 2006-2008). However, at the other end of the credit spectrum, advances were also made. Finance companies now account for 9.5% of super-prime and 8.6% of prime volume whereas they typically accounted for about 3% of either grade prior to the recession. From 2006 to today, average size of an auto loan or lease is up 8.7%, less than half of the compound rate of inflation. The Captive Auto finance companies had long held the highest average loan amount as seen on slide 7, but Bank averages have grown recently to match them at approximately $21,674 per origination. Finance company origination size is the lowest of all financial institution types ($17,820). Meanwhile, the average size has progressed 18% since 2006. Since 2006, average loan/line commitments for all types of lending except deep-subprime have grown between 6% and 9%. Deep-subprime paper saw a large decline in average size during the recession and is still about 3% below the 2006 level. Average terms for new loans and leases also have recently returned to pre-recession levels. Banks have the highest current average term at 62 months. Finance companies and Captive Auto finance companies have the lowest average term (56 and 55 months respectively). The interest rate trends by type of lending as seen on slide 8 show that rates on super-prime (now 2.89%), prime (now 3.91%) and near-prime (6.92%) have declined significantly since 2009. Subprime (now 12.88%) and particularly deep-subprime (16.74%) have declined less. Consequently, spreads between super-prime and deep-subprime are currently 13.85%. This is because of a long-term widening of spreads between near-prime and subprime paper, and especially subprime and deep-subprime. Banks generally have higher interest rates, even across similar credit grades. Still, the differences in rates in these categories between Banks and Captive Auto have declined significantly. Where this spread may have been 150 bp or higher in rates five years ago, Bank APRs are currently 35 bp for super-prime and 62 bp for prime over rates for Captive Auto finance companies. Finance companies show much higher rates (at least 600 bp over) than other financial institutions for subprime and deep-subprime paper. On slide 9 we examine the acquisition volumes by state and you can see that in 2011, Texas bypassed California in quarterly auto volume and is now the leading state in the nation. Together, Texas and California account for 23% of national volume. Florida and New York make up almost 12%. Ten other states account for between 2% (Maryland) and 3.8% (Pennsylvania). The remaining states (and D.C.) account for 36% of volume. Volume has grown fastest in North Dakota (up 319% since 2008) and slowest in Connecticut and New Jersey (110% and 100% respectively). In the second part of this blog, we will look at trends in auto lending outstandings and performance. Learn more about what Experian Intelliview can do for you.
As data breaches continue to attract publicity, consumers are expecting more from impacted organizations.
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