As we approach the one-year anniversary of the EMV liability shift, we have seen an increase in e-commerce fraud — to the tune of 15% higher than last year. Additional insights from Experian’s biannual analysis on e-commerce fraud include: 44% of e-commerce billing fraud came from Florida, California and New York* 52% of e-commerce shipping fraud came from Florida, New York and California* Miami, Fla., is the most dangerous city in the United States for e-commerce merchants* As fraudsters continue to perpetrate card-not-present fraud, ensure you are prepared. You’ll be thankful if fraudsters come calling. >> E-commerce Attack Rates
In this new Telephone Consumer Protection Act (TCPA) era, calling your customers isn’t a thing of the past. It’s still okay to reach out to your clients by phone, whether to offer a new product or collect on an overdue bill. But strict compliance with TCPA rules is critical for any business that contacts customers by phone. Some of the very best ways you can protect yourself from TCPA exposure is to follow four steps when creating your dialing strategy: Customer consent: It’s important to maintain and update your customers’ contact preferences and consent to call them. Simply having a phone number on an application isn’t sufficient. Companies are required to have written permission, such as “I consent to calling my cell phone when there’s a problem …” Remember, permission may only be granted by the party who subscribes to the cellular service or who regularly uses that cell phone number. Landline or wireless?: Your database should also include the phone type for the telephone numbers you have for your customers. The dialing rules differ depending on the phone type, so it’s critical to know the type of phone you are calling or texting. Verify ownership: Ownership of cell phones should especially be validated to ensure the number hasn’t been reassigned and that the person who gave consent still owns the phone. One call can be made to a reassigned number with no liability, assuming you have no knowledge the number has changed. Repeating the action could lead to fines from $500 to $1,500 per infraction. Scrub Your Database: Have practices in place to remove any confirmed reassigned phone numbers from your database. This will help to improve your right-party contact rate and save you from potential TCPA headaches. No one disagrees that calling cell numbers is a risky business, but it can be done if you set the proper workflow in motion. Click here to learn more about Experian solutions that will help to reduce your TCPA compliance risk.
Leasing continued its strong growth as the share of new vehicles leased jumped from 26.9% in Q2 2015 to a record high of 31.4% in Q2 2016. As vehicle prices continue to rise, used vehicle loans also set new records. The average used vehicle loan reached an all-time high of $19,101 in Q2 2016, up from $18,671 in Q2 2015. Used vehicle loans accounted for 55.6% of all vehicle loans in Q2 2016. Want to capitalize on this growth? Analytics can help you target borrowers who are creditworthy and in the market for an auto loan or lease. >>Video: Auto Acquisition Strategies
With the Oct. 3, 2016 compliance date upon us, many lenders continue to debate how they would like to solve for the Military Lending Act (MLA). With new enhancements, more protections have been granted to members of the military and their dependents when it comes to “consumer credit” products, specifically around the 36% cap on the MAPR. The key then becomes how to identify these individuals. At origination, how can the lender know if an individual is a member of the military, or a service member’s dependent? The answer, of course, lies in verification. Under the new Department of Defense (DOD) rule, lenders will have to check each credit applicant to confirm that they are not a service member, spouse, or the dependent of a service member. The final rule includes a “safe harbor” from liability for lenders who verify the MLA status of a consumer through a nationwide Credit Reporting Agency (CRA) or the DOD’s own database, known as the DMDC. Obviously, lenders will want to have this “safe harbor,” so the question becomes do you opt for the direct or indirect solution? The direct solution is to have the lender access the DMDC on their own. With this option, expected turnaround time is 24 hours for batch searches. The DMDC expects the volume of searches to their servers to increase from 220 million a week to 1.9 billion a week. For some, this feels like a more manual process, but it can be done. The indirect solution involves the CRA accessing the DMDC data on the lender’s behalf. In Experian’s case, this would translate into lenders seeing the MLA indicator on the credit report at point of origination or making a call out for just the MLA indicator. The process is integrated into the credit-pull cycle, so no manual effort is required on the lender’s end. MLA status is simply flagged. The rule also permits the consumer report to be obtained from a reseller that obtains such a report from a nationwide consumer reporting agency. Required data to perform a search includes full legal name, address, social security number and date of birth. This applies to both the credit report add-on and Experian’s standalone solutions. If any of this data is missing from the inquiry, Experian is unable to perform the MLA search. Credit card lenders have until Oct. 3, 2017 to adhere to the new standards, but all other applicable lenders must act now and build out their compliance standards and solutions. Direct or indirect? That is the question. To learn more about MLA or how Experian can help, visit our dedicated-MLA site.
Experian analyzed millions of e-commerce transactions from the first six months of 2016 to identify the latest fraud attack rates across the United States for both shipping and billing locations. As we approach the one-year anniversary of the EMV liability shift, the 2016 e-commerce fraud attack rates look to be at least 15 percent higher than last year’s total. Experian analyzed millions of e-commerce transactions from the first six months of 2016 to identify the latest fraud attack rates across the United States for both shipping and billing locations. Billing fraud rates are associated with the address of the purchaser. Shipping fraud rates are associated with the address where purchased goods are sent. As we approach the one-year anniversary of the EMV liability shift, the 2016 e-commerce fraud attack rates look to be at least 15 percent higher than last year’s total. E-commerce fraud is often an indicator that other fraud activities have already happened, whether a credit card has been stolen, identity fraud has occurred, or personal credentials have been compromised.
In this age of content and increasing financial education available to all, most entities are familiar with credit bureaus, including Experian. They are known for housing enormous amounts of data, delivering credit scores and helping businesses decision on credit. On the consumer side, there are certainly myths about credit scores and the credit report. But myths exist among businesses as well, especially as it pertains to the topic of reporting credit data. How does it work? Who’s responsible? Does reporting matter if you’re a small lender? Let’s tackle three of the most common myths surrounding credit reporting and shine a light on how it really is essential in creating a healthy credit ecosystem. Myth No. 1: Reporting to one bureau is good enough. Well, reporting to one bureau is definitely better than reporting to none, but without reporting to all three bureaus, there could be gaps in a consumer’s profile. Why? When a lender pulls a consumer’s profile to evaluate it for extending additional credit, they ideally would like to see a borrower’s complete credit history. So, if one of their existing trades is not being reported to one bureau, and the lender makes a credit pull from a different bureau to use for evaluation purposes, no knowledge of that trade exists. In cases like these, credit grantors may offer credit to your customer, not knowing the customer already has an obligation to you. This may result in your customer getting over-extended and negatively impacting their ability to pay you. On the other side, in the cases of a thin-file consumer, not having that comprehensive snapshot of all trades could mean they continue to look “thin” to other lenders. The best thing you can do for a consumer is report to all three bureaus, making their profile as robust as it can be, so lenders have the insights they need to make informed credit offers and decisions. Some believe the bureaus are regional, meaning each covers a certain part of the country, but this is false. Each of the bureaus are national and lenders can report to any and all. Myth No. 2: Reporting credit data is hard. Yes, accurate and timely data reporting requires a few steps, but after you get familiar with Metro 2, the industry standard format for consumer data reporting, choose a strategy, and register for e-Oscar, the process is set. The key is to do some testing, and also ensure the data you pass is accurate. Myth No. 3: Reporting credit data is a responsibility for the big institutions –not smaller lenders and companies. For all lenders, credit bureau data is vitally important in making informed risk determinations for consumer and small business loans. Large financial institutions have been contributing to the ecosystem forever. Many smaller regional banks and credit unions have reported consistently as well. But just think how much stronger the consumer credit profile would be if all lenders, utility companies and telecom businesses reported? Then you would get a true, complete view into the credit universe, and consumers benefit by having the most comprehensive profile --- Bottom line is that when comprehensive data on consumer credit histories is readily available, it’s a good thing for consumers and lenders. And the truth is all businesses - big and small - can make this a reality.
Historically, the introduction of EMV chip technology has resulted in a significant drop in card-present fraud, but a spike in card-not-present (CNP) fraud. CNP fraud accounts for 60% to 70% of all card fraud in many countries and is increasing. Merchants and card issuers in the United States likely will see a rise in CNP fraud as EMV migration occurs — although it may be more gradual as issuers and merchants upgrade to chip-based cards. As fraud continues to evolve, so too should your fraud-prevention strategies. Make a commitment to stay abreast of the latest fraud trends and implement sophisticated, cross-channel fraud-prevention strategies. >>Protecting Growth Ambitions Against Rising Fraud Threats
Prescriptive solutions: Get the Rx for your right course of action By now, everyone is familiar with the phrase “big data” and what it means. As more and more data is generated, businesses need solutions to help analyze data, determine what it means and then assist in decisioning. In the past, solutions were limited to simply describing data by creating attributes for use in decisioning. Building on that, predictive analytics experts developed models to predict behavior, whether that was a risk model for repayment, a propensity model for opening a new account or a model for other purposes. The next evolution is prescriptive solutions, which go beyond describing or predicting behaviors. Prescriptive solutions can synthesize big data, analytics, business rules and strategies into an environment that provides businesses with an optimized workflow of suggested options to reach a final decision. Be prepared — developing prescriptive solutions is not simple. In order to fully harness the value of a prescriptive solution, you must include a series of minimum capabilities: Flexibility — The solution must provide users the ability to make quick changes to strategies to adjust to market forces, allowing an organization to pivot at will to grow the business. A system that lacks agility (for instance, one that relies heavily on IT resources) will not be able to realize the full value, as its recommendations will fall behind current market needs. Expertise — Deep knowledge and a detailed understanding of complex business objectives are necessary to link overall business goals to tactical strategies and decisions made about customers. Analytics — Both descriptive and predictive analytics will play a role here. For instance, the use of a layered score approach in decisioning — what we call dimensional decisioning — can provide significant insight into a target market or customer segment. Data — It is assumed that most businesses have more data than they know what to do with. While largely true, many organizations do not have the ability to access and manage that data for use in decision-making. Data quality is only important if you can actually make full use of it. Let’s elaborate on this last point. Although not intuitive, the data you use in the decision-making process should be the limiting factor for your decisions. By that, I mean that if you get the systems, analytics and strategy components of the equation right, your limitation in making decisions should be data-driven, and not a result of another part of the decision process. If your prescriptive environment is limited by gaps in flexibility, expertise or analytic capabilities, you are not going to be able to extract maximum value from your data. With greater ability to leverage your data — what I call “prescriptive capacity” — you will have the ability to take full advantage of the data you do have. Taking big data from its source through to the execution of a decision is where prescriptive solutions are most valuable. Ultimately, for a business to lead the market and gain a competitive advantage over its competitors — those that have not been able to translate data into meaningful decisions for their business — it takes a combination of the right capabilities and a deep understanding of how to optimize the ecosystem of big data, analytics, business rules and strategies to achieve success.
Experian conducted a joint-survey that uncovered insights into the topic of conversational commerce and voice assistants. The survey audience constituted nearly 1300 smartphone users of smart voice assistant tools. The survey asked about most requested tasks and general consumer satisfaction with the voice-recognition capabilities of Amazon's Alexa relative to other smart voice assistants such as Siri and Google.
Unfortunately, identity theft can happen to anyone and has far-reaching consequences for its victims. According to the US Department of Justice (DOJ)’s most recent study, 17.6 million people in the US experience some form of identity theft each year. This includes activities such as fraudulent credit card transactions or personal information being used to open unauthorized accounts. The most obvious consequence that identity theft victims encounter is financial loss, which comes in two forms: direct and indirect. Direct financial loss refers to the amount of money stolen or misused by the identity theft offender. Indirect financial loss includes any outside costs associated with identity theft, like legal fees or overdraft charges. The DOJ’s study found that victims experienced a combined average loss of $1,343. In total, identity theft victims lost a whopping $15.4 billion in 2014. Beyond money lost, identity theft can negatively impact credit scores. While credit card companies detect a majority of credit card fraud cases, the rest can go undetected for extended periods of time. A criminal’s delinquent payments, cash loans, or even foreclosures slowly manifest into weakened credit scores. Victims often only discover the problem when they are denied for a loan or credit card application. Last year, Experian found that these types of fraud take the longest time to resolve. Identity theft doesn’t just impact victims financially; it also often takes a significant emotional toll. A survey from the Identity Theft Research Center found that 69 percent felt fear for their personal financial security, and 65 percent felt rage or anger. And, almost 40 percent reported some sleep disruption. These feelings increased over time when victims were unable to settle the issue on their own, according to the report, which can result in problem as work or school, and add stress to relationships with friends and family. Thankfully, consumers are getting smarter about the best ways to protect their information, like using monitoring services or following security best practices. How are you protecting yourself against identity theft? Learn more about our Identity Protection Services
This summer, the Consumer Financial Protection Bureau (CFPB) took a significant step toward reforming the regulatory framework for the debt collection industry. The focus is fueled in part by the large number of consumer complaints the CFPB receives about the debt collection market — roughly 35% of total complaints. Here are highlights from the recent CFPB proposal: Data quality: Collectors would be required to substantiate claims that a consumer owes a debt in order to begin collection Communication frequency: Collectors would be limited to six emails, phone calls or mailings per week, including unanswered calls and voice mails Waiting period: Reporting a person’s debt would be prohibited unless the collector has communicated directly with the consumer first The CFPB said its proposal will affect only third-party debt collectors; however, it may consider a separate set of proposals for first-party collectors. >> Insights into CFPB's latest debt collection proposal
The first six months of 2016 has shown that the total credit card limits among the subprime and deep subprime credit range totaled $6.4 billion, the highest amount reported for those groups in the last five years. Our Q2 2016 Experian-Oliver Wyman Market Intelligence Report webinar will analyze the trends impacting consumer credit decisions in the current economy. The data is from the latest Experian Market Intelligence Brief report.
Fraudsters are more sophisticated than ever. Just when you think you’ve filled the gaps, a new fraud threat emerges. Here are five strategic recommendations from Juniper Research for businesses that accept online payments: Invest in top-of-the-range fraud detection and prevention solutions Implement mobile security as soon as possible Develop a fraud prevention investment strategy Empower cross-industry collaboration to reduce online fraud effectively Fraud continues to evolve from individual rogues to organized global networks. Is your fraud prevention strategy keeping up? >>Juniper Research: Online payment fraud whitepaper
Tick-tock. Tick-tock. Lenders are just weeks away from the required Military Lending Act compliance date of Oct. 3, yet many are scrambling to find a solution. In fact, officials with CUNA and the American Bankers Association said they were still confused by the rules, and requested a six-month extension from the Department of Defense for compliance. Card holders have until Oct. 3, 2017 to comply, but others are trying to navigate what the rule means and how to introduce new practices to protect and serve military credit consumers. What are the top questions still circulating about this key piece of regulation? Here are a few we’ve been tracking, along with some responses to assist with this shift in compliance. 1. What types of accounts are covered under the Military Lending Act (MLA)? It initially applied to three narrowly-defined “consumer credit” products: Closed-end payday loans; Closed-end auto title loans; and Closed-end tax refund anticipation loans. The new rule, issued in 2015 by the Department of Defense, expands the definition of “consumer credit” covered by the regulation to more closely align with the definition of credit in the Truth in Lending Act and Regulation Z. This means MLA now covers a wide range of credit transactions. It does not apply to residential mortgages and credit secured by personal property, such as vehicle purchase loans. 2. Who are the covered borrowers under the MLA? The DMDC database identifies individuals who meet one of the following criteria: Is on active duty Regular or reserve member of the Army, Navy, Marine Corps, Air Force, or Coast Guard, serving on active duty under a call or order that does not specify a period of 30 days or less, or such a member serving on Active Guard and Reserve duty as that term is defined in 10 u.s.c. 101 (d)(6) The member’s spouse The member’s child defined in 38 USC 101(4), or An individual for whom the member provided more than one-half of the individual’s support for 180 days immediately preceding the extension of consumer credit covered by 32 C.F.R. Part 232 The flag returned from DMDC will not specifically identify the active duty military member, but it will flag if the applicant is a covered borrower. 3. How is MAPR calculated? What additional fees are included? The MAPR includes interest, fees, credit service charges, credit renewal charges, credit insurance premiums and other fees for credit-related products sold in connection with the loan. You should work with your legal/compliance teams for MLA restrictions and applicability. 4. What is the difference between the Servicemembers Civil Relief Act (SCRA) and the Military Lending Act (MLA)? Both regulations are designed to protect U.S. service members and their families, but each focus on different areas. SCRA has been around for decades and was designed to temporarily suspend judicial and administrative proceedings and transactions that may adversely affect service members during their actual military service. In fact, if a service member has a debt before he or she joined the active military service, they can have the interest rate reduced to 6 percent, upon request. If the loan is a mortgage, that rate can also be reduced for the duration the member is in the military, plus one year. Other loans are only reduced for the duration the member is on active duty. MLA, on the other hand, is focused solely on providing specific protections for active duty service members and their dependents in certain consumer credit transactions. It was introduced in 2007, but strengthened in 2015. Specifically, it limits APR to 36 percent on covered products, which was recently expanded to include closed-end payday loans, closed-end auto title loans and closed-end tax refund anticipation loans. Unlike SCRA, where the responsibility to activate these protections falls on the service member, MLA requires creditors to verify active duty status and dependents at origination. 5. Explain the difference between accessing MLA status directly versus indirectly. The Final Rule permits a creditor to use information obtained directly from the Department of Defense’s Database. Information can also be obtained from a nationwide consumer reporting agency to determine whether a consumer applicant is a covered borrower. When working with Experian, the one-stop solution will entail outputting the MLA indicator on the credit report at point of origination. We anticipate this solution will be available in fall 2016. --- Not much is known about what the punishments or fines will look like for infractions, but now is the time to start reviewing business governance and procedures that support compliance. To learn more about MLA and to access an on-demand webinar with industry experts, visit our site.
Consumers want to pay less. This is true in retail and in lending. No big surprise, right? So in order for lenders to capitalize and identify the right consumers for their respective portfolios, they need insights. Lenders want to better understand what rates consumers have. They want to know how much interest their customers pay. They want to know if consumers within their portfolio are at risk of leaving, and they want visibility into new prospects they can market to in an effort to grow. Luckily, lenders can look to trade level fields to be in the know. These inferred data fields, powered by Trended Data, allow lenders to offer products and terms that serve two purposes: First, their use in response models and offer alignment strategies drive better performance, ROI and life-time value. As noted earlier, consumers want to pay less, so if they are offered a better rate or money-saving offer, they’re more likely to respond. Second, they ultimately save consumers money in a way that benefits each consumer’s unique financial situation- overall savings on interest paid over the life of the loan, or consolidation of other debt often combined for a lower monthly payment. These trade level fields allow lenders to dig into various trends and insights surrounding consumers. For example, Experian data can identify big spenders and transactors (those who pay off their purchases every month). Research reveals these individuals love to be rewarded for how they use credit, demanding rewards, airline miles or other goodies for the spending they do. They also really like to be rewarded with higher credit lines, whether they use the increased line or not. Fail to serve these transactors in the right way and lenders could be faced with lackluster performance in the form poor response rates, booking rates, activation rates and early attrition. Thus, a little trade level insight can go a long way in helping lenders personalize products, offers and anticipate future financial needs. Knowing the profitability of a customer across all of their accounts is important, and accessing this intelligence in a seamless way is ideal. The data exists. For lenders, it’s just a matter of unlocking it, making those small, but meaningful changes and keeping a pulse on the portfolio. Together, these strategies can help lenders keep their best customers and acquire new ones that stick around longer.