With credit card openings and usage increasing, now is the time to make sure your financial institution is optimizing its credit card portfolio. Here are some insights on credit card trends: 51% of consumers obtained a credit card application via a digital channel. 42% of credit card applications were completed on a mobile device. The top incentives when selecting a rewards card are cash back (81%), gas rewards (74%) and retail gift cards (71%). Understanding and having a full view of your customers’ activity, behaviors and preferences can help maximize your wallet share. More credit card insight>

Millennials have been accused of “killing” a lot of things. From napkins and fabric softener to cable and golf, the generation which makes up the largest population of the United States (aka Gen Y) is cutting a lot of cords. Despite homeowning being listed as one of the notorious generational group’s casualties, it’s one area that millennials want to keep alive, according to recent statistics. In fact, a new Experian study revealed 86% of millennials believe that buying a house is a good financial investment. However, only 15% have a mortgage today. One explanation for this gap may be that they appear too risky. Younger millennials (age 22-28) have an average near prime score of 652 and older millennials (age 29-35) have a prime score of 665. Both subsets fall below the average VantageScore® credit score* of U.S. consumers – 677. Yes, with the majority of millennials having near prime or worse credit scores, we can agree that they will need need to improve their financial hygiene to improve their overall credit rankings. But their dreams of homeownership have not yet been dashed. Seemingly high aspirations (of homeownership), disrupted by a reality of limited assets, low scores, and thin credit files, create a disconnect that suggests a lack of resources to get into their first homes – rather than a lack of interest. Or, maybe not. Maybe, after surviving a few first-time credit benders that followed soon after opening the floodgates to credit, millennials feel like the combination of low scores and the inability to get any credit is only salt in their wounds from their lending growing pains. Or maybe it’s all the student loans. Or maybe it’s the fact that so many of them are underemployed. But maybe there’s still more to the story. This emerging generation is known for having high expectations for change and better frictionless experiences in all areas of their life. It turns out, their borrowing behavior is no different. Recent research by Experian reveals consumers who use alternative financial services (AFS) are 11 years younger on average than those that do not. What’s the attraction? Financial technology companies have contributed to the explosive growth of AFS lenders and millennials are attracted to those online interactions. The problem is many of these trades are alternative finance products and are not reported to traditional credit bureaus. This means they do nothing to build credit experience in the eyes of traditional lenders and millennials with good credit history find it difficult to get access to credit well into their 20s. Alternative credit data provides a deeper dive into consumers, revealing their transactions and ability to pay as evidenced by alternative finance data, rental, utility and telecom payments. Alt data may make some millennials more favorable to lenders by revealing that their three-digit credit score (or lack there of) may not be indicative of their financial stability. By incorporating alternative financial services data (think convenient, tech-forward lenders that check all the boxes for bank removed millennials, not just payday loan recipients), credit-challenged millennials have a chance at earning recognition for their experience with alternative financial services that may help them get their first mortgage. Society may have preconceived notions about millennials, but lenders may want to consider giving them a second look when it comes to determining creditworthiness. In a national Experian survey, 53% of consumers said they believe some of these alternative sources would have a positive effect on their credit score. We all grow up sometime and as our needs change, there may come a day when millennials need more traditional financial services. Lenders who take a traditional view of risk may miss out on opportunities that alternative credit data brings to light. As lending continues to evolve, combining both traditional credit scores and alternative credit data appears to offer a potentially sweet (or rather, home sweet home) solution for you and your customers.   *Calculated on the VantageScore® credit score model. Your VantageScore® credit score from Experian indicates your credit risk level and is not used by all lenders, so don't be surprised if your lender uses a score that's different from your VantageScore® credit score.

First-party fraud is an identity-centric risk that changes over time. And the fact that no one knows the true size of first-party fraud is not the problem. It’s a symptom. First-party fraud involves a person making financial commitments or defaulting on existing commitments using their own identity, a manipulated version of their own identity or a synthetic identity they control. With the identity owner involved, a critical piece of the puzzle is lost. Because fraud “treatments” tend to be all-or-nothing and rely on a victim, the consequences of applying traditional fraud strategies when first-party fraud is suspected can be too harsh and significantly damage the customer relationship. Without feedback from a victim, first-party fraud hides in plain sight — in credit losses. As a collective, we’ve created lots of subsets of losses that nibble around the edges of first-party fraud, and we focus on reducing those. But I can’t help thinking if we were really trying to solve first-party fraud, we would collectively be doing a better job of measuring it. As the saying goes, “If you can’t measure it, you can’t improve it.” Because behaviors exhibited during first-party fraud are difficult to distinguish from those of legitimate consumers who’ve encountered catastrophic life events, such as illness and unemployment, individual account performance isn’t typically a good measurement. First-party fraud is a person-level event rather than an account-level event and needs to be viewed as such. So why does first-party fraud slip through the cracks? Existing, third-party fraud prevention tools aren’t trained to detect it. Underwriting relies on a point-in-time assessment, leaving lenders blind to intentions that may change after booking. When first-party fraud occurs, the different organizations that suffer losses attach different names to it based on their account-level view. It’s hidden in credit losses, preventing you from identifying it for future analysis. As an industry, we aren’t going to be able to solve the problem of first-party fraud as long as three different organizations can look at an individual and declare, “Never pay!” “No. Bust-out!” “No! Charge-off!” So, what do we need to stop doing? Stop thinking that it’s a different problem based on when you enter the picture. Whether you opened an account five years ago or 5 minutes ago doesn’t change the problem. It’s still first-party fraud if the person who owns the identity is the one misusing it. Stop thinking that the financial performance of an account you maintain is the only relevant data. And what do we need to start doing? See and treat first-party fraud as a continuous Leverage machine learning techniques and robust data (including your own observations) to monitor for emerging risk over Apply multiple levels of treatments to respond and tighten controls/reduce exposure as risk Define first-party fraud using a broader set of elements beyond your individual observations.

Identity-related fraud exposure and losses are increasing, and the underlying schemes are becoming more complex. To make better decisions on the need for step-up authentication in this dynamic environment, you should take a layered approach to the services you need. Some of these services include: Identity verification and reverification checks for ongoing reaffirmation of your customer identity data quality and accuracy. Targeted identity risk scores and underlying attributes designed to isolate identity theft, first-party fraud and synthetic identity. Layered, passive or more active authentication, such as document verification, biometrics, knowledge-based authentication and alternate data sources. Bad guys are more motivated, and they’re getting better at identity theft and synthetic identity attacks. Fraud prevention needs to advance as well. Future-proof your investments. More fraud prevention strategies to consider>

Consumer confidence is nearing an 18-year high. Unemployment figures are at record lows. Retail spend is healthy, and expected to stay that way through the back-to-school and holiday shopping booms. Translation for credit card issuers? The swiping and spending continue. In fact, credit card openings were up 4% in the first quarter of 2018 compared to the same time last year, and card utilization is hovering around 20.5%. Even with the Fed’s gradual 2018 rate hikes, consumers are shopping. In a new Mintel report, outstanding credit card debt is now $1.03 trillion (as of the end of Q1, 2018), and the number of consumers with credit cards is growing fastest among people aged 18 to 34. In the retail card arena specifically, boomers and Gen X’ers are leading the charge, opening 45% and 27% of new retails cards, respectively. “A stronger economy always bodes well for credit cards,” said Kelley Motley, director of analytics for Experian. “Now is the time for card issuers to zero in on their most loyal consumers and ensure they are treating them with the right offers, rewards and premium benefits.” Consumer data reveals the top incentives when selecting a rewards-based card includes cash back, gas rewards and retail cards (including travel rewards and airfare). In fact, for younger consumers, offering rewards has proven to be the most effective way to get them to switch from debit to credit cards. Cash back was the most preferred reward for consumers aged 18 to 44 when asked about their motivation to apply for a new card. For individuals 45 and older, 0% interest was the top motivator. Of course, beyond credit card opens, the ideal is to engage with the consumers who are utilizing the card the most. From a segmentation standpoint, the loyal retail cardholder has an average VantageScore® credit score of 671 with an average total balance of $1,633. They use the card regularly and consistently make payments. Finding more loyalists is the goal and can be achieved with informed segmentation insights and targeted prescreen campaigns. On the flip side, insights can inform card issuers with data, helping them to avoid wasting marketing dollars on consumers who merely want to game a quick credit card offer and then close an account. A batch and blast marketing approach no longer works in the credit card marketing game. “Consumers expect you to know them and their financial needs,” said Paul DeSaulniers, senior director of Experian’s segmentation solutions. “The data exists and tells you exactly who to target and how to structure the offer – you just need to execute.”

Consumer credit scores A recent survey* released by the Consumer Federation of America and VantageScore Solutions, LLC, shows that potential borrowers are more likely to have obtained their credit score than nonborrowers. 70% of those intending to take out a consumer or mortgage loan in the next year received their credit score in the past year, compared with 57% of those not planning to borrow. Consumers who obtained at least one credit score in the past year were more likely to say their knowledge of scores is good or excellent compared with those who haven’t (68% versus 45%). While progress is being made, there’s still a lot of room for improvement. By educating consumers, lenders can strengthen consumer relationships and reduce loss rates. It’s a win-win for consumers and financial institutions. Credit education for your customers>

  Keeping your customers happy is critical to success. And while reducing fraud is imperative, it shouldn’t detract from a positive customer experience. Here are 3 fraud detection and prevention strategies that can help you reduce fraud and protect (and retain) customers. Use customer-centric strategies — Recognizing legitimate customers online is more important than ever, particularly since the web’s built-in anonymity makes it a breeding ground for scammers and fraudsters. Balance fraud prevention and the customer experience — When implementing security protocols, consider consumers’ fluctuating and potentially diminishing tolerance levels for security protocols. Embrace new fraud protection technologies — Multilayered approaches should include data-driven, artificial intelligence–powered systems that will recognize customers while keeping their transactions stress-free. Fraud prevention shouldn’t discourage honest customers from buying, but it should instill confidence and strengthen the customer relationship. Learn more>

Believe it or not, 66% of consumers want to see some visible signs of security and barriers when accessing their accounts so they can be sure that a transaction is more secure. Other takeaways from our 2018 Global Fraud and Identity Report: Nearly 3/4 of surveyed businesses cite fraud as growing over the past 12 months. 30% of surveyed businesses are experiencing more fraud losses year-over-year. While 83% of businesses believe that their fraud solutions are scalable, cost is the biggest obstacle to adopting new tactics. There’s a delicate balance in delivering a digital experience that instills confidence while allowing for easy and convenient account access. It’s not easy to deliver both — but it is possible.

Business guide to new markets Competition is fierce. Expectations are high. Navigating a new market can be profitable — if managed strategically. Consider these actionable insights when entering a new market: Use historical data to identify the right target population. Identify, access and leverage the right data to gain the insights you need to make sound decisions. Consider insights from a seasoned professional for a bigger, more accurate picture of the market. Entering a new market isn’t without some risk. But with the right data, strategies and expertise, you can navigate new markets, reduce risk and start making profitable decisions. Learn more>  

Customer Identification Program (CIP) solution through CrossCore® Every day, I work closely with clients to reduce the negative side effects of fraud prevention. I hear the need for lower false-positive rates; maximum fraud detection in populations; and simple, streamlined verification processes. Lately, more conversations have turned toward ID verification needs for Customer Information Program (CIP) administration. As it turns out, barriers to growth, high customer friction and high costs dominate the CIP landscape. While the marketplace struggles to manage the impact of fraud prevention, CIP routinely disrupts more than 10 percent of new customer acquisitions. Internally at Experian, we talk about this as the biggest ID problem our customers aren’t solving. Think about this: The fight for business in the CIP space quickly turned to price, and price was defined by unit cost. But what’s the real cost? One of the dominant CIP solutions uses a series of hyperlinks to connect identity data. Every click is a new charge. Their website invites users to dig into the data — manually. Users keep digging, and they keep paying. And the challenges don’t stop there. Consider the data sources used for these solutions. The winners of the price fight built CIP solutions around credit bureau header data. What does that do for growth? If the identity wasn’t sufficiently verified when a credit report was pulled, does it make sense to go back to the same data source? Keep digging. Cha-ching, cha-ching. Right about now, you might be feeling like there’s some sleight of hand going on. The true cost of CIP administration is much more than a single unit price. It’s many units, manual effort, recycled data and frustrated customers — and it impacts far more clients than fraud prevention. CIP needs have moved far beyond the demand for a low-cost solution. We’re thrilled to be leading the move toward more robust data and decision capabilities to CIP through CrossCore®. With its open architecture and flexible decision structure, our CrossCore platform enables access to a diverse and robust set of data sources to meet these needs. CrossCore unites Experian data, client data and a growing list of available partner data to deliver an intelligent and cost-conscious approach to managing fraud and identity challenges. The next step will unify CIP administration, fraud analytics and a range of verification treatment options together on the CrossCore platform as well. Spoiler alert. We’ve already taken that step.

Trivia question: Millennials don’t purchase new vehicles. True or False?

When it comes to driving the automotive industry forward, Experian Automotive has a motto: “The right cars. The right customers. The right data to know the difference.” We deliver an integrated perspective based on the highest quality automotive information and market intelligence. Data is important to us, and we have the most robust combination of data assets under one roof. The North American Vehicle Database℠, File One℠ Credit Database, Consumer View℠ Marketing Database, Online Activity Databases, and National Fraud Database℠ all fed into Experian’s Auto HyperConnect™.   Auto HyperConnect houses two different solutions: Auto HyperTargeting™ and Auto HyperMonitoring™. There are four different components to Auto HyperTargeting, and the one we will focus on today is Expired Lease. Dealers have found success marketing to their own customers when vehicle leases come due. The challenge has been conquesting off-lease consumers who didn’t buy from them. While off-lease consumer marketing lists are available, they only provide the estimated lease end date and monthly lease payment.  When restricted to this data, it’s hard to tell if a $550 a month payment is for a Ford F150 or a BMW 3-series. And yet this is exactly the level of detail needed to successfully target off-lease marketing. Experian’s new Auto HyperTargeting- Expired Lease addresses this challenge by enabling dealers to identify and engage off-lease audiences through a highly targeted approach that has never been possible! Now, finding customers is much easier and cost-effective. You can use the best mix of selection criteria to maximize your off-lease conquesting strategy. Some of the ways you can identify your audience are: Lease Maturity Date Vehicle Make Vehicle Model Zip Code Model Performance Tier Distance from Dealer Ship Vehicle Status (New or Used) Signing up for Auto HyperTargeting- Expired Lease comes with five perks. The first is a monthly file. This includes name and address, lease maturity date, make/model, monthly payment bands, and phone and email address when available. The second is the ability to make sign up for a subscription monthly payments. Third is marketing flexibility with direct mail, email, and phone. Four there is no firm offer of credit required for this. Finally, a quarterly sales report. ARA reports provide sales metrics industry wide for your targets. Other competitive features also available in Auto HyperTargeting- Expired Lease is the customers full contact information with name, address, email address and phone number. And for online and offline channels, you can select a specific audience that is customizable. Auto HyperTargeting has some amazing features to successfully conquest customers, and Expired Lease is one of the four ways to do this. Stay tuned for Auto HyperTargeting- Vehicle Owners coming up next!

As more financial institutions express interest and leverage alternative credit data sources to decision and assess consumers, lenders want to be assured of how they can best utilize this data source and maintain compliance. Experian recently interviewed Philip Bohi, Vice President for Compliance Education for the American Financial Services Association (AFSA), to learn more about his perspective on this topic, as well as to gain insights on what lenders should consider as they dive into the world of alternative credit data. Alternative data continues to be a hot topic in the financial services space. How have you seen it evolve over the past few years? It’s hard to pinpoint where it began, but it has been interesting to observe how technology firms and people have changed our perceptions of the value and use of data in recent years. Earlier, a company’s data was just the information needed to conduct business. It seems like people are waking up to the realization that their business data can be useful internally, as well as to others.  And we have come to understand how previously disregarded data can be profoundly valuable. These insights provide a lot of new opportunities, but also new questions.  I would also say that the scope of alternative credit data use has changed.  A few years ago, alternative credit data was a tool to largely address the thin- and no-file consumer. More recently, we’ve seen it can provide a lift across the credit spectrum. We recently conducted a survey with lenders and 23% of respondents cited “complying with laws and regulations” as the top barrier to utilizing alternative data. Why do you think this is the case? What are the top concerns you hear from lenders as it relates to compliance on this topic? The consumer finance industry is very focused on compliance, because failure to maintain compliance can kill a business, either directly through fines and expenses, or through reputation damage. Concerns about alternative data come from a lack of familiarity. There is uncertainty about acquiring the data, using the data, safeguarding the data, selling the data, etc. Companies want to feel confident that they know where the limits are in creating, acquiring, using, storing and selling data. Alternative data is a broad term. When it comes to utilizing it for making a credit decision, what types of alternative data can actually be used?  Currently the scope is somewhat limited. I would describe the alternative data elements as being analogous to traditional credit data. Alternative data includes rent payments, utility payments, cell phone payments, bank deposits, and similar records. These provide important insights into whether a given consumer is keeping up with financial obligations. And most importantly, we are seeing that the particular types of obligations reflected in alternative data reflect the spending habits of people whose traditional credit files are thin or non-existent.  This is a good thing, as alternative data captures consumers who are paying their bills consistently earlier than traditional data does. Serving those customers is a great opportunity. If a lender wants to begin utilizing alternative credit data, what must they know from a compliance standpoint? I would begin with considering what the lender’s goal is and letting that guide how it will explore using alternative data. For some companies, accessing credit scores that include some degree of alternative data along with traditional data elements is enough. Just doing that provides a good business benefit without introducing a lot of additional risk as compared to using traditional credit score information. If the company wants to start leveraging its own customer data for its own purposes, or making it available to third parties, that becomes complex very quickly.  A company can find itself subject to all the regulatory burdens of a credit-reporting agency very quickly. In any case, the entire lifecycle of the data has to be considered, along with how the data will be protected when the data is “at rest,” “in use,” or “in transit.” Alternative data used for credit assessment should additionally be FCRA-compliant. How do you see alternative credit data evolving in the future? I cannot predict where it will go, but the unfettered potential is dizzying. Think about how DNA-based genealogy has taken off, telling folks they have family members they did not know and providing information to solve old crimes. I think we need to carefully balance personal privacy and prudent uses of customer data. There is also another issue with wide-ranging uses of new data. I contend it takes time to discern whether an element of data is accurately predictive.  Consider for a moment a person’s utility bills. If electricity usage in a household goes down when the bills in the neighborhood are going up, what does that tell us? Does it mean the family is under some financial strain and using the air conditioning less? Or does it tell us they had solar panels installed? Or they’ve been on vacation?  Figuring out what a particular piece of data means about someone’s circumstances can be difficult. About Philip Bohi Philip joined  AFSA in 2017 as Vice President, Compliance Education. He is responsible for providing strategic direction and leadership for the Association’s compliance activities, including AFSA University, and is the staff liaison to the Operations and Regulatory Compliance Committee and Technology Task Forces. He brings significant consumer finance legal and compliance experience to AFSA, having served as in-house counsel at Toyota Motor Credit Corporation and Fannie Mae. At those companies, Philip worked closely with compliance staff supporting technology projects, legislative tracking, and vendor management. His private practice included work on manufactured housing, residential mortgage compliance, and consumer finance matters at McGlinchey Stafford, PLLC and Lotstein Buckman, LLP. He is a member of the Virginia State Bar and the District of Columbia Bar. Learn more about the array of alternative credit data sources available to financial institutions.

In our previous post, we talked about Experian’s 2018 Attribution Study. This study is a wide-ranging, dealer-focused sales-driven attribution study to answer the question of what drives sales. Three takeaways were formed and the first was looking at shopper behavior instead of isolated KPIs. Now, we look at the second and third takeaways. Optimize your paid advertising Paid search is an important part of dealership marketing and precise targeting will help with both traffic and purchasing rate. Branded search drives quality traffic to websites. 7% of all traffic and 12% of HVU traffic comes from branded search. Along with traffic, the purchase rate was found to be 54% higher than average. In terms of value, New Make and Model has impressive results. 2% of all traffic and 12% of HVU traffic comes from New Make and Model. The purchase rate is 137% higher than average. Of note, we found that in order to optimize paid search to drive sales, you must buy your own name. 100% of dealers studied had buyers via branded search. With that, optimized “New Make Model” campaigns are crucial. 82% of dealers had buyers come through Make Model keywords. Traditionally, New Make Model would just create a higher funnel but since we are in the digital age, this does not happen anymore. Some participating dealers spent <20% of search budget on New Make Model campaigns. A key point is that no dealer had buyers come through via competitors’ keywords. As for a dealer’s website, display leasing offers and content for buyers since many search queries contained lease keywords. Although paid search is important, there are other channels to optimize and segmentation is key. This study found that conquesting with bulk email-blasts is not effective. You can achieve better email marketing results by targeting shoppers more intelligently and using quality lists. CRM-driven loyalty campaigns performed well in this segment. Display campaigns revealed that social media is no longer just for posting content but paid social advertising campaigns were effective. In fact, this study found Facebook display to be more effective than Google and other display networks. The reason is it is easier to segment and target a specific audience through Facebook. Google is more difficult to segment and has too many set-it-and-forget-it campaigns. Evaluate your third-party investments This brings us to third-parties, such as Automotive Shopping Portals and other lead providers. Performance with third-parties can vary and dealers should evaluate third-party performance as it relates to your sales. The third-party buy rate was under-indexed for dealers versus all sales. The business model for third-parties is not focused on driving traffic to dealer sites. Since there are so many vehicles listed on third-party sites from franchises, independent dealers, and private parties, there is a lot of “noise” for customers to sift through. For dealers, finding out what drives sales has led to Experian's 2018 Attribution. Our wide-ranging, dealer focused sales-driven attribution study focused on key variables and delivers three recommendations: Focus on website shopper behavioral metrics to drive sales. optimize paid search, specifically branded search and new make model campaigns. and evaluate third-party performance as it relates to your sales. With these, a dealer can be more confidant with their marketing and their data.