As soon as the holiday decorations are packed away and Americans reign in the New Year, the advertisements shift to two of our favorite themes – weight loss and taxes. No wonder the “blues” kick in during February. While taxes aren’t due until April 17, the months of January, February and March have consumers prepping to file. Coincidentally, it is also a big season for lenders to collect after the high-spending months of October through December. “Knowing which of your customers may receive a refund is critical,” said Colleen Rose, an Experian product manager specializing in the collections industry. “This information can help lenders create a strategy to capitalize on this important segment during the compressed collections window.” The industry has become more familiar with trended data and its ability to predict how consumers are faring on the credit score slider, but many don’t know that it has also proven popular in identifying people who may get a tax refund, and who is likely to use a refund to pay down delinquent balances. The past two tax seasons are evaluated to provide a complete picture of a customer’s behavior during tax refund season. Balance, credit limit and other historical fields are incorporated with tradeline-level data to determine who paid down their delinquent balances during this time. According to the IRS, in fiscal year 2016, the average individual income tax refund was about $3,050, so it’s a prime time for consumers to come into some unexpected cash to either pay down debt or spend. It’s estimated that 35% of consumers who get a refund will pay down debt. “Using Experian’s trended data attributes, we’ve identified past-due customers who paid down a delinquent tradeline balance by at least 10% and made a large payment during tax season,” said Rose. “With these specific attributes, we can help clients target a very desirable population during the critical collections months, helping them to refine their campaigns and create offers geared toward this population.” Anticipating who is likely to receive a refund and use it to pay down debt can influence how collections departments develop their messaging, call outreach and mailings. And for consumers who owe multiple debts, these well-timed touchpoints and messages could influence who they pay back first. The collectors with the best data, once again win, with trended data providing the secret sauce for predictions. ‘Tis the season for taxes.

The multitude of modern fraud strategies available today necessitates applying an appropriate level of confidence to increase the likelihood of catching fraudsters without disrupting legitimate customers’ experiences. This approach is known as “rightsizing” your fraud solution. Here’s how fraud detection rates can be improved while reducing the number of false positives and disruption of legitimate customers: A right-size approach means tackling your fraud problem with a highly tailored solution that enables your business rather than crippling it. Next week, we’ll discuss this forward-looking approach to fighting fraud, or you can jump ahead and read our latest tip sheet. Tip sheet>

You just finished redeveloping an existing scorecard, and now it’s time to replace the old with the new. If not properly planned, switching from one scorecard to another within a decisioning or scoring system can be disruptive. Once a scorecard has been redeveloped, it’s important to measure the impact of changes within the strategy as a result of replacing the old model with the new one. Evaluating such changes and modifying the strategy where needed will not only optimize strategy performance, but also maximize the full value of the newly redeveloped model. Such an impact assessment can be completed with a swap set analysis. The phrase swap set refers to “swapping out” a set of customer accounts — generally bad accounts — and replacing them with, or “swapping in,” a set of good customer accounts. Swap-ins are the customer population segment you didn’t previously approve under the old model but would approve with the new model. Swap-outs are the customer population segment you previously approved with the old model but wouldn’t approve with the new model. A worthy objective is to replace bad accounts with good accounts, thereby reducing the overall bad rate. However, different approaches can be used when evaluating swap sets to optimize your strategy and keep: The same overall bad rate while increasing the approval rate. The same approval rate while lowering the bad rate. The same approval and bad rate but increase the customer activation or customer response rates. It’s also important to assess the population that doesn’t change — the population that would be approved or declined using either the old or new model. The following chart highlights the three customer segments within a swap set analysis. With the incumbent model, the bad rate is 8.3%. With the new model, however, the bad rate is 4.9%. This is a reduction in the bad rate of 3.4 percentage points or a 41% improvement in the bad rate. This type of planning also is beneficial when replacing a generic model with another or a custom-developed model. Click here to learn more about how the Experian Decision Analytics team can help you manage the impacts of migrating from a legacy model to a newly developed model.

Cybersecurity has become one of the most significant issues impacting international security and political and economic stability. Our new report, Data Breach Industry Forecast 2018, outlines 5 predictions for the data breach industry in the coming year. Here are 3: The U.S. may experience its first large-scale attack on critical infrastructure, causing disruption for governments, companies and private citizens. Failure to comply with the new EU regulations will result in large penalties for U.S. companies. Attackers will use artificial intelligence to render traditional multifactor authentication methods useless. Read all five predictions>

When gearing up to buy a car, having a checklist of things to look for is important. Happily, it looks like consumers have added something new to the top of that list: managing their credit better. According to Experian’s latest State of Automotive Finance Market report, the average credit score for purchasing a vehicle has increased four points across the board, reaching 722 for new vehicles and 682 for used vehicles. That four-point increase may seem insignificant, but it reveals that consumers are actively managing their credit. With the recent trepidation over the so-called subprime auto finance bubble, the positive change is great news for people in the market to get a new ride. Per the Q3 report, subprime originations reached the lowest level of market share since 2012 (16.6 percent), while prime and super-prime originations showed the largest increases in market share. So what does all this mean? In addition to better managed credit, the increased market share of prime and super-prime consumers shows that industry professionals are leveraging data and analytics when making lending decisions. So if you’re looking to buy a car soon, how can you use that knowledge to your advantage? About six months before zooming to the dealership, take the time to check your credit report to make sure there are no surprises when a potential lender looks at it. Once you know where you stand, you can take steps to improve your credit (if needed) by paying bills on time, keeping balances low and not applying for any new credit before you’re ready to buy that car. Your credit is in good shape, so now what? When car shopping, don’t just look into vehicle make and model. Consider your financing options as well. Different lenders offer different terms and conditions, so comparing options can make sure that you’re getting the best deal possible. For example, our Q3 report shows that credit unions and captive financers (like Ford Motor Credit or Toyota Financial Services) are earning more customers and taking a greater market share of auto lending, at 21 percent and 29.8 percent, respectively. Banks still hold the largest percentage of auto loans at 32.9 percent, but they don’t dominate auto financing like they once did. Leasing is another financing option. Consumers often choose to lease because of lower monthly payments ($412 for a new lease as opposed to $502 for a new loan). The report shows that leasing continues to be a large part of new auto financing, coming in at 29 percent of all financed new vehicles. Lastly, the report shows that loan terms continue to be extended, with the average length of a loan hitting 69 months for new cars and nearly 64 months for used. Extending loan terms can lower your monthly payment, but you should use it mindfully, so the total cost of the vehicle loan doesn’t exceed your budget. For more information about the current State of the Automotive Finance Market report or to view a recording of the webinar, visit our website.

Student loan debt is weighing down Americans of all generations, but a college education is still prized as the ticket to opportunity. So will the debt continue to climb? Where will students turn for funding? We interviewed Vince Passione, founder and CEO of LendKey, a lending-as-a-service platform specializing in student lending, to gain his perspective on the state of student lending and how the space is evolving for both consumers and lenders. We’ve all seen the headlines about U.S. student loan debt now accounting for $1.4 trillion. The majority of these loans are government-funded, but do you see this shifting? There are many factors at play here. Tuition is rising rapidly and will soon outpace the current level of governmental support available to students searching for loans. Meanwhile, today’s geopolitical climate signals that the current levels of federal funding will also decrease. With these two confounding trends, the need for competitively priced private financing and refinancing options will increase. The student loan industry will shift toward private lenders such as credit unions and banks in order for students to continue to obtain the funds they need for tuition and other college expenses. The key to helping this transition happen is for banks and credit unions to adopt the user-friendly technology platforms that appeal to these prospective student borrowers. Your end-to-end cloud-based technology platform enables lenders to get into the student loan space. How does this work and what must lenders consider as they underwrite and manage a student loan portfolio? Our turnkey platform is unique, in that it lets lenders control underwriting and pricing, unlike the “disruptive” model utilized by many other technology companies in the industry. Most community banks and credit unions lack the in-house resources to develop, implement and maintain an online lending platform. At the same time, millennials and young borrowers continue to prefer the online interface rather than engaging with a brick-and-mortar establishment. We’re committed to partnering with banks and credit unions to allow them to offer private consumer loans, such as student loans, and support them with our technology (loan application and decisioning) and people (customer service agents and loan processors). A strong grasp on the technology and support aspects of online lending platforms alone is merely the foundation for a successful program. As the student lending asset classes are highly regulated, and the regulations are constantly changing, lenders must look to partner with a firm that has a concrete understanding of the regulation, risk and customer service to translate the information to prospective borrowers. I’ve heard you use the phrase “HENRY.” Can you explain what this is and why these individuals are so lucrative for lenders? HENRY stands for “High Earners, Not Rich Yet” and is a term that can be applied to many millennials and young people in today’s economy. This demographic is typically college graduates with well-paying jobs, but have not yet established themselves financially or accrued enough wealth to subsidize larger purchases like cars, homes, renovations and advanced degrees. This is also why they are so lucrative for lenders. HENRYs have just entered their prime borrowing years and are consumers who will easily be able to pay back loans for cars, homes and renovations. But for most of this demographic, their first experience with a financial service product will be a student loan. It is important to get in on the ground floor with these borrowers through student lending to establish a trusted relationship that will result in repeat loans and referrals. You’ve done a great deal of research on millennials and how they are managing student loans. Can you share some of your key learnings? Do you believe Generation Z will behave and manage student debt similarly? It’s no secret that millennials are more apprehensive of student loans than previous generations. As Gen Z begins to enter college, many are plagued with stigmas set forward by the poor experiences millennials experienced with student loans, making them wary of debt. According to a study, 63 percent of the students said they would “possibly” take on student debt, down from 71 percent in 2016. Gen Z is better prepared by seeing the preceding generation grapple with loan issues. Many are making smarter decisions on schools and programs, and are attentive when it comes to monitoring for updates in regulation. As this generation continues to go through the typical collegiate years, the geopolitical climate, as well as rising tuition costs, will increase the need for competitively priced private financing options for Gen Zers. Finally, what trends or predictions do you see occurring in the student lending space over the next five years? The need for student loans continues to exist and shows no sign of slowing down anytime soon, but lenders are only recently opening their eyes to the opportunity that this massive market presents. With the impending drop in federal funding, more FinTech companies will continue to pop up to address this need. This spike in disruption also poses a threat to banks and credit unions, however. With more FinTechs available to help shoulder the burden of student lending, banking and credit union executives must be more judicious when vetting technology partners to ensure they’re working with a partner that meets their regulatory standards, supports their current and prospective clients, and lets them retain the control they wish to keep in-house.

Auto originations continue to increase — particularly within prime categories. According to Experian’s latest State of the Automotive Finance Market report: Prime consumers grabbed the lion’s share of the total finance market, at 40.9%. Super-prime buyers showed the largest increase, reaching 20.2%. Consumers outside the prime category (credit score of 600 or lower) decreased to the lowest share on record since 2012. Credit unions and captive lenders increased market share of total vehicle financing, growing to 21% and 29.8% — an increase of 6.9% and 35.1%, respectively. As auto loan originations continue their upward trend, lenders can stay ahead of the competition by using advanced analytics to target the right customers and increase profitability.  

Data breach industry predictions High-profile data breaches dominated the headlines in 2017, and unfortunately, these attacks are anticipated to only increase in frequency and magnitude in 2018. Breaches like those that affected LinkedIn, Dropbox and Yahoo, serve as a wake-up call for organizations to implement processes for safeguarding sensitive data and defending against attacks. However, for every advancement in cybersecurity, cybercriminals become more sophisticated in their techniques. Just when it seems like we have learned our lesson from one breach, another, more significant one occurs. As cybercriminals continue changing the rules mid-game, it has become clear that while they’re playing chess, we’re still playing checkers. To help better prepare you and your organization for potential cyber threats, our team has put together its yearly data breach industry predictions on the issues and trends surrounding data security in 2018. Here are our five predictions for 2018: The U.S. may experience its first large-scale attack on critical infrastructure, disrupting governments, companies and private citizens. Failure to comply with new EU regulations will result in large penalties for U.S. companies. Perpetrators of cyber-attacks will continue to zero in on governments – this could lead to a shift in world power. Attackers will use artificial intelligence (AI) to render traditional multifactor authentication methods useless. Vulnerabilities in Internet of Things (IoT) devices will create mass confusion, leading to new security regulations. Download our complimentary report to learn more about how these trends will shape the coming year, see how we scored against our 2017 predictions, and check out our new section revisiting predictions dating back to our inaugural 2014 report.

“Are we next?” That’s the question companies around the world are grappling with as more high-profile data breaches make headlines. At a time when one in four organizations experience cyber-attacks, mishandling the response can do more damage than the breach itself. We take precautions against dangerous situations every day. With years of practice either in school or at work, most of us know what to do if there’s an emergency. We conduct drills repeatedly because when we immediately know how to respond to a threatening situation, we can minimize destruction. Because of the high probability of a cyber-attack, businesses need to treat breach responses like internal drills, repeatedly practicing until it becomes instinctive. Prepare your data breach response drill A well-prepared incident response strategy should first define all breach scenarios (e.g., ransomware, malware, phishing, etc.) and their specific steps. Assembling a qualified team is also critical, individual roles and responsibilities should be defined and clearly communicated. After finalizing the essential components of your incident response plan, regular testing is crucial to ensuring your organization is equipped to handle the unexpected. Practice makes perfect Below are six principles to help guide your data breach response drill effectively: Bring in an outsider. Enlist the expertise of someone outside your organization to run the drills and serve as a moderator. A third-party facilitator allows you and your team to focus on individual tasks and responsibilities. Put aside plenty of time. At a minimum, give your team half a day to do the exercise and to debrief. It’s an exercise for everyone. All internal and external team members who will be involved in a data breach response need to participate in this activity. Expect the unexpected. Your drills should include various likelihoods and situations. Another benefit to bringing in an outside moderator is that they can throw unpredictable scenarios at your team. Debrief. After the exercise, the entire team should review, discuss each mock situation in detail, and identify any areas in need of improvement. Repeat every six months. Keep your team aware of the latest developments in the world of cybersecurity and prepared to tackle cyber threats by conducting drills every six months. Executing these drills are invaluable and help prove to your stakeholders, customers and employees that your company takes data security seriously. The more you practice putting your plan into action, the better prepared you’ll be in a real-life situation. Visit our website for more information about our offerings and how Experian can help you prepare and respond to data breaches.

Traditional verification and validation parameters alone are not enough to stop identity fraud. Fortunately, there are many emerging trends and best practices for modern fraud and identity strategies: Applying right-sized fraud and identity proofing solutions to reduce user friction and manage fraud risk appropriately. Maintaining a universal user view by employing diverse breadth and depth of data assets and applied analytics. Expanding the user view through a blended ecosystem by collaborating with vendors, peer agencies, and partners in identity and fraud management. The future of identity proofing is more than just verifying individual identities. Check out our tip sheet linked below for more strategies. Modernize your fraud and identity strategies>

  The journey to a mortgage is complex and expensive, so of course the transaction will require more than a few swipes on a smartphone. The U.S. existing home median sales price in October was $274,000 – not cheap. Still, with advancements in digital verification, lenders can dramatically accelerate the process, providing benefits to both their own operations and the consumer mortgage experience. Underwriting a sizeable loan can take weeks with the task of collecting income and asset documents to analyze and verify. In fact, one source from the Mortgage Bankers Association says the average mortgage application has ballooned to 500 pages. The consumer is typically asked to find, print and scan papers revealing insights around employment status and wages, bank and retirement accounts, debts and beyond. The good news is that this process can be handled digitally, and I’m not talking about simply scanning and emailing. Verification solutions exist to enable consumers to grant limited and secure access to digitally verify assets and income. As lenders evaluate verification solutions, one of the key differentiators to seek is Fannie Mae Day 1 Certainty, which claims to slash the average cycle time for income validation by 8.1 days, employment validation by 11.9 days, and asset validation by 6.1 days. * Fannie Mae features a list of approved vendors who provide Fannie Mae-approved verification reports. This group of authorized suppliers receive freedom from representations and warranties for more efficient risk management, and additionally receive the benefit of a more streamlined process through Fannie Mae’s Desktop Underwriter® (DU®). DU’s latest enhancement leverages a verification of asset report derived from aggregated bank account data, something Finicity (an Experian partner) is approved to utilize. Building on Day 1 Certainty, Finicity is participating in a new single source pilot with Fannie Mae to validate income, assets and employment. While it will take time for lenders to embrace this new technology – and consumers will need to feel comfortable granting the digital access and understanding how the process works – the thought is the mortgage journey will become faster and offer an optimized borrower experience. Like so many other aspects in our lives, mortgage is bound to go digital. *Average days saved reflects data captured between January 2017 and June 2017.

Alternative Data Shedding New Light on Consumers Why Investors Want Alternative Data Banks and Tech Firms Battle Over Something Akin to Gold: Your Data Alternative data for credit has created national headlines in the past year and a lasting buzz in the financial services world. But what exactly qualifies as alternative data in credit? How can it benefit lenders? Consumers? Ask two people these questions and you may get very different answers. Experian defines alternative data as FCRA-compliant data points that are not typically considered when evaluating a potential customer’s creditworthiness. These data points may include rent payments; utility payments, including gas, electric; telecommunications payments, such as mobile telephones; insurance payments; and any other recurring financial obligations. Taking these alternative data points into account can benefit consumers and lenders in multiple ways. Consider that roughly 45 million Americans have either no credit history, or a credit history that is too scarce or outdated to manufacture a credit score. This group of consumers includes not only minority consumers or those from low income neighborhoods, but also the shared economy workforce and millennials without traditional credit histories. Some estimate 121 million U.S. adults are credit-challenged with thin-to-no credit file and subprime credit scores below 600. “People with little or no credit history, or who lack a credit score, have fewer opportunities to borrow money to build a future, and any credit that is available usually costs more,” said Richard Cordray, while he was director of the Consumer Financial Protection Bureau. Indeed, these consumers are in a catch-22; many lenders will not lend to consumers with credit scores of under 620. In turn, these consumers have trouble building credit, and they are blocked from achieving goals like buying a car, owning a home or starting a business. By combining credit reports with alternative data, a more complete picture of subprime, near-prime and thin-file consumers can develop. And analysis of this data can help lenders evaluate a consumer’s ability to pay. When alternative data like rent payments and an individual’s short term lending history are trended appropriately, it can be an accurate predictor of an individual’s financial behavior, and can be an important step toward promoting greater financial inclusion for more consumers. In addition to using alternative data in underwriting, lenders can leverage the data to help with: Expanding the prospecting universe. Data can be used to enrich batch prospecting decisioning criteria to identify better qualified prospects, suppress high-risk consumers, and offer a more complete borrowing history Account review. Alternative data can help signal a consumer’s financial distress earlier, better manage credit lines and grow relationships with existing consumers. Collections. Identify consumers who are rebuilding credit with specialty finance trades, or who are exhibiting high-risk behaviors in the alternative financial services space. More info on Alternative Credit Data More Info on Alternative Financial Services

For most businesses, the customer experience is at the heart of every strategy. Debt collection shouldn’t be different. Here’s why: 21% of visits to an online debt recovery system were made outside the traditional working hours of 8 a.m. to 8 p.m. Of the consumers who committed to a repayment plan, only 56% did so in a single visit. PricewaterhouseCoopers reported that 46% of consumers use only digital channels to conduct banking, avoiding traditional offline channels. Conversely, data collected by Gallup between 2013 and 2016 showed that 48% of American banking customers would only consider using a bank that offered physical branches. The debt collection process is an often-overlooked opportunity to build customer relationships and loyalty. Leverage data and technology to replace outdated approaches, minimize charge-offs and create environments that value each customer. Learn more>

It’s no secret. Consumers engage and interact with brands through a variety of channels, including email, direct mail, websites and mobile. And since most organizations work to keep the consumer experience at the core, they tend to invest in an omnichannel approach that caters to the consumer’s preferences. The lone exception may be during the collections process. Often, once an account falls behind on payment, the consumer experience falls behind with it. But should it? While many banks and financial institutions view the collections process merely as an opportunity to collect outstanding debt, the potential is much more. If treated effectively, the collections process can present an opportunity to develop a positive customer relationship that builds loyalty over time. If handled poorly, the collections process could cost an organization a number of lifetime customers. To correct this, banks and financial institutions need to implement the same omnichannel approach in the collections process as they do with every other consumer interaction. Collections can no longer be treated as a linear process that leads from one channel to the next. There needs to be a more personalized touch — communicating with consumers through preferred channels, contacting them at the most opportune times. Sound complex? Sure. But consider a recent Experian analysis that invited consumers to establish a nonthreatening dialogue with an online debt recovery system. The analysis revealed 21 percent of visits to an organization’s website were outside the traditional working hours of 8 a.m. to 8 p.m. Furthermore, of the consumers who committed to a repayment plan, only 56 percent did so in a single visit. Each consumer is different. So is each situation. And banks and financial institutions need to acknowledge those differences. Luckily, technology can address the complexities of an omnichannel and personalized approach. Platforms such as Experian’s PowerCurve® Collections enable banks and financial institutions to simplify the collections process for both the consumer and the organization. By treating the collections process the same as any other stage in the consumer journey, organizations have an opportunity to build a relationship. And to do so, banks and financial institutions need to leverage the data and technology at their disposal. If they do so appropriately, they’ll minimize their charge-offs and also create a lifetime customer. To learn more about leveraging the collections process to build customer loyalty, download our white paper Getting in front of the shift to omnichannel collections.

Experian on the State of Identity podcast In today’s environment, any conversation on the identity management industry needs to include some mention of synthetic identity risk. The fact is, it’s top of mind for almost everyone. Institutions are trying to scope their risk level and identify losses, while service providers are innovating ways to solve the problem. Even consumers are starting to understand the term, albeit via a local newscast designed to scare the heck out of them. With all this in mind, I was very happy to be invited to speak with Cameron D’Ambrosi at One World Identity (OWI) on the State of Identity podcast, focusing on synthetic identity fraud. Our discussion focused on some of the unique findings and recommended best practices highlighted in our recently published white paper on the subject, Synthetic identities: getting real with customers. Additionally, we discussed how a lack of agreement on the definition and size of the synthetic identity problem further complicates the issue. This all stems from inconsistent loss reporting, a lack of confirmable victims and an absence of an exact definition of a synthetic identity to begin with. Discussions must continue to better align us all. I certainly appreciate that OWI dedicated the podcast to this subject. And I hope listeners take away a few helpful points that can assist them in their organization’s efforts to better identify synthetic identities, reduce financial losses and minimize reputation risks.