Credit Lending
There are about as many definitions for people-based marketing as there are companies using the term. Each company seems to skew the definition to fit their particular service offering. The distinctions are vast, and especially for financial services companies running regulated campaigns, they can be incredibly important. At Experian, we define people-based marketing in its purest form: targeting at the individual level across channels. This is a practice we’re very familiar with in offline marketing, having honed arguably one of the most accurate views of U.S. consumers over the past three decades. And now we’re taking those tried and true principals and applying them to digital channels. It’s not as easy as it sounds. The challenge with people-based marketing With direct mail, people-based marketing was easy. Jane Doe lives at 123 Main St. If I want to reach her, I can simply send her a direct mail piece at that address. To help, I can utilize any number of services, including the National Change of Address database, to know where to reach her if she ever moves. People-based marketing through digital channels is exponentially more difficult. While direct mail has one signal with which you use to identify a consumer (the address), digital channels offer countless signals. And not all of those signals can be used, either individually or in conjunction with other signals, to reliably tie a consumer to a persistent offline ID. A prime example of this is cookies. The problem with cookies A cookie, in and of itself, isn’t the problem. The problem is the linkage. How was a cookie associated with the person to whom the ad is being served? As marketers, we need to make sure that we are reaching the right people with the right ad … and more importantly not reaching those people who have opted out. This is especially true in the world of regulated data, where you need to know who you are targeting. And cookie-based linkage is controlled by a handful of companies, many of which are walled gardens who don’t share how they link offline people to online cookies and don’t collect this information directly. They rely on other third-party websites to gather PII, and connect it to their cookies. In some cases, the data is very accurate (especially with transaction data). In some cases, it is not (think websites that collect PII when giving surveys, offering coupons, etc.). In short, in order for you to use cookie-based targeting accurately, you need to have insight into the source of the base linkage data that was used to connect the offline consumer record to the online cookie. This same concept applies to all forms of digital linkage that drive people-based marketing. Why does people-based marketing matter in digital credit marketing? With campaigns that utilize non-regulated data, such as “Invitation to Apply” campaigns that are driven from demographic and psychographic data, the consequences of not reaching the consumer you meant to target are negligible. But with campaigns that utilize regulated data, you must ensure you’re targeting the exact consumer you meant to reach. More importantly, you must make sure you’re not targeting an ad to a consumer who had previously opted out of receiving offers driven with regulated data (prescreen offers, for example). Even if you’ve already delivered a direct mail piece with the same offer, this doesn’t negate your responsibility to reach only approved consumers who have not opted out. --- Bottom line, the world of 1:1 marketing is growing more sophisticated, and that’s a good thing. Marketers just need to understand that while regulated data can be powerful, they must also take great responsibility when handling it. The data exists to deliver firm offers of credit to your very specific target in all-new mediums. People-based marketing has its place, and it can now be done in a compliant, digitally-savvy way – in the financial services space, nonetheless. Register for our webinar on Credit Marketing Strategies to Drive Today\'s Digital Consumer.
For an industry that has grown accustomed to sustained year-over-year growth, recent trends are concerning. The automotive industry continued to make progress in the fourth quarter of 2016 as total automotive loan balances grew 8.6% over the previous year and exceeded $1 trillion. However, the positive trend is slowing and 2017 may be the first year since 2009 to see a market contraction. With interest rates on the rise and demand peaking, automotive lending will continue to become more competitive. Lenders can be successful in this environment, but must implement data-driven targeting strategies. Credit Unions Triumph Credit unions experienced the largest year-over-year growth in the fourth quarter of 2016, increasing 15% over the previous period. As lending faces increasing headwinds amid rising rates, credit unions can continue to play a greater role by offering members more competitive rates. For many consumers, a casual weekend trip to the auto mall turns into a big new purchase. Unfortunately, many get caught up in researching the vehicle and don’t think to shop for financing options until they’re in the F&I office. With approximately 25% share of total auto loan balances, credit unions have significant potential to recapture loans of existing members. Successful targeting starts with a review of your portfolio for opportunities with current members who have off-book loans that could be refinanced at a lower rate. After developing a strategy, many credit unions find success targeting these members with refinance offers. Helping members reduce monthly payments and interest expense provides an unexpected service that can deepen loyalty and engagement. But what criteria should you use to identify prospects? Target Receptive Consumers As originations continue to slow, marketing response rates will as well, leading to reduced marketing ROI. Maintaining performance is possible, but requires a proactive approach. Propensity models can help identify consumers who are more likely to respond, while estimated interest rates can provide insight on who is likely to benefit from refinance offers. Propensity models identify who is most likely to open a new trade. By focusing on these populations, you can cut a mail list in half or more while still focusing on the most viable prospects. It may be okay in a booming economy to send as many offers as possible, but as things slow down, getting more targeted can maintain campaign performance while saving resources for other projects. When it comes to recapture, consumers refinance to reduce their payment, interest rate, or both. Payments can often be reduced simply by ‘resetting’ the clock on a loan, or taking the remaining balance and resetting the term. Many consumers, however, will be aware of their current interest rate and only consider offers that reduce the rate as well. Estimated interest rates can provide valuable insight into a consumer’s current terms. By targeting those with high rates, you are more likely to make an offer that will be accepted. Successful targeting means getting the right message to the right consumers. Propensity models help identify “who” to target while estimated interest rates determine “what” to offer. Combining these two strategies will maximize results in even the most challenging markets. Lend Deeper with Trended Data Much of the growth in the auto market has been driven by relatively low-risk consumers, with more than 60% of outstanding balances rated prime and above. This means hypercompetition and great rates for the best consumers, while those in lower risk tiers are underserved. Many lenders are reluctant to compete for these consumers and avoid taking on additional risk for the portfolio. But trended data holds the key to finding consumers who are currently in a lower risk tier but carry significantly less risk than their current score suggests. In fact, historical data can provide much deeper insight on a consumer’s past use of credit. As an example, consider two consumers with the same risk score at a point in time. While they may be judged as carrying similar risk, trended data shows one has taken out two new trades in the past 6 months and has increasing utilization, while the other is consolidating and paying down balances. They may have the same risk score today, but what will the impact be on your future profitability? Most risk scores take a snapshot approach to gauging risk. While effective in general, it misses out on the nuance of consumers who are trending up or down based on recent behavior. Trended data attributes tell a deeper story and allow lenders to find underserved consumers who carry less risk than their current score suggests. Making timely offers to underserved consumers is a great way to grow your portfolio while managing risk. Uncertain Future The automotive industry has been a bright spot for the US economy for several years. It’s difficult to say what will happen in 2017, but there will likely be a continued slowing in originations. When markets get more competitive, data-driven targeting becomes even more important. Propensity models, estimated interest rates, and trended data should be part of every prescreen campaign. Those that integrate them now will likely shrug off any downturn and continue growing their portfolio by providing valuable and timely offers to their members.
Credit reports provide a wealth of information. But did you know credit attributes are the key to extracting critical intelligence from each credit report? Adding attributes into your decisioning enables you to: Improve acquisition strategies and implement policy rules with precision. Segment your scored population for more refined risk assessment. Design more enticing offers and increase book rates. Attributes can help you make more informed decisions by providing a more granular picture of the consumer. And that can make all the difference when it comes to smart lending decisions. Video: Making better decisions with credit attributes
The final day of Vision 2017 brought a seasoned group of speakers to discuss a wide range of topics. In just a few short hours, attendees dove into a first look at Gen Z and their use of credit, ecommerce fraud, the latest in retail, the state of small business and leadership. Move over Millennials – Gen Z is coming of credit age Experian Analytics leaders Kelley Motley and Natasha Madan gave audience members an exclusive look at how the first wave of Gen Z is handling and managing credit. Granted most of this generation is still under the age of 18, so the analysis focused on those between the ages of 18 to 20. Yes, Millennials are still the dominant generation in the credit world today, standing strong at 61 million individuals. But it’s important to note Gen Z is sized at 86 million, so as they age, they’ll be the largest generation yet. A few stats to note about those Gen Z individuals managing credit today: Their average debt is $12,679, compared to younger Millennials (21 to 27) who have $65,473 in debt and older Millennials (28 to 34) who sport $121,460. Given their young age, most of Gen Z is considered thin-file (less than 5 tradelines) Average Gen Z income is $33,000, and average debt-to-income is low at 5.7%. New bankcard balances are averaging around $1,574. As they age, acquire mortgages and vehicles, their debt and tradelines will grow. In the meantime, the speakers provided audience members a few tips. Message with authenticity. Think long-term with this group. Maintain their technological expectations. Build trust and provide financial education. State of business credit and more on the economy Moody’s Cris deRitis reiterated the U.S. economy is looking good. He quoted unemployment at 4.5%, stating “full employment is here.” Since the recession, he said we’ve added 15 million jobs, noting we lost 8 million during the recession. The great news is that the U.S. continues to add about 200,000 jobs a month, and that job growth is broad-based. Small business loans are up 10% year-to-date vs. last year. While there has been a tremendous amount of buzz around small business, he adds that most job creation has come from mid0size business (50 to 499 employees). The case for layered fraud systems Experian speaker John Sarreal shared a case study that revealed by layering on fraud products and orchestrating collaboration, a business can go from a string 75% fraud detection rate to almost 90%. Additionally, he commented that Experian is working to leverage dark web data to mine for breached identity data. More connections for financial services companies to make with mobile and social Facebook speaker Olivia Basu reinforced the need for all companies to be thinking about mobile. “Mobile is not about to happen,” she said. “Mobile is now. Mobile is everything. You look at the first half of 2017 and we’re seeing 40% of all purchases are happening on mobile devices.” Her challenge to financial services companies is to make marketing personal again, and of course leverage the right channels. Experian Sr. Director of Credit Marketing Scott Gordon commented on Experian’s ability to reach consumers accurately – whether that be through direct or digital delivery channels. A great deal of focus has been around person-based marketing vs. leveraging the cookie. -- The Vision conference was capped off with a keynote speech from legendary quarterback and Super Bowl MVP Tom Brady. He chatted about the details of this past season, and specifically the comeback Super Bowl win in February 2017. He additionally talked about leadership and what that means to creating a winning team and organization. -- Multiple keynote speeches, 65 breakout sessions, and hours of networking designed to help all attendees ready themselves for growing profits and customers, step up to digital, regulatory and fraud challenges, and capture the latest data insights. Learn more about Experian’s annual Vision conference.
Risk analysts are insatiable consumers of big data who require better intelligence to develop market insights, evaluate risk and confirm business strategies. While every credit decision, risk assessment model or marketing forecast improves when it is based on better, faster and more current data, leveraging large data sets can be challenging and unproductive. That’s why Experian added a new functionality to its Analytical Sandbox, giving clients the flexibility they need to analyze big data efficiently. Experian’s Analytical Sandbox now utilizes H2O –an open source machine learning and deep learning platform that can model and predict with high accuracy billions of rows of high-dimensional data from multiple sources in various formats. Through machine learning and advanced predictive modeling, the platform enables Experian to better provide on-demand data insights that empowers analysts with high-quality intelligence to inform regional trends, provide consumer transactional insight or expose marketing opportunities. As a hosted service, Sandbox is offered as a plug-and-play, meaning no internal development is required. Clients can instantly access the data through a secure Web interface on their desktop, giving users access to powerful artificial and business intelligence tools from their own familiar applications. No special training is required. “AI monetizes data,” said SriSatish Ambati, CEO of H2O.ai. “Our partnership with Experian democratizes and delivers AI to the wider community of financial and risk analysts. Experian\'s analytics sandbox can now model and predict with high accuracy billions of rows of high-dimensional data in mere seconds.” Through H2O and the Experian Sandbox, machine learning and predictive analytics are giving risk managers from financial institutions of all sizes the ability to incorporate machine learning models into their own big data processing systems.
In just a few short hours, Vision attendees immersed themselves into the depths of the economy, risk models, specialty finance data, credit invisibles, student loan data, online marketplace lending and more. The morning kicked off with one of the most respected and trusted macroeconomists in the U.S., Diane Swonk. With a rap sheet filled with advising central banks and multinational companies, Swonk treated a packed house to a look back on what has transpired in the U.S. economy since the Great Recession, as well as launching into current state and speculating on the months ahead. She described the past decade not as “lost, but rather lagging.” She went onto to say this past year was transitional, and while markets slowed slightly during the months leading up the U.S. presidential election, good things are happening: We’ve finally broken out of the 2% wage rut Recruiting on college campuses has picked up The labor force is growing Debt-to-income levels have returned to where they were prerecession and Investment is coming back. “I believe we’ll see growth over 2% this year,” said Swonk. Still, change is underway. She commented on how the way U.S. consumer spending is changing, and of course we’re seeing a restructuring in the retail space. While JC Penney announces store closings, you simultaneously see Amazon moving from “click to brick,” dabbling in the opening of some actual storefronts. Globally, she said the economy is the strongest it has been in eight years. She closed by noting there is a great deal of political change and unrest in the world today, but says, “Never underestimate our abilities when we tap our human capital.” -- More than 100 attendees filled a room to hear about the current trends and the future of online lending with featured guests from Oliver Wyman, Marlette Funding and Lending USA. While speakers commented on the “hiccup” in the space last year with some layoffs and mergers, volume has continued to double every year for the past several years with roughly $40 billion in cumulative originations today. Panelists discussed the use of alternative data to decision, channel bias, the importance of partnerships and how the market will see fewer and fewer players offering just one product specialty. “It is expensive to acquire customers, so you don’t just want to have one product to sell, but rather a range,” said Sharat Shankar of Lending USA. -- The numbers in the student lending universe are astounding. In a session focused on the U.S. student loan market, new Experian data reveals there is $1.49 billion in total student loan outstandings. In fact, total outstandings have grown 21% over the past four years, while the number of trades have only grown 4%. Costs are skyrocketing. The average balance per trade has grown 17% over the past four years. “We don’t ration education in this country,” said Joe DePaulo of College Ave. Student Loans. “We give everyone access to liquidity when it comes to federal student loans – and it’s not like that in other countries.” While DePaulo notes the access is great, offering many students the opportunity to obtain higher education, he says the problem is with disclosures. Guardians are often the individuals filling out the FAFSA, but the students inherit the loans. Students, he says, rarely understand how much their monthly payment will ultimately be after graduation. For every $10,000 in student loans, he says that will generally equate to a $100 monthly payment. -- Tomorrow, Vision attendees will be treated to more breakout sessions and a concluding keynote with legendary quarterback Tom Brady.
So many insights and learnings to report after the first full day of 2017 Vision sessions. From the musings shared by tech engineer and pioneer Steve Wozniak, to a panel of technology thought leaders, to countless breakout sessions on a wide array of business topics … here’s a look at our top 10 from the day. A mortgage process for the digital age. At last. In his opening remarks, Experian President of Credit Services Alex Lintner asked the audience to imagine a world when applying for a mortgage simply required a few clicks or swipes. Instead of being sent home to collect a hundred pieces of paper to verify employment, income and assets, a consumer could click on a link and provide a few credentials to verify everything digitally. Finally, lenders can make this a reality, and soon it will be the only way consumers expect to go through the mortgage process. The global and U.S. economies are stable. In fact, they are strong. As Experian Vice President of Analytics Michele Raneri notes, “the fundamentals and technicals look really solid across the countries.” While many were worried a year ago that Brexit would turn the economy upside down, it appears everything is good. Consumer confidence is high. The Dow Jones Index is high. The U.S. unemployment rate is at 4.7%. Home prices are up year-over-year. While there has been a great deal of change in the world – politically and beyond – the economy is holding strong. The rise of the micropreneur. This term is not officially in the dictionary … but it will be. What is it? A micropreneur is a business with 0 to 4 employees bringing in no more than $200k in annual revenue. But the real story is that numbers show microbusiness are improving on many fronts when it comes to contribution to the economy and overall performance compared to other small businesses. Keep an eye on these budding business people. Fraud is running fierce. Synthetic identity losses are estimated in the hundreds of millions annually, with 50% year-over year growth. Criminals are now trying to use credit cleaners to get tradelines removed from used Synthetic IDs. Oh, and it is essential for businesses to ready themselves for “Dark Web” threats. Experts advise to harden your defenses (and play offense) to keep pace with the criminal underground. As soon as you think you’ve protected everything, the criminals will find a gap. The cloud is cool and so are APIs. A panel of thought leaders took to the main stage to discuss the latest trends in tech. Experian Global CIO Barry Libenson said, “The cloud has changed the way we deliver services to our customers and clients, making it seamless and elastic.” Combine that with API, and the goal is to ultimately make all Experian data available to its customers. Experian President of Decision Analytics Steve Platt added, “We are enabling you to tap into what you need, when you need it.” No need to “rip and replace” all your tech. Expect more regulation – and less. A panel of regulatory experts addressed the fast-changing regulatory environment. With the new Trump administration settling in, and calls for change to Dodd-Frank and the Consumer Financial Protection Bureau (CFPB), it’s too soon to tell what will unfold in 2017. CFPB Director Richard Cordray may be making a run for governor of Ohio, so he could be transitioning out sooner than the scheduled close of his July 2018 term. The auto market continues to cruise. Experian’s auto expert, Malinda Zabritski, revealed the latest and greatest stats pertaining to the auto market. A few numbers to blow your mind … U.S. passenger cars and light trucks surpassed 17 million units for the second consecutive year Most new vehicle buyers in the U.S. are 45 years of age or older Crossover and sport utility vehicles remain popular, accounting for 40% of the market in 2016 – this is also driving up finance payments since these vehicles are more expensive. There are signs the auto market is beginning to soften, but interest rates are still low, and leasing is hot. Defining alternative data. As more in the industry discuss the need for alternative data to decision, it often gets labeled as something radical. But in reality, alternative data should be simple. Experian Sr. Director of Government Affairs Liz Oesterle defined it as “getting more financial data in the system that is predicted, validated and can be disputed.” #DeathtoPasswords – could it be a reality? It’s no secret we live in a digital world where we are increasingly relying on apps and websites to manage our lives, but let’s throw out some numbers to quantify the shift. In 2013, the average U.S. consumer had 26 online accounts. By 2015, that number increased to 118 online accounts. By 2020, the average person will have 207 online accounts. When you think about this number, and the passwords associated with these accounts, it is clear a change needs to be made to managing our lives online. Experian Vice President David Britton addressed his session, introducing the concept of creating an “ultimate consumer identity profile,” where multi-source data will be brought together to identify someone. It’s coming, and all of us managing dozens of passwords can’t wait. “The Woz.” I guess you needed to be there, but let’s just say he was honest, opinionated and notes that while he loves tech, he loves it even more when it enables us to live in the “human world.” Too much wonderful content to share, but more to come tomorrow …
Although the average mortgage rate was more than 4% at the end of the first quarter*, Q1 mortgage originations were nearly $450 billion — a 5% increase over the $427 billion a year earlier. As prime homebuying season kicks off, lenders can stay ahead of the competition by using advanced analytics to target the right customers and increase profitability. Revamp your mortgage and HELOC acquisitions strategies>
Experian and Creative Strategies share survey results about Apple’s AirPods, Google Home, Amazon Echo and Echo Dot for consumer behavior with voice devices.
Sometimes life throws you a curve ball. The unexpected medical bill. The catastrophic car repair. The busted home appliance. It happens, and the killer is that consumers don’t always have the savings or resources to cover an additional cost. They must make a choice. Which bills do they pay? Which bills go to the pile? Suddenly, a consumer’s steady payment behavior changes, and in some cases they lose control of their ability to fulfill their obligations altogether. These shifts in payment patterns aren’t always reflected in consumer credit scores. At a single point in time, consumers may look identical. However, when analyzing their past payment behaviors, differences emerge. With these insights, lenders can now determine the appropriate risk or marketing decisions. In the example below, we see that based on the trade-level data, Consumer A and Consumer B have the same credit score and balance. But once we see their payment pattern within their trended data, we can clearly see Consumer A is paying well over the minimum payments due and has a demonstrated ability to pay. A closer look at Consumer B, on the other hand, reveals that the payment amount as compared to the minimum payment amount is decreasing over time. In fact, over the last three months only the minimum payment has been made. So while Consumer B may be well within the portfolio risk tolerance, they are trending down. This could indicate payment stress. With this knowledge, the lender could decide to hold off on offering Consumer B any new products until an improvement is seen in their payment pattern. Alternatively, Consumer A may be ripe for a new product offering. In another example, three consumers may appear identical when looking at their credit score and average monthly balance. But when you look at the trend of their historical bankcard balances as compared to their payments, you start to see very different behaviors. Consumer A is carrying their balances and only making the minimum payments. Consumer B is a hybrid of revolving and transacting, and Consumer C is paying off their balances each month. When we look at the total annual payments and their average percent of balance paid, we can see the biggest differences emerge. Having this deeper level of insight can assist lenders with determining which consumer is the best prospect for particular offerings. Consumer A would likely be most interested in a low- interest rate card, whereas Consumer C may be more interested in a rewards card. The combination of the credit score and trended data provides significant insight into predicting consumer credit behavior, ultimately leading to more profitable lending decisions across the customer lifecycle: Response – match the right offer with the right prospect to maximize response rates and improve campaign performance Risk – understand direction and velocity of payment performance to adequately manage risk exposure Retention – anticipate consumer preferences to build long-term loyalty All financial institutions can benefit from the value of trended data, whether you are a financial institution with significant analytical capabilities looking to develop custom models from the trended data or looking for proven pre-built solutions for immediate implementation.
Knowing where e-commerce fraud takes place matters We recently hosted a Webinar with Mike Gross, Risk Strategy Director at Experian and Julie Conroy, Research Director at Aite Research Group, looking at the current state of card-not-present fraud, and what to prepare for in the coming year. Our biannual analysis of fraud attacks, served as a backdrop for the trends we’ve been seeing. I wanted to share some observations from the Webinar. Of course, if you prefer to hear it firsthand, you can download the archive recording here. I’ll start with the current landscape of card-not-present fraud. Julie shared 5 key trends her firm has identified regarding e-commerce fraud: Rising account take-over fraud Loyalty points targeted Increasingly global transactions Frustrating false declines Increasingly mobile consumers One particularly interesting note that Julie made was regarding consumer frustration levels towards forgotten passwords. While consumers are more frustrated when they’re locked out of access to their banking accounts (makes sense, it’s their money), forgotten passwords are more detrimental to e-commerce retailers since consumers are likely to go to another site. This equates to a frustrated consumer, and lost revenue for the business. Next, Mike went through the findings from our 2016 e-commerce fraud attack analysis. Fraud attack rates show the attempted fraudulent e-commerce transactions against the population of overall e-commerce orders. Overall, e-commerce attack rates spiked 33% in 2016. The biggest trends we saw included: Increased EMV adoption is driving a shift from counterfeit to card-not-present fraud 2B breached records disclosed in 2016, more than 3x any previous year Consumers reporting credit card fraud jumped from 15% in 2015 to over 32% in 2016 Attackers shifting locations slightly and international orders rely on freight forwarders 10 states saw an increase of over 100% in fraudulent orders Over 70 of the top 100 riskiest postal codes were not in last year’s list So, what will 2017 bring? Be prepared for more attacks, more global rings, more losses for businesses, and the emergence of IoT fraud. Businesses need to anticipate an increase of fraud over time and to be prepared. The value of employing a multi-layered approach to fraud prevention especially when it comes to authenticating consumers to validate transactions cannot be understated. By looking at all the points of the customer journey, businesses can better protect themselves from fraud, while maintaining a good consumer experience. Most importantly, having the right fraud solution in place can help businesses prevent losses both in dollars and reputation.
The U.S. Senate declared April to be Financial Literacy Month back in 2004. Fast forward 13 years and one has to question if we’ve moved the needle on educating Americans about personal finance and money management. There is still no national standard or common curriculum to teach our kids the basics in schools, and only five states require high school students to take one semester of personal finance in order to graduate. I read an interesting stat years back that high school seniors spend more time shopping for their prom attire than they do researching financial education options for college. No wonder there is sticker shock post-graduation when those first student loan bills coming. The lack of investment shows. In a 2016 Mintel study, very few consumers gave themselves high grades for their knowledge of personal finance, and the situation was worse among women, with twice as many assigning themselves a “C” as an “A.” Having worked in the financial services industry for more than a decade, I can say with certainty I’m a bit of a personal finance geek. Learning about the latest products and economic shifts has been rolled into my job, and I’ve sadly seen the consequences of what happens to consumers when they make poor financial decisions. Slumping credit scores. Delinquent payments. Repossessed vehicles. Hard times. The good news? There are plenty of resources to help Americans learn. The challenge? Finding the right ways to capture mind share via the right mediums at the right time. There is obviously a benefit to the consumer to be more financially literate, but financial institutions benefit as well when consumers are money smart. Individuals who understand financial products and how they can use them to achieve their goals are more likely to purchase those products throughout their financial lives. So how can financial institutions help close the financial literacy gap? Make online education and resources readily available. Research shows more consumers would like to get information about finance through the use of online resources rather than seminars. This preference is likely due to the fact that online resources can be accessed on one’s own schedule and gives the user more control over the topics s/he wants to explore. Provide parents resources to launch smart money talks with their kids. Study after study reveals parents are one of the most powerful teachers in their kids’ lives – and this includes providing an education and modeling strong money management skills. Consider adding online education for kids – or partnering with a provider who has already built a money app for youngsters. Additionally, educate parents about when it might be time to help a child establish their first savings account. Advise them on ways to finance college. Talk about co-signing on vehicles. Explain the power of saving. Train up your next wave of customers and they will likely remain loyal to you. Offer one-on-one credit education sessions. A high-touch solution is sometimes the perfect opportunity to grow a customer in the right financial direction. Perhaps a low credit score prevents an individual from securing an ideal interest rate for an auto or home loan. Each person’s financial situation is different, and a one-on-one session with a trained agent can help them understand what is specifically contributing to their low score. With a few insights, a customer can determine if they need to pay down some debt, address a few late payments, or reduce their number of credit lines. Knowledge is power, and consumers will appreciate this service and personable touch. --- Lenders have a vested interest to close the financial literacy gap, and while they can’t solve for everything, they can certainly make a difference with some basic steps and investments. If nothing else, April seems like a perfect time to evaluate what you’re doing and what resolutions you can make for the year ahead. Just as every saved penny counts, so does every effort to educate Americans on manning their money more effectively.
Pay your bills on time, have cash set aside for emergencies, and invest your money for the future. These are the rules financial pros say people should follow if they want to build wealth. Straightforward advice, but for many people these milestones can seem out of reach. A recent financial literacy study by Mintel shows that many Americans are struggling with money management and lack confidence in their financial knowledge, with just 19 percent of respondents giving themselves an “A” grade on financial knowledge. The survey and other reports released recently shed light on how well Americans are handling their money. Here are some of the prevailing trends: Young people are struggling. The Mintel study revealed less than 30 percent of Americans have an emergency savings account that equals 3-6 months of household income. Of that total number, 19 percent of iGeneration has saved for a rainy day, followed by Millennials (20 percent), Gen Xers (28 percent), Baby Boomers (37 percent) and World War II/Swing Generation (40 percent). Not surprisingly, people who make more money save a bigger percentage of their pay. People in the bottom 90 percent of the income scale save close to none of their pay each year, while those in the top 10 percent save close to 15 percent. Most are not planning for the future. The majority of people are not doing everything they can to prepare for retirement, including meeting with a financial adviser to devise a plan, researching Social Security or even talking to friends or family about planning. Even more, 21 percent of Americans are “not at all confident” they will be able to reach their financial goals. Parents plan more than non-parents. People with children have many demands on their money, and as a result think ahead and follow budgets, contribute to retirement accounts and hire a financial adviser to help them create plans and budgets. Consumers who don’t have children don’t have as many competing demands, but aren’t as sensible about following a financial plan. In Mintel’s study, just 10 percent of non-parents have a written financial plan and 26 percent contribute regularly to a retirement account. Most people have a budget. Nearly one in three Americans prepare a detailed written or computerized household budget each month that tracks their income and expenses, but a large majority do not. Those with at least some college education, conservatives, Republicans, independents, and those making $75,000 a year or more are slightly more likely to prepare a detailed household budget than are their counterparts, according to Gallup. The good news is, the majority of Americans are open to more financial education. April—which is Financial Literacy Month—is a great time to look at education efforts for your customers. Financial literacy won’t change overnight, nor in a year. Yet initiatives taken in schools, workplaces, and in communities add up. What are you doing for your customers to build financial literacy?
Knowing a consumer’s credit information at a single point in time tells only part of the story. For the whole story, lenders need to assess a consumer’s credit behavior over time. Understanding how a consumer uses credit or pays back debt over several months can better position you to: Offer the right products and terms to increase response rates. Identify profitable customers. Avoid consumers with payment stress. Trended data adds needed color to the consumer’s credit story. And with the right analytics and systems, you can derive valuable insights on consumers. Trended data>
Newest technology doesn’t mean best when it comes to stopping fraud I recently attended the Merchant Risk Conference in Las Vegas, which brings together online merchants and industry vendors including payment service providers and fraud detection solution providers. The conference continues to grow year to year – similar to the fraud and risk challenges within the industry. In fact, we just released analysis, that we’ve seen fraud rates spike to 33% in the past year. This year, the exhibit hall was full of new names on the scene – evidence that there is a growing market for controlling risk and fraud in the e-commerce space. I heard from a few merchants at the conference that there were some “cool” new technologies out to help combat fraud. Things like machine learning, selfies and other two-factor authentication tools were all discussed as the latest in the fight against fraud. The problem is, many of these “cool” new technologies aren’t yet efficient enough at identifying and stopping fraud. Cool, yes. Effective, no. Sure, you can ask your customer to take a selfie and send it to you for facial recognition scanning. But, can you imagine your mother-in-law trying to manage this process? Machine Learning, while very promising, still has some room to grow in truly identifying fraud while minimizing the false positives. Many of these “anomaly detection” systems look for just that – anomalies. The problem is, we’re fighting motivated and creative fraudsters who are experts at avoiding detection and can beat anomaly detection. I do not doubt that you can stop fraud if you introduce some of these new technologies. The problem is, at what cost? The trick is stopping fraud with efficiency – to stop the fraud and not disrupt the customer experience. Companies, now more than ever, are competing based on customer experience. Adding any amount of friction to the buying process puts your revenue at risk. Consider these tips when evaluating and deploying fraud detection solutions for your online business. Evaluate solutions based on all metrics What is the fraud detection rate? What impact will it have on approvals? What is the false positive rate and impact on investigations? Does the attack rate decline after implementing the solution? Is the process detectable by fraudsters? What friction is introduced to the process? Use all available data at your disposal to make a decision Does the consumer exist? Can we validate the person’s identity? Is the web-session and user-entered data consistent with this consumer? Step up authentication but limit customer friction Is the technology appropriate for your audience (i.e. a selfie, text-messaging, document verification, etc...)? Are you using jargon in your process? In the end, any solution can stop 100% of the fraud – but at what cost. It’s a balance - a balance between detection and friction. Think about customer friction and the impact on customer satisfaction and revenue.
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