Data & Analytics

For lenders to capitalize and identify the right consumers for their respective portfolios, they need insights. Trade level fields can bridge the gap.

Experian defines how businesses should approach Identity Relationship Management for user authentication and devices to enable better fraud protection.

Experian estimates card-to-card consumer balance transfer activity to be between $35 and $40 billion a year, representing a sizeable opportunity for proactive lenders seeking to grow their revolving product line. This opportunity, however, is a threat for reactive lenders that only measure portfolio attrition instead of working to retain current customers. While billions of dollars are transferred every year, this activity represents only a small percentage of the total card population. And given the expense of direct marketing, lenders seeking to capitalize on and protect their portfolio from balance transfer activity must leverage data insights to make more informed decisions. Predicting a consumer’s future propensity to engage in card-to-card balance transfers starts with trended data. A credit score is a snapshot in time, but doesn’t reveal deep insights about a consumer’s past balance transfer activity. Lenders that rely only on current utilization will group large populations of balance revolvers into one bucket – and many of these individuals will have no intention of transferring to another product in the near future. Still, balance transfer activity can be identified and predicted by utilizing trended data. By analyzing the spend and payment data over time to see when one (or multiple) trade’s payment approximately matches another trade’s spend, we have the logic that suggests there has been a card-to-card transfer. What most people don’t realize is that trended data is difficult to work with. With 24 months of history on five fields, a single trade includes 120 data points. That’s 720 data points for a consumer with six trades on file and 72,000,000 for a file with 100,000 records, not to mention the other data fields in the file. It’s easy to see why even the most sophisticated organizations become paralyzed working with trended data. While teams of analysts get buried in the data, projects drag, costs swell, and eventually the world changes as rates climb and fall. By the time the analysis is complete, it must be recalibrated. But there is a solution. Experian has developed powerful predictions tools that combine past balance transfer history, historical transfer amounts, current trades carried and utilized, payments, and spend. Combined, these data fields can help identify consumers who are most likely to transfer a balance in the future. With Experian’s Balance Transfer Index the highest scoring 10 percent of consumers capture nearly 70 percent of total balance transfer dollars. Imagine the impact on ROI of reducing 90 percent of the marketing cost of your next balance transfer campaign and still reaching 70 percent of the balance transfer activity. Balance transfer activity represents a meaningful dollar opportunity for growth, but is concentrated in a small percentage of the population making predictive analytics key to success. Trended data is essential for identifying those opportunities, but financial institutions must assess their capabilities when it comes to managing the massive data attached. The good news is that regardless of financial institution size, solutions now exist to capture the analytics and provide meaningful and actionable insights to lenders of all sizes.

Recent survey by Experian revealed opportunities for businesses to build relationships with future homebuyers before they’re ready to obtain a loan.

While organizations increasingly rely on data to make decisions, when it comes to data accuracy, too many wait to correct errors rather than implement proactive solutions.

James W. Paulsen, Chief Investment Strategist for Wells Capital Management, kicked off the second day of Experian’s Vision 2016, sharing his perspective on the state of the economy and what the future holds for consumers and businesses alike. Paulsen joked this has been “the most successful, disappointing recovery we’ve ever had.” While media and lenders project fear for a coming recession, Paulsen stated it is important to note we are in the 8th year of recovery in the U.S., the third longest in U.S. history, with all signs pointing to this recovery extending for years to come. Based on his indicators – leverage, restored household strength, housing, capital spending and better global growth – there is still capacity to grow. He places recession risk at 20 to 25 percent – and only quotes those numbers due the length of the recovery thus far. “What is the fascination with crisis policies when there is no crisis,” asks Paulsen. “I think we have a good chance of being in the longest recovery in U.S. history.” Other noteworthy topics of the day: Fraud prevention Fraud prevention continues to be a hot topic at this year’s conference. Whether it’s looking at current fraud challenges, such as call-center fraud, or looking to future-proof an organization’s fraud prevention techniques, the need for flexible and innovative strategies is clear. With fraudsters being quick, and regularly ahead of the technology fighting them, the need to easily implement new tools is fundamental for you to protect your businesses and customers. More on Regulatory The Military Lending Act has been enhanced over the past year to strengthen protections for military consumers, and lenders must be ready to meet updated regulations by fall 2016. With 1.46 million active personnel in the U.S., all lenders are working to update processes and documentation associated with how they serve this audience. Alternative Data What is it? How can it be used? And most importantly, can this data predict a consumer’s credit worthiness? Experian is an advocate for getting more entities to report different types of credit data including utility payments, mobile phone data, rental payments and cable payments. Additionally, alternative data can be sourced from prepaid data, liquid assets, full file public records, DDA data, bill payment, check cashing, education data, payroll data and subscription data. Collectively, lenders desire to assess someone’s stability, ability to pay and willingness to repay. If alternative data can answer those questions, it should be considered in order to score more of the U.S. population. Financial Health The Center for Financial Services Innovation revealed insights into the state of American’s financial health. According to a study they conducted, 57 percent of Americans are not financially healthy, which equates to about 138 million people. As they continue to place more metrics around defining financial health, the center has landed on four components: how people plan, spend, save and borrow. And if you think income is a primary factor, think again. One-third of Americans making more than $60k a year are not healthy, while one-third making less than $60k a year are healthy. --- Final Vision 2016 breakouts, as well as a keynote from entertainer Jay Leno, will be delivered on Wednesday.

It’s impossible to capture all of the insights and learnings of 36 breakout sessions and several keynote addresses in one post, but let’s summarize a few of the highlights from the first day of Vision 2016. 1. Who better to speak about the state of our country, specifically some of the threats we are facing than Leon Panetta, former Secretary of Defense and Director of the CIA. While we are at a critical crossroads in the United States, there is room for optimism and his hope that we can be an America in Renaissance. 2. Alex Lintner, Experian President of Consumer Information Services, conveyed how the consumer world has evolved, in large part due to technology: 67 percent of consumers made purchases across multiple channels in the last six months. More than 88M U.S. consumers use their smartphone to do some form of banking. 68 percent of Millennials believe within five years the way we access money will be totally different. 3. Peter Renton of Lend Academy spoke on the future of Online Marketplace Lending, revealing: Banks are recognizing that this industry provides them with a great opportunity and many are partnering with Online Marketplace Lenders to enter the space. Millennials are not the largest consumers in this space today, but they will be in the future. Sustained growth will be key for this industry. The largest platforms have everything they need in place to endure – even through an economic downturn.In other words, Online Marketplace Lenders are here to stay. 4. Tom King, Experian’s Chief Information Security Officer, addressed the crowds on how the world of information security is growing increasingly complex. There are 1.9 million records compromised every day, and sadly that number is expected to rise. What can businesses do?  “We need to make it easier to make the bad guys go somewhere else,” says King. 5. Look at how the housing market has changed from just a few years ago: Inventory continues to be extraordinarily lean. Why? New home building continues to run at recession levels. And, 8.5 percent of homeowners are still underwater on their mortgage, preventing them from placing it on the market. In the world of single-family home originations, 2016 projections show that there will be more purchases, less refinancing and less volume. We may see further growth in HELOC’s. With a dwindling number of mortgages benefiting from refinancing, and with rising interest rates, a HELOC may potentially be the cheapest and easiest way to tap equity. 6. As organizations balance business needs with increasing fraud threats, the important thing to remember is that the customer experience will trump everything else. Top fraud threats in 2015 included: Card Not Present (CNP) First Party Fraud/Synthetic ID Application Fraud Mobile Payment/Deposit Fraud Cross-Channel FraudSo what do the experts believe is essential to fraud prevention in the future? Big Data with smart analytics. 7. The need for Identity Relationship Management can be seen by the dichotomy of “99 percent of companies think having a clear picture of their customers is important for their business; yet only 24 percent actually think they achieve this ideal.” Connecting identities throughout the customer lifecycle is critical to bridging this gap. 8. New technologies continue to bring new challenges to fraud prevention. We’ve seen that post-EMV fraud is moving “upstream” as fraudsters: Apply for new credit cards using stolen ID’s. Provision stolen cards into mobile wallet. Gain access to accounts to make purchases.Then, fraudsters are open to use these new cards everywhere. 9. Several speakers addressed the ever-changing regulatory environment. The Telephone Consumer Protection Act (TCPA) litigation is up 30 percent since the last year. Regulators are increasingly taking notice of Online Marketplace Lenders. It’s critical to consider regulatory requirements when building risk models and implementing business policies. 10. Hispanics and Millennials are a force to be reckoned with, so pay attention: Millennials will be 81 million strong by 2036, and Hispanics are projected to be 133 million strong by 2050. Significant factors for home purchase likelihood for both groups include VantageScore® credit score, age, student debt, credit card debt, auto loans, income, marital status and housing prices. More great insights from Vision coming your way tomorrow!          

Experian’s 2016 Digital Marketer Report reveals digital marketing trends and the key issues impacting marketers today.

Identity management traditionally has been made up of creating rigid verification processes that are applied to any access scenario. But the market is evolving and requiring an enhanced Identity Relationship Management strategy and framework. Simply knowing who a person is at one point in time is not enough. The need exists to identify risks associated with the entire identity profile, including devices, and the context in which consumers interact with businesses, as well as to manage those risks throughout the consumer journey. The reasoning for this evolution in identity management is threefold: size and scope, flexible credentialing and adaptable verification. First, deploying a heavy identity and credentialing process across all access scenarios is unnecessarily costly for an organization. While stringent verification is necessary to protect highly sensitive information, it may not be cost-effective to protect less-valuable data with the same means. A user shouldn’t have to go through an extensive and, in some cases, invasive form of identity verification just to access basic information. Second, high-friction verification processes can impede users from accessing services. Consumers do not want to consistently answer multiple, intrusive questions in order to access basic information. Similarly, asking for personal information that already may have been compromised elsewhere limits the effectiveness of the process and the perceived strength in the protection. Finally, an inflexible verification process for all users will detract from a successful customer relationship. It is imperative to evolve your security interactions as confidence and routines are built. Otherwise, you risk severing trust and making your organization appear detached from consumer needs and preferences. This can be used across all types of organizations — from government agencies and online retailers to financial institutions. Identity Relationship Management has three unique functions delivered across the Customer Life Cycle: Identity proofing Authentication Identity management Join me at Vision 2016 for a deeper analysis of Identity Relationship Management and how clients can benefit from these new capabilities to manage risk throughout the Customer Life Cycle. I look forward to seeing you there!

Every portfolio has a set of delinquent customers who do not make their payments on time. Truth. Every lender wants to collect on those payments. Truth. But will you really ever be able to recover all of those delinquent funds? Sadly, no. Still, financial institutions often treat all delinquent customers equally, working the account the same and assuming eventually they’ll get their funds. The sentiment to recover is good, but a lot of collection resources are wasted on customers who are difficult or impossible to recover. The good news? There is a better way. Predictive analytics can help optimize the allocation of collection resources by identifying the most effective accounts to prioritize to your best collectors, do not contact and proceed to legal actions to significantly increase the recovery of dollars, and at the same time reduce collection costs. I had the opportunity to recently present at the annual Debt Buyer Association’s International Conference and chat with my peers about this very topic. We asked the room, “How many of you are using scoring to determine how to work your collection accounts?” The response was 50/50, revealing many of these well-intentioned collectors are working themselves too hard, and likely not getting the desired returns. Before you dive into your collections work, you need to respond to two questions: Which accounts am I going to work first? How am I going to work those accounts? This is where scoring enters the scene. A scoring model is a statistical algorithm that assigns a numerical expression based on known information to predict an unknown future outcome. You can then use segmentation to group individuals with others that show the same behavior characteristics and rank order groups for collection strategies. In short, you allow the score to dictate the collection efforts and slope your expenses based on the propensity and expected amount of the consumer to pay. This will inform you on: What type, if any, skip trace tactic you should use? If you should purchase additional data? What intensity you should work the account? With scoring, you will see different performances on different debts. If you have 100 accounts you are collecting on, you’ll then want to find the accounts where you will have the greatest likelihood to collect, and collect the most dollars. I like to say, “You can’t get blood from a stone.” Well the same holds true for certain accounts in your collections pile. Try all you like, but you’ll never recoup those dollars, or the dollars you do recoup will be minimal. With a scoring strategy, you can establish your “hit list” and find the most attractive accounts to collect on, and also match your most profitable accounts with your best collectors. My message to anyone managing a collections portfolio can be summed up in three key messages. You need to use scoring in your business to optimize resources and increase profits. The better data that goes into your model will net you better performance results. Get a compliance infrastructure in place so you can ensure you are collecting the right way and stay out of trouble. The beauty of scores is they tell you what to do. It will help you best match resources to the most profitable accounts, and work smarter, not harder. That’s the power of scoring.

Basically, a blockchain is a permissionless, distributed database that maintains a growing list of records in a linear, chronological ledger.

Who will take the coveted Super Bowl title in 2016? Now that we’re down to the final two teams, the commentary will heighten. Sportscasters, analysts, former athletes, co-workers ... even your local barista has an opinion. Will it be Peyton Manning's Denver Broncos or the rising Carolina Panthers? Millions will make predictions in the coming weeks, but a little research can go a long way in delivering meaningful insights. How have the teams been trending over the season? Are there injuries? Who is favored and what’s the spread? Which quarterback is leading in pass completions, passing yards, touchdowns, etc.? Who has been on this stage before, ready to embrace the spotlight and epic media frenzy? The world of sports is filled with stats resulting from historical data. And when you think about it, the world of credit could be treated similarly. Over the past several years, there has been much hype about “credit invisibles” and the need to “score more.” A traditional pull will likely leave many “no-file” and “thin-file” consumers out, so it’s in a lender’s best interest to leverage alternative scoring models to uncover more. But it’s also important to remember a score is just a snapshot, a mere moment in time. How did a consumer arrive to that particular score pulled on any given day? Has their score been trending up or down? Has an individual been paying off debt at a rapid pace or slipping further behind?   Two individuals could have the exact same score, but likely arrived to that place differently. The backstory is good to know – in sports and in the world of credit. Trended data can be attached to balances, credit limits, minimum payment due, actual payment and date of payment. By assessing these areas on a consumer file for 24 months, more insights are delivered and lenders can take note of behavior patterns to assist with risk assessment, marketing and share-of-wallet analysis. For example, looking closer at those consumers with five trades or more, Experian trended data reveals: 27% are revolvers, carrying balances each month 27% are transactors, paying off large portions, or all of their balances 9% are rate surfers, who tend to frequently transfer balances to credit cards with 0% or low introductory rates. Now these consumers can be viewed beyond a score. Suddenly, lenders can look within or outside their portfolio to understand how consumers use credit, what to offer them, and assess overall profitability. In short, trended data provides a more detailed view of a borrower’s historical credit performance, and that richness makes for a more informed decision. Without a doubt, there is power in the score – and being able to score more – but when it comes time to place your bets, the trended data matters, adding a whole new dimension to an individual’s credit score. Place your wagers accordingly. As for who will win Super Bowl 2016? I haven’t a clue. I’m more into the commercials. And I hear Coldplay is on for the half-time show. If you’re betting, best of luck, and do your homework.

For marketers, the start of a new year is an opportunity to look ahead.

With Black Friday quickly approaching, a recent Experian study shows online Black Friday searches are already tracking ahead of last year. This October, the weekly search share for Black Friday averaged 12% higher than October 2014 and is expected to increase dramatically between now and Thanksgiving week. Top product searches for the week ending October 31, 2015 include: Marketers can design more successful campaigns and maximize rewards for both consumers and brands by staying on top of the latest search trends. >> Holiday Hot Sheet

While marketers typically begin deploying Halloween emails in September, last-minute mailings receive the highest response.