Data & Analytics
A recent national survey by Experian revealed opportunities for businesses to build relationships with future homebuyers before they’re ready to obtain a loan. Insights include: 35% of future buyers said they don’t know what steps to take to qualify for a larger loan 75% of future buyers are not preapproved for a home loan 29% of those surveyed would purchase a more expensive home if they had better credit and could qualify for a larger loan A large portion of near-future homebuyers are millennials. Building relationships with this generation now will benefit financial institutions in the future. >> White paper: Building lasting relationships with millennials
Trend: a general direction in which something is developing or changing. Last Update: January 2019 As a lender, it’s important to understand a consumer’s credit behavior and whether it is improving or deteriorating over time. Sure, you can pull a credit score at any moment, but it is merely a snapshot. Knowing a consumer’s credit information at a single point in time only tells part of the story. Two consumers can have the same credit score, but one consumer’s score could be moving up while another’s could be moving down. In order to understand the whole story, lenders need the ability to leverage trended data to assess a consumer’s credit behavior over time. Experian’s Trended Data is comprised of five fields of historical payment information over a 24-month period. It includes: Balance Amount Original Loan / Limit Amount Scheduled Payment Amount Actual Payment Amount Last Payment Date By analyzing historical payment information, lenders can determine if a consumer is consistently paying more than the minimum payment, has a demonstrated ability to pay and shows no signs of payment stress. It can conversely identify if a consumer is making only minimum payments and has increasing payment stress. Knowing how a consumer uses credit, or pays back debt over time, can help lenders offer the right products and terms to increase response rates, determine up-sell and cross-sell opportunities, prevent attrition, identify profitable customers, avoid consumers with payment stress and limit loss exposure. Using a consumer’s historical payment information provides a more accurate assessment of future behavior, which in turn helps effectively manage changes in risk, predicts in-the-market timing or balance transfer activity, and provides additional insight for other lending strategies. There is a catch though. In order for lenders to extract the benefits of trended data, they need to be able to analyze an enormous amount of data. Five fields of data across 24 months on every trade is huge and can be difficult for lenders with limited analytical resources to manage. For example, a single consumer with 10 trades on file would have upwards of 1,200 data points to analyze. Multiply that by a file of 100,000 consumers and you are now dealing with over 120,000,000 data points. Additionally, if lenders utilize the trended data in their underwriting processing and intend to use it to decline consumers, they will need to create their own adverse action reason codes to communicate to the consumer. Not all lenders are equipped to take on this level of effort. Still, there are solutions to assist lenders with managing and unlocking the power of trended data. Experian’s pre-calculated solutions utilizing trended data allow even the smallest lenders to leverage the most cutting-edge solutions in near plug-and-play environments to quickly and effectively action on the benefits of trended data, minus the hassles of analyzing it. Trended data, and the solutions built from it, allow lenders to effectively predict where a consumer is going based on where they’ve been. And really, that can make all the difference when it comes to smart lending decisions. Get Started Today
What you give, you get. At least that is what popular philosophers claim. And if you think about it, this statement is also applicable to the world of data accuracy. As organizations of all sizes increasingly rely on data to interact with customers and create insights to drive strategy, it’s no secret bad data can quickly lead a company or financial institution down the wrong path, even landing them into regulatory troubles. A recent Experian Data Quality study found: Seventy-five percent of organizations believe inaccurate data is undermining their ability to provide an excellent customer experience. Sixty-five percent of organizations wait until there are specific issues with their data before they address and fix them. Fifty-six percent of organizations believe mistakes can be attributed to human error. For years, organizations have wanted good data simply for operational efficiencies and cost savings, but now a shift has taken place where businesses are using data for nearly every aspect of their organization. The majority of sales decisions are expected to be driven by customer data by 2020, with companies determined to turn data into actionable insight to find new customers, increase customer retention, better understand their needs, and increase the value of each customer. Additionally, the Fair Credit Reporting Act (FCRA) requires those contributing data to provide accurate and complete information to the credit reporting agencies. If they fail to meet accuracy obligations when reporting negative account histories to credit reporting companies, the result could be bureau action and fines. Organizations still deal with a high degree of inaccurate data because there are a number of challenges to maintaining it. Some of them are external forces, but many are internal challenges – most notably a reliance on reactive data management strategies. The biggest problem organizations face around data management today actually comes from within. Businesses get in their own way by refusing to create a culture around data and not prioritizing the proper funding and staffing for data management. Many businesses know they need to improve their data quality, but often have a hard time defining why an investment is needed in the current structure. Solutions exist to get in front of data accuracy challenges. DataArc 360 Powered by Experian Pandora, for example, is designed to check the consumer credit information provided by data furnishers prior to submission to credit bureaus. This allows data suppliers to take more of a proactive approach to ensuring the accuracy of information, that may result in fewer credit disputes and a more positive interaction between consumers and their credit. Creating a clear governance plan, and centralizing data management policies and policies can also clean up internal challenges and improve accuracy standards. The importance of data cannot be neglected, but again, the data has to be clean for it to matter. What you give is what you’ll get.
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, 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 the key issues impacting marketers today. 38% of marketers rank knowing customer needs, wants and attitudes as their top challenge. Other key challenges include: Increasing visibility over competitors (35%) Staying ahead of new marketing trends (33%) Integrating multiple marketing technologies and platforms (32%) Making messages relevant/contextual (27%) Companies can increase engagement by leveraging data and technology to understand customers and provide exceptional experiences through every channel, every time. >> Download The 2016 Digital Marketer Report
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.
What is blockchain? Blockchain is beginning to get a lot of attention, so I thought it might be time to figure out what it is and what it means. Basically, a blockchain is a permissionless, distributed database that maintains a growing list of records (transactions) in a linear, chronological (and time-stamped) ledger. At a high level, this is how it works. Each computer connected to the network gets a copy of the entire blockchain and performs the task of validating and relaying transactions for the whole chain. The batches of valid transactions added to the record are called “blocks.” A block is the “current” part of a blockchain that records some or all of the recent transactions and once completed goes into the blockchain as a permanent database. Each time a block gets completed, a new block is created, with every block containing a hash of the previous block. There are countless numbers of blocks in the blockchain. To use a conventional banking analogy, the blocks would be a full history of every banking transaction for every person, and the blockchain would be a complete banking history. The entire blockchain is sent to everyone who has access, and every user validates the information in the block. It’s like if Tom, Bob and Harry were standing on the street corner and saw a cyclist hit by a car. Individually, all three men will be asked if the cyclist was struck by the car, and all three will respond “yes.” The cyclist being hit by the car becomes part of the blockchain, and that fact cannot be altered. Blockchain generally is used in the context of bitcoin, where similar uses of the structure are called altchains. Why should I care or, at the very least, pay attention to this movement? Because the idea of it is inching toward the tipping point of mainstream. I recently read an article that identified some blockchain trends that could shape the industry in coming months. The ones I found most interesting were: Blockchain apps will be released Interest in use cases outside payments will pick up Consortia will prove to be important Venture capital money will flow to blockchain start-ups While it’s true that much of the hype around blockchain is coming from people with a vested interest, it is beginning to generate more generalized market buzz as its proponents emphasize how it can reduce risk, improve efficiency and ultimately provide better customer service. Let’s face it, the ability to maintain secure, fast and accurate calculations could revolutionize the banking and investment industries, as well as ecommerce. In fact, 11 major banks recently completed a private blockchain test, exchanging multiple tokens among offices in North America, Europe and Asia over five days. (You can read The Wall Street Journal article here.) As more transactions and data are stored in blockchain or altchain, greater possibilities open up. It’s these possibilities that have several tech companies, like IBM, as well as financial institutions creating what has become known as an open ledger initiative to use the blockchain model in the development of new technologies that will enable a wider array of services. There is no doubt that the concept is intriguing — so much so that even the SEC has approved a plan to issue stock via blockchain. (You can read the Wired article here.) The potential is enough to make many folks giddy. The idea that risk could become a thing of the past because of the blockchain’s immutable historical record — wow. It’s good to be aware and keep an eye on the open ledger initiative, but let’s not forget history, which has taught us that (in the wise words of Craig Newmark), “Crooks are early adopters.” Since blockchain’s original and primary usage has been with bitcoin, I don’t think it is unfair to say that there will be some perceptions to overcome — like the association of bitcoin to activities on the Dark Web such as money laundering, drug-related transactions and funding illegal activities. Until we start to see the application across mainstream use cases, we won’t know how secure blockchain is or how open business and consumers will be to embracing it. In the meantime, remind me again, how long has it taken to get to a point of practical application and more widespread use of biometrics? To learn more, click here to read the original article.
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.
With the holidays around the corner, retailers are getting ready to release their holiday campaigns.
While mobile subscriber lists typically are much smaller than email lists, mobile subscribers tend to be loyal and highly engaged customers.
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