All posts by Guest Contributor

  There’s no shortage of headlines alluding to a student loan crisis. But is there a crisis brewing or is this just a headline grab? Let’s look at the data over the past 4 years to find out. Outstanding student loan (should be loan) debt grew 21%, reaching a high of $1.49 trillion in Q4 2016. Over the past 4 years, student loan trades grew 4%, with a slight decline from 2015 to 2016. Average balance per trade grew 17% to reach $8,210. Number of overall student loan trades per consumer is down 5% to just 3.85. The average person with a student loan balance had just over $32,000 outstanding at the end of 2016 — a rise of 15%. While we’re seeing some increases, the data tells us this is a media headline grab. If students are educated about the debt they’re acquiring and are confident they can repay it, student loan debt shouldn’t be a crippling burden. More student loan insights

Did you know that 80% of all data migrations fail? Like any large project, data migration relies heavily on many variables. Successful data migration depends on attention to detail, no matter how small. Here are 3 items essential to a successful data migration: Conduct a Pre-Migration Impact Assessment to identify the necessary people, processes and technology needed. Ensure accurate, high-quality data to better streamline the migration process and optimize system functionality. Assemble the right team, including an experienced leader and business users, to ensure timely and on-budget completion. 35% of organizations plan to migrate data this year.   If you’re among them, use this checklist to create the right plan, timeline, budget, and team for success.

We live in a digital world where online identities are ubiquitous. But with the internet’s inherent anonymity, how do you know you’re interacting with a legitimate individual rather than an imposter? Too often we hear stories about consumers who see unauthorized purchases on their credit cards, enable access to their devices based on an imposter claiming to be a security vendor or send money to someone they met online only to learn they’ve been “catfished” by a fraudster. These are growing problems, as more consumers transition to digital services and look to businesses to protect them, enable seamless trusted interactions and maintain their privacy. I recently chatted with MarketWatch about how consumers can protect themselves and their privacy when using online dating apps, as well as what businesses are doing to safeguard digital data. As part of the discussion, I mentioned that a simple, standard verification process companies of all sizes can leverage is vital to our rapidly evolving digital economy. Today, companies have their own policies, processes and definitions of identity verification, depending on the services they offer. This ranges from secure access requiring strong identity proofing, document verification, multifactor authentication and biometric enrollment to new social profiles that do little more than validate receipt of an email to establish an online account. To satisfy those diverse risk-based needs, more organizations are turning to federated identity verification options. A federated system allows businesses to leverage trusted, reputable, third-party sources to validate identity by cross-referencing the information they’ve received from a consumer against these sources to determine whether to establish an account or allow a transaction. While some organizations have attempted to develop similar identity verification capabilities, many lack a trusted identity source. For example, there are solutions that leverage data from social media accounts or provide multifactor fraud and authentication options, but they often become easily compromised because of the absence of verifiable data. A trusted solution aggregates data across multiple providers that have undergone thorough security and data quality vetting to ensure the identity data is accurately submitted in accordance with business and compliance requirements. In fact, there are only a handful of trusted identity sources with this level of due diligence and oversight. At Experian, we assess verification requests against an aggregate of hundreds of millions of records that include identity relationships, profile risk attributes, historical usage records and demographic data assets. With decades of knowledge about identity management and fraud prevention, we help companies of all sizes balance risk mitigation and maintain compliance requirements — all while ensuring consumer data privacy. Trust takes years to build and mere seconds to lose, and the industry has made undeniable progress in security. But there is much left to do. Consumers are increasingly involved in the protection and use of their data. However, they often don’t realize downloading a hot new app and entering personal details or linking to their friends exposes them to unnecessary risk. It’s important for businesses to be clear about their identity verification processes so consumers can make educated decisions before electing to provide invaluable identity data. The most effective fraud prevention and identity strategy is one that quickly establishes trust without inconveniencing the consumer. By staying up to date on verification methods, businesses can ensure customers have a smooth, personalized and engaging online experience.

  The economic expansion just passed the eight-year mark, and consumer credit defaults across mortgages, bankcards and auto loans are at pre–financial crisis levels. More specifically: The first-mortgage default rate dropped 4 basis points from May to 0.60%. The bankcard default rate experienced its first drop in 9 months, with a decrease of 4 basis points bringing it to 3.49%. Auto loan defaults decreased 3 basis points from the previous month to 0.82%. With inflation at 1% to 2%, debt service levels close to record lows, and disposable income increasing and supporting spending growth, consumers are in good financial shape nationally. Lenders should take this opportunity to review and adjust their acquisition strategies accordingly. Can your originations platform capitalize on this?

1 in 10 Americans are living paycheck to paycheck Financial health means more than just having a great credit score or money in a savings account. It includes being able to manage daily finances, save for the future and weather a financial shock. Here are some facts about Americans’ financial health: 46% of Americans are struggling financially. Roughly 31% of nonretired adults have no retirement savings or pension. Approximately 50% are unprepared for a financial emergency, and about 1 in 5 have no savings set aside to cover unexpected emergencies. It’s never too late for people to achieve financial health. By providing education on money management, you can drive new opportunities for increased engagement, loyalty and long-term revenue streams. Why financial health matters >

A combination of mass identity data compromise and the increasing abilities of organized fraud rings has created a synthetic identity epidemic that is impacting all markets. Here are the three ways that synthetic identities are generally created: Credit applications and inquiries that result in synthetic credit profile creation or build. Exploitation of the authorized user process designed to take over or piggyback on legitimate credit profiles. Data furnishing schemes that falsify regular credit reporting agency updates. When it comes to fighting synthetic fraud, we all need to be a part of the solution – or we are just a part of the problem. Mitigate synthetic identity fraud >

There’s a new crew coming of age. Enter Generation Z. Gen Z — those born between the mid-1990s and the early 2000s — makes up one-quarter of the U.S. population. By 2020, they’ll account for 40% of all consumers. The oldest members of this next cohort — 18- to 20-year-olds — are coming of age. Here are some insights on how this initial segment of Gen Z is beginning to use credit. Credit scores averaged 631 in 2016. Debt levels — consisting largely of bankcards and auto and student loans — are low, with an average debt-to-income ratio of just 5.7%. Average income is $33,800. This generation is being raised in an era of instant, always-on access. They expect a quick, seamless and customized mobile experience. You have just 8 seconds to capture their attention. Webinar: A First Look at Gen Z and Credit

The State of Credit Unions 2017 In the financial services universe, there is no shortage of players battling for consumer attention and share of wallet. Here’s a look at how one player — credit unions — has fared over the past two years compared to banks and online lenders: Personal loans grew 2%, but online lenders and finance companies still own 51% of this market. Card originations at credit unions increased 18%, with total credit limits on newly originated cards approaching $100 billion in Q1 2017. Mortgage market share rose 7% for credit unions, while banks lost share to online lenders. Auto originations increased 25% for credit unions to 1.93 million accounts in Q1 2017. Whether your organization is a credit union, a financial institution or an online lender, a “service first” mentality is essential for success in this highly competitive market. The State of Credit Unions 2017

Financial health means more than just having a great credit score or money in a savings account. Although those things are good indicators of financial well-being, personal finance experts believe that financial health means more: being able to manage daily finances, save for the future and weather a financial shock, such as a job loss. As we approach #FinHealthMatters Day on June 27—a day created to bring attention to the 46 percent of Americans who are struggling financially—let’s take a look at financial health trends of Americans. Young adults not actively saving for retirement: Roughly 31% of non-retired adults have no retirement savings or a pension, according to a survey by the Federal Reserve. Nearly half of 18- to 29-year-olds surveyed had no retirement savings or pension, and about 75% of non-retired people 45 and older had some savings. Still, about 14% of adults 60 or older who are not retired and employed had no retirement savings, according to the report. Managing daily finances a challenge for many: Living paycheck to paycheck is a reality for about 1 in 10 Americans (11%), who say they spend more on monthly expenses than their household income allows, according to a Harris Poll. Of those surveyed, about one-third (32%) say they just make ends meet. Most lack an emergency fund: About 50% of people are unprepared for a financial emergency. Nearly 1 in 5 (19%) Americans have no savings set aside to cover unexpected emergencies, while about 1 in 3 (31%) Americans don’t have $500 reserved for an unexpected emergency expense, according to a survey released by HomeServe USA, a home repair service. Renewed focus on personal savings: On a positive note, Americans are sharpening their focus on personal savings, with slight increases among those who say they are saving more than last year (26% in 2017 vs. 24% in 2016). And the portion of those contributing income toward non-retirement savings has returned to its 2013 level of 69%. The good news is it’s never too late for people to achieve financial health. To do so, they need guidance to develop financial routines that build long-term resilience and opportunity. Promoting financial health is good for the financial services industry, as financially healthy consumers drive new opportunities for increased engagement, loyalty, and long-term revenue streams. We invite you to join the conversation and contribute your support and ideas for a healthier future.

Mitigating synthetic identities Synthetic identity fraud is an epidemic that does more than negatively affect portfolio performance. It can hurt your reputation as a trusted organization. Here is our suggested 4-pronged approach that will help you mitigate this type of fraud: Identify how much you could lose or are losing today to synthetic fraud. Review and analyze your identity screening operational processes and procedures. Incorporate data, analytics and cutting-edge tools to enable fraud detection through consumer authentication. Analyze your portfolio data quality as reported to credit reporting agencies. Reduce synthetic identity fraud losses through a multi-layer methodology design that combats both the rise in synthetic identity creation and use in fraud schemes. Mitigating synthetic identity fraud>  

Call it big data, smart data or evidence-based decision-making. It’s not just the latest fad, it’s the future of how business will be guided and grow. Here are a few telling stats that show data is exploding and a new age is upon us: Data is growing faster than ever before, and we’re on track to create about 1.7 megabytes of new information per person every second by 2020. The social universe—which includes every digitally connected person—doubles in size every two years. By 2020, it will reach 44 zettabytes or 44 trillion gigabytes, according to CIO. In 2015, more than 1 billion people used Facebook and sent an average of 31.25 million messages and viewed 2.77 million videos each minute. More than 100 terabytes of data is uploaded daily to the social channel. By 2020, more than 6.1 billion smartphone users will exist globally. And there will be more than 50 billion smart connected devices in the world, all capable of collecting, analyzing and sharing a wealth of data. More than one-third of all data will pass through or exist in the cloud by 2020. The IDC estimates that by 2020, business transactions on the internet—business-to-business and business-to-consumer—will reach 450 billion per day. All of this new data means we’ll be looking at a whole new set of possibilities and a new level of complexity in the years ahead. The data itself is of great value, however, lenders need the right automated decisioning platform to store, collect, quickly process and analyze the volumes of consumer data to gain accurate consumer stories. While lenders don’t necessarily need to factor in decisioning on social media uploads and video views, there is an expectation for immediacy to know if a consumer is approved, denied or conditioned. Online lenders have figured out how to quickly capture and understand big data, and are expected to account for $122 billion in lending by 2020. This places more pressure on banks and credit unions to enhance their technology to cut down on loan approval times and move away from various manual touch points. Critics of automated decisioning solutions used in lending cite compliance issues, complacency by lenders and lack of human involvement. But a robust platform enables lenders to improve and supplement their current decisioning processes because it is: Agile: Experian hosts our client’s solutions and decisioning strategies, so we are able to make and deploy changes quickly as the needs of the market and business change, and deliver real-time instant decisions while a consumer is at the point of sale. A hosted environment also means reduced implementation timelines, as no software or hardware installation is required, allowing lenders to recognize value faster. A data work horse: Internal and external data can be pulled from multiple sources into a lender’s decisioning model. Lenders may also access an unlimited number of scores and attributes—including real-time access to credit bureau data—and integrate third-party data sources into the decisioning engine. Powerful: A robust decision engine is capable of calculating numerous predictive attributes and custom scoring models, and can also test new strategies against current decision models or perform “what if” simulations on historical data. Data collection, storage and analysis are here to stay. As will be the businesses which are savvy enough to use a solution that can find opportunities and learnings in all of that complex data, quickly curate the best possible actions to take for positive outcomes, and allow lenders and marketers to execute on those recommendations with the click of a button. To learn more about Experian’s decisioning solutions, you can additionally explore our PowerCurve and Attribute Toolbox solutions.

On June 7, the Consumer Financial Protection Bureau (CFPB) released a new study that found that the ways “credit invisible” consumers establish credit history can differ greatly based on their economic background. The CFPB estimated in its May 2015 study "Data Point: Credit Invisibles" that more than 45 million American consumers are credit invisible, meaning they either have a thin credit file that cannot be scored or no credit history at all. The new study reviewed de-identified credit records on more than one million consumers who became credit visible. It found that consumers in lower-income areas are 240 percent more likely to become credit visible due to negative information, such as a debt in collection. The CFPB noted consumers in higher-income areas become credit visible in a more positive way, with 30 percent more likely to become credit visible by using a credit card and 100 percent more likely to become credit visible by being added as a co-borrower or authorized user on someone else’s account. The study also found that the percentage of consumers transitioning to credit visibility due to student loans more than doubled in the last 10 years. CFPB’s research highlights the need for alternative credit data The new study demonstrates the importance of moving forward with inclusion of new sources of high-quality financial data — like on-time payment data from rent, utility and telecommunications providers — into a consumer’s credit file. Experian recently outlined our beliefs on the issue in comments responding to the CFPB’s Request for Information on Alternative Data. As a brand, we have a long history of using alternative credit data to help lenders make better lending decisions. Extensive research has shown that there is an immense opportunity to facilitate greater access to fair and affordable credit for underserved consumers through the inclusion of on-time telecommunications, utility and rental data in credit files. While these consumers may not have a traditional credit history, many make on-time payments for telephone, rent, cable, power or mobile services. However, this data is not typically being used to enhance traditional credit files held by the nationwide consumer reporting agencies, nor is it being used in most third-party or custom credit scoring models. Further, new advances in financial technology and data analytics through account aggregation platforms are also integral to the credit granting process and can be applied in a manner to broaden access to credit. Experian is currently using account aggregation software to obtain consumer financial account information for authentication and income verification to speed credit decisions, but we are looking to expand this technology to increase the collection and utilization of alternative data for improving credit decisions by lenders. Policymakers should act to help credit invisible consumers While Experian continues to work with telecommunications and utility companies to facilitate the furnishing of on-time credit data to the nationwide consumer reporting agencies, regulatory barriers continue to exist that deter utility and telecommunications companies from furnishing on-time payment data to credit bureaus. To help address this issue, Congress is currently considering bipartisan legislation (H.R. 435, The Credit Access and Inclusion Act of 2017) that would amend the FCRA to clarify that utility and telecommunication companies can report positive credit data, such as on-time payments, to the nation' s credit reporting bureaus. The legislation has bipartisan support in Congress and Experian encourages lawmakers to move forward with this important initiative that could benefit tens of millions of American consumers. In addition, Experian believes policymakers should more clearly define the term alternative data. In public policy debates, the term "alternative data" is a broad term, often lumping data sources that can or have been proven to meet regulatory standards for accuracy and fairness required by both the Fair Credit Reporting Act and the Equal Credit Opportunity Act with data sources that cannot or have not been proven to meet these standards. In our comment letter, Experian encourages policymakers to clearly differentiate between different types of alternative data and focus the consumer and commercial credit industry on public policy recommendations that will increase the use of those sources of data that have or can be shown to meet legal and societal standards for accuracy, validity, predictability and fairness. More info on Alternative Credit Data More Info on Alternative Financial Services

Summer spending A study by Experian and Edelman Berland noted that travelers relied heavily on credit for vacation purchases last year — with many planning to charge more than half of their vacation expenses this summer. Of those surveyed about their 2015 summer purchases: 86% spent money on a summer vacation in 2015. $2,275 was spent per person, with $1,308 of that being credit card purchases. 35% hadn’t saved in advance. 61% spent more than they planned. Summer brings vacations and credit card use. By identifying consumer credit trends like these, you can target new customers and identify balance transfer opportunities. Learn more>

Analyzing credit scores and card balances According to a study by VantageScore® Solutions LLC, consumers with credit scores between 601 and 650 carry the largest credit card bills, at more than $10,000 — nearly 2x that of the average consumer. Other key findings include: Those with the highest scores have the largest total credit limit ($46,735), compared with just $2,816 for those with the lowest scores. The average credit card holder has $29,197 in credit lines, with an average balance of $5,720. Those with scores between 701 and 750 use an average of 27% of their available credit versus 47% for those with scores between 651 and 700. The study reinforces the importance of staying current on the latest credit trends to best identify areas of opportunity and adjust lending strategies accordingly. Make better decisions >

The 1990s brought us a wealth of innovative technology, including the Blackberry, Windows 98, and Nintendo. As much as we loved those inventions, we moved on to enjoy better technology when it became available, and now have smartphones, Windows 10 and Xbox. Similarly, technological and modeling advances have been made in the credit scoring arena, with new software that brings significant benefits to lenders who use them. Later this year, FICO will retire its Score V1, making it mandatory for those lenders still using the old software to find another solution. Now is the time for lenders to take a look at their software and myriad reasons to move to a modern credit score solution. Portfolio Growth As many as 70 million Americans either have no credit score or a thin credit file. One-third of Millennials have never bothered to apply for a credit card, and the percentage of Americans under 35 with credit card debt is at its lowest level in more than 25 years, according to the Federal Reserve. A recent study found that Millennials use cash and debit cards much more than older Americans. Over time, Millennials without credit histories could struggle to get credit. Are there other data sets that provide a window into whether a thin file consumer is creditworthy or not? Modern credit scoring models are now being used in the marketplace without negatively impacting credit quality. For example, the VantageScore® credit score allows for the scoring of 30 million to 35 million more people consumers who are typically unscoreable by other traditional generic credit models. The VantageScore® credit score does this by using a broader, deeper set of credit file data and more advanced modeling techniques. This allows the VantageScore® credit score model to more accurately predict unique consumer behaviors—is the consumer paying his utility bill on time?—and better evaluate thin file consumers. Mitigate Risk In today’s ever-changing regulatory landscape, lenders can stay ahead of the curve by relying on innovative credit score models like the VantageScore® credit score. These models incorporate the best of both worlds by leaning on innovative scoring analytics that are more inclusive, while providing marketplace lenders with assurances the decisioning is both statistically sound and compliant with fair lending laws. Newer solutions also offer enhanced documentation to ease the burden associated with model risk management and regulatory compliance responsibilities. Updated scores Consumer credit scores can vary depending on the type of scoring model a lender uses. If it's an old, outdated version, a consumer might be scored lower. If it's a newer, more advanced model, the consumer has a better shot at being scored more fairly. Moving to a more advanced scoring model can help broaden the base of potential borrowers. By sticking to old models—and older scores—a sizable number of consumers are left at a disadvantage in the form of a higher interest rate, lower loan amount or even a declined application. Introducing advanced scoring models can provide a more accurate picture of a consumer. As an example, for many of the newest consumer risk models, like FICO Score 9, a consumer’s unpaid medical collection agency accounts will be assessed differently from unpaid non-medical collection agency accounts. This isn't true for most pre-2012 consumer risk score versions. Each version contains different nuances for increasing your score, and it’s important to understand what they are. Upgrading your credit score to the latest VantageScore® credit score or FICO solution is easier than you think, with a switch to a modern solution taking no longer than eight weeks and your current business processes still in place. Are you ready to reap the rewards of modern credit scoring?