Financial Services
The early stages of establishing a startup are some of the most difficult. In fact, it is said 90 percent of startups fail. Challenges include forming the right team, raising capital, and constructing a business model. But no one will deny that one of the most important parts of a startup’s business strategy is the data and technology that underpin its solution. On the one hand, new startups don’t benefit from a wealth of historic data on their clients, prospects, and partners like their more established competitors. While this isn’t the end of the world, it does emphasize the importance of finding a trusted data partner to build those data insights into the design for their application or platform. By using a trusted third-party data provider, companies can ensure they receive reliable and accurate data to utilize in their products and services. On the other hand, startups have the luxury of not being bogged down and burdened by legacy systems and older tech. While building a solution from the ground up is never an easy feat, startups can generally move faster. They can benefit from the latest technology to build new apps and products, making them nimbler than the incumbents in the space. Cloud technology enables organizations to quickly get their business up and running. In addition, companies are exposing many of their data assets and services through application programming interfaces (APIs), allowing others to more easily create their own solutions. Rather than reinventing the wheel, companies can leverage existing services to build more complex solutions and launch faster. “We’ve talked to countless startups and businesses and know they want easy, fast, and secure access to our data assets and services,” said Alpa Jain, vice president of Experian’s API Center of Excellence. “That’s why we’ve launched our API Developer Portal.” The list of APIs available through Experian’s Developer Portal includes solutions like consumer credit data, commercial credit data, commercial public record information, data quality, vehicle history information, and more. Companies can browse the list of available APIs, create an account, and start utilizing the APIs for building out a product within minutes. “Our goal is to help companies unlock untapped market opportunities and grow,” said Jain. “Success with APIs requires a successful developer program and portal to accelerate developer productivity – we believe we’ve created both with our new portal experience.\"
An introduction to the different types of validation samples Model validation is an essential step in evaluating and verifying a model’s performance during development before finalizing the design and proceeding with implementation. More specifically, during a predictive model’s development, the objective of a model validation is to measure the model’s accuracy in predicting the expected outcome. For a credit risk model, this may be predicting the likelihood of good or bad payment behavior, depending on the predefined outcome. Two general types of data samples can be used to complete a model validation. The first is known as the in-time, or holdout, validation sample and the second is known as the out-of-time validation sample. So, what’s the difference between an in-time and an out-of-time validation sample? An in-time validation sample sets aside part of the total sample made available for the model development. Random partitioning of the total sample is completed upfront, generally separating the data into a portion used for development and the remaining portion used for validation. For instance, the data may be randomly split, with 70 percent used for development and the other 30 percent used for validation. Other common data subset schemes include an 80/20, a 60/40 or even a 50/50 partitioning of the data, depending on the quantity of records available within each segment of your performance definition. Before selecting a data subset scheme to be used for model development, you should evaluate the number of records available in your target performance group, such as number of bad accounts. If you have too few records in your target performance group, a 50/50 split can leave you with insufficient performance data for use during model development. A separate blog post will present a few common options for creating alternative validation samples through a technique known as resampling. Once the data has been partitioned, the model is created using the development sample. The model is then applied to the holdout validation sample to determine the model’s predictive accuracy on data that wasn’t used to develop the model. The model’s predictive strength and accuracy can be measured in various ways by comparing the known and predefined performance outcome to the model’s predicted performance outcome. The out-of-time validation sample contains data from an entirely different time period or customer campaign than what was used for model development. Validating model performance on a different time period is beneficial to further evaluate the model’s robustness. Selecting a data sample from a more recent time period having a fully mature set of performance data allows the modeler to evaluate model performance on a data set that may more closely align with the current environment in which the model will be used. In this case, a more recent time period can be used to establish expectations and set baseline parameters for model performance, such as population stability indices and performance monitoring. Learn more about how Experian Decision Analytics can help you with your custom model development needs.
Consumers and businesses alike have been hyper-focused on all things data over the past several months. From the headlines surrounding social media privacy, to the flurry of spring emails we’ve all received from numerous brands due to the recent General Data Protection Regulation (GDPR) going into effect in Europe, many are trying to assess the data “sweet spot.” In the financial services space, lenders and businesses are increasingly seeking to leverage enhanced digital marketing channels and methods to deliver offers and invitations to apply. But again, many want to know, what are the data rules and how can they ensure they are playing it safe in such a highly regulated environment. In an Experian-hosted webinar, Credit Marketing in the Digital Age, the company recently featured a team of attorneys from Venable LLP’s award-winning privacy and advertising practice. There’s no question today’s consumers expect hyper-targeted messages and user experiences, but with the number of data breaches on the rise, there is also the concern around data access. Who has my data? Is it safe? Are companies using it in the appropriate way? As financial services companies wrestle with the laws and consumer expectations, the Venable legal team provided a few insights to consider. While the digital delivery channels may be new, the underlying credit product remains the same. A prescreened offer is a prescreened offer, and an application for credit is still an application for credit. The marketing of these and other credit products is governed by an array of pre-existing laws, regulations, and self-regulatory principles that combine to form a unique compliance framework for each of the marketing channels. Adhere to credit regulations, but build in enhanced policies and technological protocols with digital delivery. With digital delivery of the offer, lenders should be thinking about the additional compliance aspects attached to those varying formats. For example, in the case of digital display advertising, you should pay close attention to ensuring delivery of the ad to the correct consumer, with suitable protections in place for sharing data with vendors. Lenders and service providers also should think about using authentication measures to match the correct consumer with a landing page containing the firm offer along with the appropriate disclosures and opt-outs. Strong compliance policies are important for all participants in this process. Working with a trusted vendor that has a commitment to data security, compliance by design, and one that maintains an integrated system of decisioning and delivery, with the ability to scrub for FCRA opt-outs, is essential. Consult your legal, risk and compliance teams. The digital channels raise questions that can and must be addressed by these expert audiences. It is so important to partner with service providers that have thought this through and can demonstrate a compliance framework. Embrace the multitude of delivery methods. Yes, there are additional considerations to think about to ensure compliance, but businesses should seek opportunities to reach their consumers via email, text, digital display and beyond. Also, digital credit offers need not replace mail and phone and traditional channels. Rather, emerging digital channels can supplement a campaign to drive the response rates higher. In Mary Meeker’s annual tech industry report, she touched on a phenomenon called the “privacy paradox” in which companies must balance the need to personalize their products and services, but at the same time remain in good favor with consumers, watchdog groups and regulators. So, while financial services players have much to consider in the regulatory space, the expectation is they embrace the latest technology advancements to interact with their consumers. It can be done and the delivery methods exist today. Just ensure you are working with the right partners to respect the data and consumer privacy laws.
With delinquencies on the rise, financial institutions are looking for new tools to evaluate and improve the financial lives of customers and members. As the consumer’s bureau, Experian is also committed to improving the financial well-being of consumers. As part of that commitment, Experian supports the mission of the Center for Financial Services Innovation (CFSI), an organization focused on improving the financial health of Americans, especially the underserved, through innovative financial products and services. Experian recently spoke with CFSI’s Thea Garon, a Director on CFSI’s Program Team to learn more about a new free, open-source tool the organization will be launching in June to help financial institutions drive consumer financial health. Here are some insights she shared about the new tool. Can you provide an overview of the CFSI Financial Health Score™ and how it is calculated? The CFSI Financial Health Score™ is designed to help financial service providers, employers, and other organizations diagnose and measure the financial health of their customers, clients, and employees. The framework provides a holistic, moment-in-time snapshot of an individual’s financial health based on eight multiple-choice questions that align with CFSI’s eight indicators of financial health. It includes one Financial Health Score and four sub-scores (Spend, Save, Borrow, and Plan). A set of nationally representative benchmarks offers comparisons across peer groups. CFSI has designed the framework to be free, open-source, simple, and easy-to-use. It’s intended to be a starting point; a proof point that financial health can be quantified, measured, and ultimately improved. Why did CFSI decide to develop this framework? At CFSI, we believe, and have recently released research to support the concept that financial institutions have a business incentive to help their customers lead financially healthy lives. Financial health comes about when your daily financial systems allow you to be resilient and pursue opportunities over time. As a financial service provider, you can help your customers lead financially healthy lives by helping them spend wisely, build savings, borrow responsibly, and plan for the future. To do this, you need a measurement framework to understand and track your customers’ financial health over time. The CFSI Financial Health Score™ is one way to do this. You can use the methodology to diagnose your customers’ financial needs and use these insights to develop products, programs, and solutions to help them improve their financial health over time. You can also share financial health scores directly with your customers to help them understand the actions they can take to improve their own financial health. Ongoing tracking will allow you to assess whether your company is making a meaningful difference in your customers’ lives over time. Can you provide any early examples of how CFSI Health Network members have adopted and incorporated this framework? Approximately 100 financial service providers have downloaded the framework, representing a diverse range of companies, including banks, credit unions, fintechs, non-profits, payment networks, and B2B technology providers. At least 14 companies are actively using the Financial Health Score to measure and track their customers’ financial health and have committed to sharing data and insights with us through CFSI’s Financial Health Leaders program. Some companies, are using the framework to assess their customers’ financial health for strategic planning purposes. Other companies, such as Wright-Patt Credit Union, are using the financial health score to engage their customers in a dialogue about financial health. The credit union has incorporated the framework into their MoneyMagnifier program, a financial coaching program designed to provide free, one-on-one advice and guidance to members in a judgment-free environment. Financial coaches have been trained to use the framework to start a conversation with members to help them improve their spending, saving, borrowing, and planning behaviors. Coaches help members set goals and develop personalized action plans to achieve those goals toward a better financial future, following up with them after six months to measure improvement and advance the conversation. What have you learned from companies who have started measuring and improving their customers’ financial health with the CFSI Financial Health Score™? While interest in advice is high, uptake can be slow. Making the interaction quick and easy, whether online or in person, is critical. The health check lengthens the interaction, so conducting the health check by appointment rather than with walk-in customers, can help set customer expectations for a lengthier interaction, but may reduce the number of potential participants. Enabling customers to expedite the session by taking the survey online can be helpful, but requires development resources to implement. Many companies are exploring the pros and cons of sharing customers’ scores with them. A single score can help motivate individuals to take action that will improve their financial well-being. However, sharing a low score can also be demoralizing to some, and focusing on the number itself can divert attention from behavioral changes and action steps. Some organizations are choosing to use customers’ response patterns to drive recommendations without sharing the score. Others are opting for a middle ground, sharing an indicator (such as green, yellow, red) instead of a specific number. The most effective measurement and improvement strategies go beyond the CFSI Financial Health Score™. While the framework can help you get started identifying high-level needs, targeted recommendations often require a more nuanced understanding of behaviors and challenges. Combining survey data with account or transaction data can provide a more holistic view into a customer’s full financial life. Each organization must find a balance between the comprehensiveness required to provide meaningful advice and the simplicity required to engage both customers and staff. How can interested companies start using the CFSI Financial Health Score™? We will be publicly releasing the CFSI Financial Health Score™ at the EMERGE: Financial Health Forum (June 6 -8 in Los Angeles). The score will be easy to download and completely free to use. Those who are interested in learning more can also sign up for our newsletter to get an update when the Toolkit is released.
The second full day of Experian Vision 2018 kicked off with an inspirational message from keynote speakers Capt. Mark Kelly and Former Congresswomen Gabby Giffords, rolled into a series of diverse breakout sessions, and concluded with Super Bowl-winning quarterback Aaron Rodgers sharing tales of sports, leadership and winning. Need a recap of some of the headlines from the day? Here you go ... Retail Apocalypse? Not so fast alarmists. Yes, there are media headlines around mergers, closings and consumers adopting new ways to shop, but let me give you three reasons as to why the retail sky is not falling. There were more store openings last year than closings, and that trend is expected to continue this year with an estimated 5,500 openings by December. There continues to be a positive sales trajectory. E-commerce sales are increasing. Big department stores have seen pains, but if brands are focused on connection, relevance and convenience, there is hope. Consumers continue to spend. Subprime auto bubble? Nope. Malinda Zabritski, Sr. Director of Experian Automotive Sales, says the media likes to fixate on the subprime, but subprime financing has been on the decline, reaching record lows. Deep subprime is at .65%. Additionally, delinquency rates have also tapered. The real message? Consumers are relying on auto lenders for financing, largely due to consumer preferences to lease. The market is healthy, and while it has slowed slightly, the market is still at 7% year-over-year growth. Consumer-permissioned data is not just a value-add for thin-file consumers. Take for instance the inclusion of demand deposit accounts (DDAs). David Shellenberger, Sr. Director of Scoring and Predictive Analytics for FICO, says people who have had long relationships with their checking accounts tend to be more stable and generally sport higher credit scores. Consumers with thick, mature files can also benefit with DDA data. Consumer-permissioned data is not just about turning a “no” to a “yes.” It can also take a consumer from near-prime to prime, or from prime to super-prime. Would you want to make a credit decision with less information or more? This was the question Paul DeSaulniers, Experian Sr. Director of Product, posed to the audience as he kicked off the session on alternative data. With an estimated 100 million U.S. consumers falling below “thick-file” credit status, there is a definite need to learn more about these individuals. By leveraging alternative credit data – like short-term lending product use, rental data, public records and consumer-permissioned data – a more holistic view of these consumers is available. A few more facts: While alternative finance users tend to be more subprime, 20% are prime or better. A recent data pull revealed 20% of approved credit card users also had alternative finance data on them as well. About 2/3 of households headed by young adults are rentals. Imagine a world where the mortgage journey takes only seven to 10 days. With data and technology, we are closer than you think. Future products are underway that could master the underwriting phase in just one day, leaving the remaining days dedicated for signing disclosures, documents and wiring funds. Processes need to be firmed up, but a vision has been set. The average 30- to 45-day mortgage journey could soon be a distant memory. 97% of online banking applications that are started are abandoned. Why? Filling out lengthy forms, especially on a mobile device, is not fun. New technology, such as Experian’s Instant Form Fill, is allowing consumers to provide a name, zip and last four numbers of their social security number for an instant form fill of the rest of the application. Additionally, voice assistants are expected to increasingly facilitate research on purchases big and small. A recent study revealed nearly half of consumers perceive voice assistants to be useful. Businesses have more fraud losses than ever before. Not surprising. What is scary? An estimated 54% of businesses said they are not confident in their ability to detect fraud. Another session reported that approximately 20% of credit charge-offs are synthetic IDs, a growing pain point for all businesses. Consumers, on the other hand, say they “want visible signs of security” and “no friction.” Tough to balance, but those are today’s expectations. More Vision 2018 insights can be accessed on #ExperianVision twitter feed. Vision 2019 will be in San Antonio, Texas next May 5-8.
Alternative credit data. Enhanced digital credit marketing. Faster, integrated decisioning. Fraud and identity protections. The latest in technology innovation. These were the themes Craig Boundy, Experian’s CEO of North America, imparted to an audience of 800-plus Vision guests on Monday morning. “Technology, innovation and new sources of data are fusing to create an unprecedented number of new ways to solve pressing business challenges,” said Boundy. “We’re leveraging the power of data to help people and businesses thrive in the digital economy.” Main stage product demos took the shape of dark web scans, data visualization, and the latest in biometric fraud scanning. Additionally, a diverse group of breakout sessions showcased all-new technology solutions and telling stats about how the economy is faring in 2018, as well as consumer credit trends and preferences. A few interesting storylines of the day … Regulatory Under the Trump administration, everyone is talking about deregulation, but how far will the pendulum swing? Experian Sr. Director of Regulatory Affairs Liz Oesterle told audience members that Congress will likely pass a bill within the next few days, offering relief to small and mid-sized banks and credit unions. Under the new regulations, these smaller players will no longer have to hold as much capital to cover losses on their balance sheets, nor will they be required to have plans in place to be safely dismantled if they fail. That trigger, now set at $50 billion in assets, is expected to rise to $250 billion. Fraud Alex Lintner, Experian’s President of Consumer Information Services, reported there were 16.7 million identity theft victims in 2017, resulting in $16.8 billion in losses. Need more to fear? There is also a reported 323k new malware samples found each day. Multiple sessions touched on evolving best practices in authentication, which are quickly shifting to biometrics-based solutions. Personal identifiable information (PII) must be strengthened. Driver’s licenses, social security numbers, date of birth – these formats are no longer enough. Get ready for eye scans, as well as voice and photo recognition. Emerging Consumers The quest to understand the up-and-coming Millennials continues. Several noteworthy stats: 42% of Millennials said they would conduct more online transactions if there weren’t so many security hurdles to overcome. So, while businesses and lenders are trying to do more to authenticate and strengthen security, it’s a delicate balance for Millennials who still expect an easy and turnkey customer experience. Gen Z, also known as Centennials, are now the largest generation with 28% of the population. While they are just coming onto the credit scene, these digital natives will shape the credit scene for decades to come. More than ever, think mobile-first. And consider this … it\'s estimated that 25% of shopping malls will be closed within five years. Gen Z isn’t shopping the mall scene. Retail is changing rapidly! Economy Mortgage originations are trending up. Consumer confidence, investor confidence, interest rates and home sales are all positive. Unemployment remains low. Bankcard originations have now surpassed the 2007 peak. Experian’s Vice President of Analytics Michele Raneri had glowing remarks on the U.S. economy, with all signs pointing to a positive 2018 across the board. Small business loan volumes are also up 10% year-to-date versus the same time last year. Keynote presenters speculate there could be three to four rate hikes within the year, but after years of no hikes, it’s time. Data There are 2.5 quintillion pieces of data created daily. And 80% of what we know about a consumer today is the result of data generated within the past year. While there is no denying there is a LOT of data, presenters throughout the day talked about the importance of access and speed. Value comes with more APIs to seamlessly connect, as well as data visualization solutions like Tableau to make the data easier to understand. More Vision news to come. Gain insights and news throughout the day by following #ExperianVision on Twitter.
The traditional credit score has ruled the financial services space for decades, but it‘s clear the way in which consumers are managing their money and credit has evolved. Today’s consumers are utilizing different types of credit via various channels. Think fintech. Think short-term loans. Think cash-checking services and payday. So, how do lenders gain more visibility to a consumer’s credit worthiness in 2018? Alternative credit data has surfaced to provide a more holistic view of all consumers – those on the traditional file and those who are credit invisibles and emerging. In an all-new report, Experian dives into “The State of Alternative Credit Data,” providing in-depth coverage on how alternative credit data is defined, regulatory implications, consumer personas attached to the alternative financial services industry, and how this data complements traditional credit data files. “Alternative credit data can take the shape of alternative finance data, rental, utility and telecom payments, and various other data sources,” said Paul DeSaulniers, Experian’s senior director of Risk Scoring and Trended/Alternative Data and attributes. “What we’ve seen is that when this data becomes visible to a lender, suddenly a much more comprehensive consumer profile is formed. In some instances, this helps them offer consumers new credit opportunities, and in other cases it might illuminate risk.” In a national Experian survey, 53% of consumers said they believe some of these alternative sources like utility bill payment history, savings and checking account transactions, and mobile phone payments would have a positive effect on their credit score. Of the lenders surveyed, 80% said they rely on a credit report, plus additional information when making a lending decision. They cited assessing a consumer’s ability to pay, underwriting insights and being able to expand their lending universe as the top three benefits to using alternative credit data. The paper goes on to show how layering in alternative finance data could allow lenders to identify the consumers they would like to target, as well as suppress those that are higher risk. “Additional data fields prove to deliver a more complete view of today’s credit consumer,” said DeSaulniers. “For the credit invisible, the data can show lenders should take a chance on them. They may suddenly see a steady payment behavior that indicates they are worthy of expanded credit opportunities.” An “unscoreable” individual is not necessarily a high credit risk — rather they are an unknown credit risk. Many of these individuals pay rent on time and in full each month and could be great candidates for traditional credit. They just don’t have a credit history yet. The in-depth report also explores the future of alternative credit data. With more than 90 percent of the data in the world having been generated in just the past five years, there is no doubt more data sources will emerge in the coming years. Not all will make sense in assessing credit decisions, but there will definitely be new ways to capture consumer-permissioned data to benefit both consumer and lender. Read Full Report
Experian’s annual Vision Conference kicks off on Sunday to a sold-out crowd in Scottsdale, Ariz., bringing together some of the industry’s top thought leaders in financial services, technology, data science and information security. The conference, now in its 37th year, will run through Tuesday evening and showcase 55-plus breakout sessions and several all-star keynotes. “We take great pride in offering our guests the cutting-edge data and insights they need to keep advancing and evolving their own businesses,” said Reshma Peck, Experian’s senior vice president of marketing. “But what makes Vision really special is the networking and collaboration we witness throughout the conference – leaders connect and leave inspired – ready to make strides in a world that is evolving at breakneck speed.” A few session spotlights include: A look at data visualization tools and the ability to access anonymized credit data on 220 million U.S. credit consumers A deep dive into machine learning and artificial intelligence, showcasing how advancements in technology are improving credit risk scores and fraud detection Multiple breakouts on trends attached to Milliennials, Gen Z, the economy, automotive finance, small business performance and fraud How alternative credit data is providing deeper insights to uncover opportunities with both thin-file and thick-file credit consumers Digital credit advancements in mobile, voice and targeting. Beyond the traditional breakouts, featured speakers will punctuate each day. On Monday, Dr. Janet Yellen, former chair of the Federal Reserve, will deliver one of her first speeches since retiring her influential role in February 2018. On Tuesday, Gabby Giffords and Captain Mark Kelly will take the stage to talk about the importance of community, service and perseverance. Finally, NFL Quarterback Aaron Rodgers will share leadership lessons and sports highlights on Tuesday afternoon. An exclusive Tech Showcase will additionally run throughout the conference, delivering first-hand demos for participants to experience the latest in technology tools associated with fraud, voice and data analytics and access. Stats, insights and event highlights will be shared on multiple social media platforms throughout the three-day conference. Follow along with #ExperianVision.
At Experian, innovation is at the heart of our culture. We strive for continuous improvement, from finding new ways to better use data to identifying ways to make access to credit faster and simpler for millions of people around the world. So we are especially proud that one of our latest innovations—Text for Credit—was recognized by FinTech Breakthrough, an organization that highlights the top companies, technologies and products in the global FinTech market. The Innovation Award for Consumer Lending comes in a year of significant innovation milestones for Experian. In addition to introducing Text for Credit, we’ve partnered with Finicity, and also created a more open and adaptive technology environment by implementing API capabilities across the Experian network. We recently introduced Text for Credit, the first credit solution that enables consumers to apply for credit with a simple text message. Using mobile identification through our Smart Lookup process, consumers can be recognized by their device credentials, bypassing the need to fill out a lengthy credit application. Our Text for Credit product enables consumers to apply for real-time access to credit while standing in line to make their purchases, or before entering an auto dealership. This recognition as an innovator is a testament to our employees’ focus on putting the consumer and our customers at the center of what we do, and powering innovative opportunities to secure better, more productive futures for people and organizations. What’s next We are also exploring other opportunities to make the consumer experience more convenient. As we’re becoming a keyboard-less society, we’re looking at the next frontier: voice technology. The progression to voice-activated services has started already using voice commands through Amazon Alexa and Google Home-enabled devices. And while voice technology is still in its infancy, it’s not a tremendous leap to envision being able to use voice commands to access lines of credit in a store, like Text for Credit now. Experian DataLabs is exploring many possibilities for voice-activated credit, using several different devices—more than just via phone. As technology innovators, our greatest challenge is determining which potential solutions to pursue. It comes down to a simple equation: the magnitude of impact a new application may have, plus its probability of success. So far, we’ve found plenty of options that satisfy both criteria—and our curiosity, too. With technology, machine learning and ever-smarter applications of big data, we can deliver intriguing and convenient experiences to shoppers in ways we never imagined a decade ago. Predicting the future has never been this much fun.
In my first blog post on the topic of customer segmentation, I shared with readers that segmentation is the process of dividing customers or prospects into groupings based on similar behaviors. The more similar or homogeneous the customer grouping, the less variation across the customer segments are included in each segment’s custom model development. A thoughtful segmentation analysis contains two phases: generation of potential segments, and the evaluation of those segments. Although several potential segments may be identified, not all segments will necessarily require a separate scorecard. Separate scorecards should be built only if there is real benefit to be gained through the use of multiple scorecards applied to partitioned portions of the population. The meaningful evaluation of the potential segments is therefore an essential step. There are many ways to evaluate the performance of a multiple-scorecard scheme compared with a single-scorecard scheme. Regardless of the method used, separate scorecards are only justified if a segment-based scorecard significantly outperforms a scorecard based on a broader population. To do this, Experian® builds a scorecard for each potential segment and evaluates the performance improvement compared with the broader population scorecard. This step is then repeated for each potential segmentation scheme. Once potential customer segments have been evaluated and the segmentation scheme finalized, the next step is to begin the model development. Learn more about how Experian Decision Analytics can help you with your segmentation or custom model development needs.
Marketers are keenly aware of how important it is to “Know thy customer.” Yet customer knowledge isn’t restricted to the marketing-savvy. It’s also essential to credit risk managers and model developers. Identifying and separating customers into distinct groups based on various types of behavior is foundational to building effective custom models. This integral part of custom model development is known as segmentation analysis. Segmentation is the process of dividing customers or prospects into groupings based on similar behaviors such as length of time as a customer or payment patterns like credit card revolvers versus transactors. The more similar or homogeneous the customer grouping, the less variation across the customer segments are included in each segment’s custom model development. So how many scorecards are needed to aptly score and mitigate credit risk? There are several general principles we’ve learned over the course of developing hundreds of models that help determine whether multiple scorecards are warranted and, if so, how many. A robust segmentation analysis contains two components. The first is the generation of potential segments, and the second is the evaluation of such segments. Here I’ll discuss the generation of potential segments within a segmentation scheme. A second blog post will continue with a discussion on evaluation of such segments. When generating a customer segmentation scheme, several approaches are worth considering: heuristic, empirical and combined. A heuristic approach considers business learnings obtained through trial and error or experimental design. Portfolio managers will have insight on how segments of their portfolio behave differently that can and often should be included within a segmentation analysis. An empirical approach is data-driven and involves the use of quantitative techniques to evaluate potential customer segmentation splits. During this approach, statistical analysis is performed to identify forms of behavior across the customer population. Different interactive behavior for different segments of the overall population will correspond to different predictive patterns for these predictor variables, signifying that separate segment scorecards will be beneficial. Finally, a combination of heuristic and empirical approaches considers both the business needs and data-driven results. Once the set of potential customer segments has been identified, the next step in a segmentation analysis is the evaluation of those segments. Stay tuned as we look further into this topic. Learn more about how Experian Decision Analytics can help you with your segmentation or custom model development needs.
Alternative credit data sources make it possible for lenders to gain a more holistic view of existing and potential client bases, enabling them to better determine the risk of lending to someone with little or no credit history. These sources also can provide lenders with a competitive edge by preparing them to be better equipped to mitigate losses, expand their scope of potential applicants, give them another look at the creditworthiness of previously-denied applicants, and enable them to properly adjust credit terms and pricing to better speak to compatible consumers. “Experian is a big supporter of the widespread reporting of alternative data—including, rental payments, utility payments and cellular telephone payments to name a few,” said Alex Lintner, president of Experian’s Consumer Information Services. Here are four FCRA-compliant alternative credit data sources to consider when evaluating consumers for credit: Alternative Financial Services: Alternative financial credit information, including payday and short-term installment loans and inquiries, on the majority of the United States’ subprime population. Rental Data: RentBureau includes detailed, positive and negative rental payment history information on more than 18 million consumers in the United States. Extended View Score: A risk model designed to evaluate the creditworthiness of thin-file and no-file consumers who have little to no traditional credit history. Account Aggregation: Permissioned by the consumer, a real-time data collection of his/her financial accounts (bank, credit card, investment and business) in a single location to digitally verify income and assets. Tapping into these resources can give deeper and richer results—improving overall data analytics and, subsequently, possibilities for future lending.
In the credit game, the space is deep and diverse. From super prime to prime to subprime consumers, there is much to be learned about how different segments are utilizing credit and navigating the financial services arena. With 78 percent of full-time workers saying they live paycheck-to-paycheck and 71 percent of U.S. workers responding that they live in debt, it is not surprising a sudden life event can plunge a solid credit consumer from prime to subprime within months. Think lost job, divorce or unexpected medical bill. This population is not going away, and they are seeking ways to make ends meet and obtain finances for needs big and small. In many instances, alternative credit data can shed a light on new opportunities for traditional lenders, fintech players and those in the alternative financial space when servicing this specific consumer segment. In a new study, Clarity analyzed the trends and financial behavior of subprime loan users by looking at application and loan data in Clarity’s database, as well as overlaying Vantage Score insights from Experian from 2013 to 2017. Clarity conducted this subprime trends report last year, but this is the first time it factored in Vantage score data, providing a different lens as to where consumers fall within the credit score tiers. Among the study highlights: Storefront single pay loan customers are becoming more comfortable with applying for online loans, with a growing percentage seeking installment products. For the first time in five years, online single pay lending (payday) saw a reduction in total credit utilization per customer. Online installment, on the other hand, saw an increase. While the number of online installment loans increased by 12 percent and the number of borrowers by only 9 percent, the dollar value grew by 30 percent. Online installment lenders had the greatest percentage increase in average loan amount. California and Texas remain the most significant markets for online lenders, ranking first and second for five years in a row due to population size. There has also been growth in the Midwest. The in-depth report additionally delves into demographics, indicators of financial stability among the subprime market and comparisons between storefront and online product use and performance. “Every year, there are more financial lenders and products emerging to serve this population,” said Andy Sheehan, president of Clarity Services. “It’s important to understand the trends and data associated with these individuals and how they are maneuvering throughout the credit spectrum. As we know, it is often not a linear journey.” The inclusion of the Vantage Score showcased additional findings around prime versus subprime financial behaviors and looks at generational trends. Access Full Report
With 16.7 million reported victims of identity fraud in 2017 (that’s 6.64 percent of the U.S. population), it was another record year for the number of fraud victims. And as online and mobile transaction growth continued to significantly outpace brick-and-mortar growth, criminal attacks also grew rapidly. This past year, we saw an increase of more than 30 percent in e-commerce fraud attacks compared with 2016. As we’ve done over the past three years, Experian® analyzed millions of online transactions to identify fraud attack rates for both shipping and billing locations across the United States. We looked at several data points, including geography and IP address, to help businesses better understand how and where fraud is being perpetrated so they can better protect against it. The 2017 e-commerce fraud attack rate analysis shows: Delaware and Oregon continue to be the riskiest states for both billing and shipping fraud. Delaware; Oregon; Washington, D.C.; Florida; and Georgia are the top five riskiest states for billing fraud. Delaware, Oregon, Florida, New York and California are the top five riskiest states for shipping fraud, accounting for 50 percent of total fraud attacks. South El Monte, Calif., is the riskiest city overall, with an increase in shipping fraud of approximately 230 percent. Shipping fraud most often occurs near major airports and seaports due to reshippers and freight forwarders that receive domestic goods and often send them overseas. When a transaction originates from an international IP address, shipping fraud is 6.7 times likelier than the average, while billing fraud becomes 7.1 times likelier. Where is e-commerce fraud happening? Typically, the highest-risk areas for fraud are in ZIP™ codes and cities near large ports of entry or airports. These are ideal locations to reship fraudulent merchandise, enabling criminals to move stolen goods more effectively. Top 10 riskiest billing ZIP™ codes Top 10 riskiest shipping ZIP™ codes 97252 Portland, OR 97079 Beaverton, OR 33198 Miami, FL 33122 Miami, FL 33166 Miami, FL 91733 South El Monte, CA 33122 Miami, FL 97251 Portland, OR 77060 Houston, TX 97250 Portland, OR 33195 Miami, FL 33166 Miami, FL 97250 Portland, OR 97252 Portland, OR 97251 Portland, OR 33198 Miami, FL 33191 Miami, FL 33195 Miami, FL 97253 Portland, OR 33192 Miami, FL Source: Experian.com Source: Experian.com What’s more, many of the riskiest ZIP™ codes and cities experience a high volume of transactions originating from international IP addresses. In fact, the top 10 riskiest ZIP codes overall tend to experience fraudulent activity from numerous countries overseas, including China, Venezuela, Taiwan and Hong Kong, and Argentina. These fraudsters tend to implement complex fraud schemes that can cost businesses millions of dollars in fraud losses. Additionally, the analysis shows that traffic coming from a proxy server — which could originate from domestic and international IP addresses — is 74 times riskier than the average transaction. The problem The increase in e-commerce fraud attacks shouldn’t come as a huge surprise. The uptick in data breaches, merchants’ continued adoption of EMV-enabled terminals to protect against counterfeit card fraud and the abundance of consumer data on the dark web means that information is even more accessible to criminals. This enables them to open fraudulent accounts, take over legitimate accounts and submit fraudulent transactions. Another reason for the increase is automation. In the past, criminals needed a strong understanding of fraud methods and technology, but they can now bring down an entire organization by simply downloading a file and automating the submission of thousands of applications or transactions simultaneously. Since fraudsters need to make these transactions appear as normal as possible, they often leverage the cardholder’s actual billing details with slight differences, such as e-mail address or shipping location. Unfortunately, the mass availability of compromised data and the abundance of fraudsters makes it increasingly challenging to identify and separate legitimate customers from attackers across the country. Because of the widespread prevalence of fraud and data compromises, we don’t see billing fraud concentrated in just one region of the country. In fact, the top five states for billing fraud make up only about 18 percent of overall fraud attacks. Top 5 riskiest billing fraud states Top 5 riskiest shipping fraud states State Fraud attack rate State Fraud attack rate Delaware 93.4 Delaware 195.9 Oregon 86.1 Oregon 170.1 Washington, D.C. 46.5 Florida 45.1 Florida 39.2 New York 37.3 Georgia 31.5 California 32.6 Source: Experian.com Source: Experian.com Prevention and protection need to be the priority As businesses get a better understanding of how and where fraud is perpetrated, they can implement proactive strategies to detect and prevent attacks, as well as protect payment information. While no one single strategy can address the entire scope of fraud, there are advanced data sets and technology — such as device intelligence, behavioral and physical biometrics, document verification and entity resolution — that can help businesses make better fraud decisions. Fortunately, consumers can also play a major role in safeguarding their information. In addition to regularly checking their credit reports and bank/credit card statements for fraudulent activity, consumers can limit the data they share on social networking sites, where attackers often begin when perpetrating identity fraud. While we continue to help both organizations and consumers limit their exposure to e-commerce fraud, we anticipate that criminals will attempt more sophisticated fraud schemes. But businesses can stay ahead of the curve. This comes down to having a keen understanding of how fraud is being perpetrated, as well as leveraging data, technology and multiple layered strategies to better recognize legitimate customers and make more precise fraud decisions. View our e-commerce fraud heat map and download the top 100 riskiest ZIP codes in the United States. Experian is a nonexclusive full-service provider licensee of the United States Postal Service®. The following trademark is owned by the United States Postal Service®: ZIP. The price for Experian’s services is not established, controlled or approved by the United States Postal Service.
Managing your customer accounts at the identity level is ambitious and necessary, but possible Identity-related fraud exposure and losses continue to grow. The underlying schemes have elevated in complexity. Because it’s more difficult to perpetrate “card present” fraud in the post–chip-and-signature rollout here in the United States, bad guys are more motivated and getting better at identity theft and synthetic identity attacks. Their organized nefarious response takes the form of alternate attack vectors and methodologies — which means you need to stamp out any detected exposure point in your fraud prevention strategies as soon as it’s detected. Experian’s recently published 2018 Global Fraud and Identity Report suggests two-thirds, or 7 out of every ten, consumers want to see visible security protocols when they transact. But an ever-growing percentage of them, fueled in no small part by those tech-savvy millennials, expect to be recognized with little or no friction. In fact, 42 percent of the surveyed consumers who stated they would do more transactions online if there weren’t so many security hurdles to overcome were — you guessed it — millennials. So how do you implement identity and account management procedures that are effective and, in some cases, even obvious while being passive enough to not add friction to the user experience? In other words, from the consumer’s perspective, “Let me know you know me and are protecting me but not making it too difficult for me when I want to access or manage my account.” Let’s get one thing out of the way first. This isn’t a one-time project or effort. It is, however, a commitment to the continued informing of your account management strategies with updated identity intelligence. You need to make better decisions on when to let a low-risk account transaction (monetary or nonmonetary) pass and when to double down a bit and step up authentication or risk assessment checks. I’d suggest this is most easily accomplished through a single, real-time access point to myriad services that should, at the very least, include: Identity verification and reverification checks for ongoing reaffirmation of your customer identity data quality and accuracy. Know Your Customer program requirements, anyone? Targeted identity risk scores and underlying attributes designed to isolate identity theft, first-party fraud and synthetic identity. Fraud risk comes in many flavors. So must your analytics. Device intelligence and risk assessment. A customer identity is no longer just their name, address, Social Security number and date of birth. It’s their phone number, email address and the various devices they use to access your services as well. Knowing how that combination of elements presents itself over time is critical. Layered passive or more active authentication options such as document verification, biometrics, behavioral metrics, knowledge-based verification and alternative data sources. Ongoing identity monitoring and proactive alerting and segmentation of customers whose identity risk has shifted to the point of required treatment. Orchestration, workflow and decisioning capabilities that allow your team to make sense of the many innovative options available in customer recognition and risk assessment — without a “throw the kitchen sink at this problem” approach that will undoubtedly be way too costly in dollars spent and good customers annoyed. Fraud attacks are dynamic. Your customers’ perceptions and expectations will continue to evolve. The markets you address and the services you provide will vary in risk and reward. An innovative marketplace of identity management services can overwhelm. Make sure your strategic identity management partner has good answers to all of this and enables you to future-proof your investments.
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