Models & Scores
Experian Boost provides a unique opportunity to help dealers build loyalty while helping consumers.
Many companies rely on attributes for decisioning but lack the resources needed to invest in developing, managing, and updating the attributes themselves. Experian is there to guide you every step of the way with our Attribute Toolbox – our source independent solution that provides maximum flexibility and multiple data sources you can use in the calculation and management of attributes. To create and manage our attributes, Experian has established development principles and created a set methodology to ensure that our attribute management system works across the attribute life cycle. Here’s how it works: Develop Attributes The attribute development process includes: discovery, exploratory data analysis, filter leveling, and the development of attributes. When we create attributes, Experian takes great care to ensure that we: Analyze the available data elements and how they are populated (the frequencies of fields). Determine a “sensible” definition of the attribute. Evaluate attribute frequencies. Review consumer credit reports, where possible. Refine the definition and assess more frequencies and examples. Test Attributes Before implementing, Experian performs an internal audit of filters and attributes. Defining, coding and auditing filters is 80% of the attribute development process. The main objective of the auditing process is to ensure both programming and logical accuracy. This involves electronic and manual auditing and requires a thorough review of all data elements used in development. Deploy Attributes Deployment is very similar to attribute testing. However, in this case, the primary objective of the deployment audit is to ensure both the programming and logical accuracy of the output is executing correctly on various platforms. We aim to maintain consistency among various business lines and products, between batch and online environments across the life cycle, and wherever your models are deployed: on premises, in the cloud, and off-site in your partners’ systems. Govern Attributes Experian places a robust attribute governance process in place to ensure that our attributes remains up-to-date and on track with internal and external compliance regulations and audits. New learnings, industry and regulatory changes can lead to updated attributes or new attributes over time. Because attributes are ever-changing, we take great care to expand, update and add new attributes over time based on three types of external changes: economic, bureau, and reporting changes. Fetch Data While we gather the data, we ensure that you can integrate a variety of external data sources, including: consumer bureau, business, fraud, and other data sources. Attributes need to be: Highly accurate. Suitable for use across the Customer Life Cycle. Suitable for use in credit decisioning and model development. Available and consistent across multiple platforms. Supportive and adaptable to ever-evolving regulatory considerations. Thoroughly documented and monitored. Monitor Performance We generate attribute distribution reports and can perform custom validations using data from credit reporting agencies (CRAs) and other data providers. This is based on monthly monitoring to ensure continued integrity and stability to stand up to regulatory scrutiny and compliance regulations. Variations that exceed predetermined thresholds are identified, quantified, and explained. If new fields or data values within existing fields are announced, we assess the impact and important of these values on attributes – to determine if revisions are needed. Maintain Attributes Credit bureau data updates, new attributes in response to market needs, compliance requirements, corrections in logic where errors are identified or improvements to logic often lead to new version releases of attributes. With each new version release, Experian takes care to conduct thorough analyses comparing the previous and current set of attributes. We also make sure to create detailed documentation on what’s changed between versions, the rationale for changes and the impact on existing attributes. Experian Attributes are the key to unlocking consistent, enhanced and more profitable decisions. Our data analysts and statisticians have helped hundreds of clients build custom attributes and custom models to solve their business problems. Our Attribute Toolbox makes it easier to deploy and manage attributes across the customer lifecycle. We give companies the power to code, manage, test, and deploy all types of attributes, including: Premier AttributesSM, Trended 3DTM, and custom attributes – without relying on a third-party. We do the heavy lifting so that you don’t have to. Learn More
Today is National Fintech Day – a day that recognizes the ever-important role that fintech companies play in revolutionizing the customer experience and altering the financial services landscape. Fintech. The word itself has become synonymous with constant innovation, agile technology structures and being on the cusp of the future of finance. Fintech challengers are disrupting existing financial models by leveraging data, advanced analytics and technology – both inspiring traditional financial institutions in their digital transformation strategies and giving consumers access to a variety of innovative financial products and services. But to us at Experian, National Fintech Day means more than just financial disruption. National Fintech Day represents the partnerships we have carefully fostered with our fintech clients to drive financial inclusion for millions of people around the globe and provide consumers with greater control and more opportunities to access the quality credit they deserve. “We are actively seeking out unresolved problems and creating products and technologies that will help transform the way businesses operate and consumers thrive in our society. But we know we can’t do it alone,” said Experian North American CEO, Craig Boundy in a recent blog article on Experian’s fintech partnerships. “That’s why over the last year, we have built out an entire team of account executives and other support staff that are fully dedicated to developing and supporting partnerships with leading fintech companies. We’ve made significant strides that will help us pave the way for the next generation of lending while improving the financial health of people around the world.” At Experian, we understand the challenges fintechs face – and our real-world solutions help fintech clients stay ahead of constantly changing market conditions and demands. “Experian’s pace of innovation is very impressive – we are helping both lenders and consumers by delivering technological solutions that make the lending ecosystem more efficient,” said Experian Senior Account Executive Warren Linde. “Financial technology is arguably the most important type of tech out there, it is an honor to be a part of Experian’s fintech team and help to create a better tomorrow.” If you’d like to learn more about Experian’s fintech solutions, visit us at Experian.com/Fintech.
The fact that the last recession started right as smartphones were introduced to the world gives some perspective into how technology has changed over the past decade. Organizations need to leverage the same technological advancements, such as artificial intelligence and machine learning, to improve their collections strategies. These advanced analytics platforms and technologies can be used to gauge customer preferences, as well as automate the collections process. When faced with higher volumes of delinquent loans, some organizations rapidly hire inexperienced staff. With new analytical advancements, organizations can reduce overhead and maintain compliance through the collections process. Additionally, advanced analytics and technology can help manage customers throughout the customer life cycle. Let’s explore further: Why use advanced analytics in collections? Collections strategies demand diverse approaches, which is where analytics-based strategies and collections models come into play. As each customer and situation differs, machine learning techniques and constraint-based optimization can open doors for your organization. By rethinking collections outreach beyond static classifications (such as the stage of account delinquency) and instead prioritizing accounts most likely to respond to each collections treatment, you can create an improved collections experience. How does collections analytics empower your customers? Customer engagement, carefully considered, perhaps comprises the most critical aspect of a collections program—especially given historical perceptions of the collections process. Experian recently analyzed the impact of traditional collections methods and found that three percent of card portfolios closed their accounts after paying their balances in full. And 75 percent of those closures occurred shortly after the account became current. Under traditional methods, a bank may collect outstanding debt but will probably miss out on long-term customer loyalty and future revenue opportunities. Only effective technology, modeling and analytics can move us from a linear collections approach towards a more customer-focused treatment while controlling costs and meeting other business objectives. Advanced analytics and machine learning represent the most important advances in collections. Furthermore, powerful digital innovations such as better criteria for customer segmentation and more effective contact strategies can transform collections operations, while improving performance and raising customer service standards at a lower cost. Empowering consumers in a digital, safe and consumer-centric environment affects the complete collections agenda—beginning with prevention and management of bad debt and extending through internal and external account resolution. When should I get started? It’s never too early to assess and modernize technology within collections—as well as customer engagement strategies—to produce an efficient, innovative game plan. Smarter decisions lead to higher recovery rates, automation and self-service tools reduce costs and a more comprehensive customer view enhances relationships. An investment today can minimize the negative impacts of the delinquency challenges posed by a potential recession. Collections transformation has already begun, with organizations assembling data and developing algorithms to improve their existing collections processes. In advance of the next recession, two options present themselves: to scramble in a reactive manner or approach collections proactively. Which do you choose? Get started
Today, Experian and Oliver Wyman announced the launch of Ascend CECL ForecasterTM, a solution built to help financial institutions of all sizes more quickly and accurately forecast lifetime credit losses. The Financial Accounting Standards Board’s current expected credit loss (CECL) model has been a hot discussion topic throughout the financial services industry - first when it was announced (and considered one of the most significant accounting changes in decades), and most recently with the FASB’s delay for implementation for smaller lenders. As the compliance deadlines approach, Experian and Oliver Wyman have joined forces to help financial institutions adhere their loan portfolios to the new guidelines. Delivered through Experian’s Ascend Technology PlatformTM, Ascend CECL Forecaster is a new user-friendly, web-based application that combines Experian’s vast loan-level data and Premier AttributesSM, third-party macroeconomic data, valuation data and Oliver Wyman’s industry-leading CECL modeling methodology to accurately calculate potential losses over the life of a loan. “Ascend CECL Forecaster is a critical capability needed urgently by all lending and financial institutions,” said Ash Gupta, a Senior Advisor to Oliver Wyman and former Chief Risk Officer for American Express, in a press release. “The collaboration between Experian and Oliver Wyman allows a frictionless synthesis of industry data, capabilities and experience to serve customers in both first and second line of defense.” The premise behind the model, which will need access to more data than that used to calculate reserves under the incurred loss model, Allowance for Loan and Lease Losses (ALLL), is for financial institutions to estimate the expected loss over the life of a loan by using historical information, current conditions and reasonable forecasts. Built using advanced machine learning and statistical techniques, the web-based application maximizes the more than 15 years of historical credit data spanning previous economic cycles to help financial institutions gauge loan portfolio performance under various scenarios. Ascend CECL Forecaster does not require additional data nor does it require a secondary integration from the financial institution and enables organizations to more quickly test their portfolios under different economic factors. Moreover, financial institutions receive guidance from industry experts to assist with implementation and strategy. Additionally, Experian and Oliver Wyman will host a webinar to help financial institutions better understand and prepare for the upcoming CECL standards. Register today! Read the Press Release Register for Webinar
Consumer behavior is constantly evolving — from the channels they prefer to the economic trends spurring varying interest and activity. It’s no surprise that businesses find it challenging to know what their customers want today or tomorrow. But knowing and understanding this information is essential to growing your bottom line. Through years of working with businesses across every vertical, we’ve found that a solid approach to growing your business revolves around your customers. The better you know your customers, the better you can achieve your goals. Seeing the future. How well can you identify and rank your current customer population? Are you leveraging that insight to acquire new customers, manage current customers and prioritize collections efforts? If so, you’re probably using custom models in your business strategy. But if your organization is like many businesses, you may use a more traditional approach. In our highly competitive market, strategy and decisions must be based on the right data and insights. No excuses. The data is there, and we can help you turn it into actionable insights. Implementing a custom model can maximize your return on investment and help you make more profitable business decisions — now and in the future. No palm reading required. Without visiting your local fortuneteller, you still can predict the future. You need a model, but not the “runway” type. What constitutes a highly predictive and effective model? Many factors. A highly predictive custom model should incorporate robust data, advanced modeling methodologies, analytical expertise and attributes. Having these foundational components is essential to knowing your customers and making confident decisions. Models aren’t one-size-fits-all. When you take an innovative approach to model development, the model is targeted to support your specific business goals while providing the documentation required for regulatory reviews. Consider these items as you develop your custom model: Data — It all starts with the right data. Combining multiple data assets — your master-file data, our credit data and any additional data sources — is key to developing a robust model development sample. In other words, a model development sample should represent your future through-the-door population. Model design — To ensure the custom model is designed to help you achieve your specific goals, you’ll want to incorporate the latest analytics and modeling methodologies. An experienced analytics team will be essential here. Segmentation — With the right model development and segmentation strategies, you can identify optimal segments that will result in a more predictive custom model. This way, each consumer is scored on a scorecard developed using a credit profile similar to theirs. Validation — To ensure the model’s predictive ability and longevity, validate each custom model on a holdout sample and compare it with other scores to ensure it accounts for the current and future (through-the-door) consumer populations, as well as policy rule and behavioral changes. Regulatory review — Don’t forget about the documentation needed for compliance. While audits are unpleasant , fines and extensive scrutiny can significantly impact your business. Take your fortunetelling to the next level. Machine learning is all the rage. This cutting-edge technology can be embedded in your predictive models to help uncover patterns in data that may not be apparent otherwise. This can be done by comparing the performance of the machine learning model with your existing models. Once you know that machine learning can add the lift you’re looking for, you can apply that methodology to develop a custom model focused on stability, cost-efficiency, transparency and predictive performance. Predicting behavior across the Customer Life Cycle. How can a custom model benefit you? From improving baseline performance and increasing profitability by approving more good accounts to uncovering opportunities within your target market, custom models can provide the confidence needed to grow your business. Which one of these models can help you achieve your business goals? When it comes to accurately predicting customer behavior, you don’t need a crystal ball. You need a well-built, highly predictive custom model. Use the data that’s available to gain insight into your customers and grow your bottom line. If you need help, we’re here. We have the data, analytics and expertise to help you get started.
Alex Lintner, Group President at Experian, recently had the chance to sit down with Peter Renton, creator of the Lend Academy Podcast, to discuss alternative credit data,1 UltraFICO, Experian Boost and expanding the credit universe. Lintner spoke about why Experian is determined to be the leader in bringing alternative credit data to the forefront of the lending marketplace to drive greater access to credit for consumers. “To move the tens of millions of “invisible” or “thin file” consumers into the financial mainstream will take innovation, and alternative data is one of the ways which we can do that,” said Lintner. Many U.S. consumers do not have a credit history or enough record of borrowing to establish a credit score, making it difficult for them to obtain credit from mainstream financial institutions. To ease access to credit for these consumers, financial institutions have sought ways to both extend and improve the methods by which they evaluate borrowers’ risk. By leveraging machine learning and alternative data products, like Experian BoostTM, lenders can get a more complete view into a consumer’s creditworthiness, allowing them to make better decisions and consumers to more easily access financial opportunities. Highlights include: The impact of Experian Boost on consumers’ credit scores Experian’s take on the state of the American consumer today Leveraging machine learning in the development of credit scores Expanding the marketable universe Listen now Learn more about alternative credit data 1When we refer to \"Alternative Credit Data,\" this refers to the use of alternative data and its appropriate use in consumer credit lending decisions, as regulated by the Fair Credit Reporting Act. Hence, the term \"Expanded FCRA Data\" may also apply in this instance and both can be used interchangeably.
Once you have kids, your bank accounts will never be the same. From child care to college, American parents spend, on average, over $233,000 raising a child from birth through age 17. While moms and dads are facing the same pile of bills, they often don’t see eye to eye on financial matters. In lieu of Father’s Day, where spending falls $8 million behind Mother’s Day (sorry dads!), we’re breaking down the different spending habits of each parent: Who pays the bills? With 80% of mothers working full time, the days of traditional gender roles are behind us. As both parents share the task of caring for the children, they also both take on the burden of paying household bills. According to Pew Research, when asked to name their kids’ main financial provider, 45% of parents agreed they split the role equally. Many partners are finding it more logical to evenly contribute to shared joint expenses to avoid fighting over finances. However, others feel costs should be divvied up according to how much each partner makes. What do they splurge on? While most parents agree that they rarely spend money on themselves, splurge items between moms and dads differ. When they do indulge, moms often purchase clothes, meals out and beauty treatments. Dads, on the other hand, are more likely to binge on gadgets and entertainment. According to a recent survey on millennial dads, there’s a strong correlation between the domestic tasks they’re taking on and how they’re spending their money. For instance, most dads are involved in buying their children’s books, toys and electronics, as well as footing the bill for their leisure activities. Who are they more likely to spend on? No parent wants to admit favoritism. However, research from the Journal of Consumer Psychology found that you’re more likely to spend money on your daughter if you’re a woman and more likely to spend on your son if you’re a man. The suggested reasoning behind this is that women can more easily identify with their daughters and men with their sons. Overall, parents today are spending more on their children than previous generations as the cost of having children in the U.S. has exponentially grown. How are they spending? When it comes to money management both moms and dads claim to be the “saver” and label the other as the “spender.” However, according to Experian research, there are financial health gaps between men and women, specifically when it pertains to credit. For example, women have 11% less average debt than men, a higher average VantageScore and the same revolving debt utilization of 30%. Even with more credit cards, women have fewer overall debts and are managing to pay those debts on time. There’s no definite way to say whether moms are spending “better” than dads, or vice versa. Rather, each parent has their own strengths and weaknesses when it comes to allocating money and managing expenses. To gain better insight on the different ways consumers are spending money, consider Experian TAPSSM, which allows you to more accurately estimate consumer spend on all general-purpose credit and charge cards over the last 12 months. Learn more about Experian TAPS
Financial institutions preparing for the launch of the Financial Accounting Standard Board’s (FASB) new current expected credit loss model, or CECL, may have concerns when it comes to preparedness, implications and overall impact. Gavin Harding, Experian’s Senior Business Consultant and Jose Tagunicar, Director of Product Management, tackled some of the tough questions posed by the new accounting standard. Check out what they had to say: Q: How can financial institutions begin the CECL transition process? JT: To prepare for the CECL transition process, companies should conduct an operational readiness review, which includes: Analyzing your data for existing gaps. Determining important milestones and preparing for implementation with a detailed roadmap. Running different loss methods to compare results. Once losses are calculated, you’ll want to select the best methodology based on your portfolio. Q: What is required to comply with CECL? GH: Complying with CECL may require financial institutions to gather, store and calculate more data than before. To satisfy CECL requirements, financial institutions will need to focus on end-to-end management, determine estimation approaches that will produce reasonable and supportable forecasts and automate their technology and platforms. Additionally, well-documented CECL estimations will require integrated workflows and incremental governance. Q: What should organizations look for in a partner that assists in measuring expected credit losses under CECL? GH: It’s expected that many financial institutions will use third-party vendors to help them implement CECL. Third-party solutions can help institutions prepare for the organization and operation implications by developing an effective data strategy plan and quantifying the impact of various forecasted conditions. The right third-party partner will deliver an integrated framework that empowers clients to optimize their data, enhance their modeling expertise and ensure policies and procedures supporting model governance are regulatory compliant. Q: What is CECL’s impact on financial institutions? How does the impact for credit unions/smaller lenders differ (if at all)? GH: CECL will have a significant effect on financial institutions’ accounting, modeling and forecasting. It also heavily impacts their allowance for credit losses and financial statements. Financial institutions must educate their investors and shareholders about how CECL-driven disclosure and reporting changes could potentially alter their bottom line. CECL’s requirements entail data that most credit unions and smaller lenders haven’t been actively storing and saving, leaving them with historical data that may not have been recorded or will be inaccessible when it’s needed for a CECL calculation. Q: How can Experian help with CECL compliance? JT: At Experian, we have one simple goal in mind when it comes to CECL compliance: how can we make it easier for our clients? Our Ascend CECL ForecasterTM, in partnership with Oliver Wyman, allows our clients to create CECL forecasts in a fraction of the time it normally takes, using a simple, configurable application that accurately predicts expected losses. The Ascend CECL Forecaster enables you to: Fulfill data requirements: We don’t ask you to gather, prepare or submit any data. The application is comprised of Experian’s extensive historical data, delivered via the Ascend Technology PlatformTM, economic data from Oxford Economics, as well as the auto and home valuation data needed to generate CECL forecasts for each unsecured and secured lending product in your portfolio. Leverage innovative technology: The application uses advanced machine learning models built on 15 years of industry-leading credit data using high-quality Oliver Wyman loan level models. Simplify processes: One of the biggest challenges our clients face is the amount of time and analytical effort it takes to create one CECL forecast, much less several that can be compared for optimal results. With the Ascend CECL Forecaster, creating a forecast is a simple process that can be delivered quickly and accurately. Q: What are immediate next steps? JT: As mentioned, complying with CECL may require you to gather, store and calculate more data than before. Therefore, it’s important that companies act now to better prepare. Immediate next steps include: Establishing your loss forecast methodology: CECL will require a new methodology, making it essential to take advantage of advanced statistical techniques and third-party solutions. Making additional reserves available: It’s imperative to understand how CECL impacts both revenue and profit. According to some estimates, banks will need to increase their reserves by up to 50% to comply with CECL requirements. Preparing your board and investors: Make sure key stakeholders are aware of the potential costs and profit impacts that these changes will have on your bottom line. Speak with an expert
Many may think of digital transformation in the financial services industry as something like emailing a PDF of a bank statement instead of printing it and sending via snail mail. After working with data, analytics, software and fraud-prevention experts, I have found that digital transformation is actually much more than PDFs. It can have a bigger and more positive influence on a business’s bottom line – especially when built on a foundation of data. Digital transformation is the new business model. And executives agree. Seventy percent of executives feel the traditional business model will disappear in the next five years due to digital transformation, according to recent Experian research. Our new e-book, Powering digital transformation: Transforming the customer experience with data, analytics and automation, says, “we live in a world of ‘evolve or fail.’ From Kodak to Blockbuster, we’ve seen businesses resist change and falter. The need to evolve is not new. What is new is the speed and depth needed to not only compete, but to survive. Digital startups are revolutionizing industries in months and years instead of decades and centuries.” So how do businesses evolve digitally? First, they must understand that this isn’t a ‘one-and-done’ event. The e-book suggests that the digital transformation life cycle is a never-ending process: Cleanse, standardize and enrich your data to create features or attributes Analyze your data to derive pertinent insights Automate your models and business practices to provide customer-centric experiences Test your techniques to find ways to improve Begin the process again Did you notice the key word or phrase in each of these steps is ‘data’ or ‘powered by data?’ Quality, reliable data is the foundation of digital transformation. In fact, almost half of CEOs surveyed said that lack of data or analytical insight is their biggest challenge to digital transformation. Our digital world needs better access to and insight from data because information derived from data, tempered with wisdom, provides the insight, speed and competitive advantage needed in our hypercompetitive environment. Data is the power behind digital transformation. Learn more about powering your digital transformation in our new e-book>
The universe has been used as a metaphor for many things – vast, wide, intangible – much like the credit universe. However, while the man on the moon, a trip outside the ozone layer, and all things space from that perspective may seem out of touch, there is a new line of access to consumers. In Experian\'s latest 2019 State of Alternative Credit Data report, consumers and lenders alike weigh in on the growing data set and how they are leveraging the data in use cases across the lending lifecycle. While the topic of alternative credit data is no longer as unfamiliar as it may have been a year or two ago, the capabilities and benefits that can be experienced by financial institutions, small businesses and consumers are still not widely known. Did you know?: - 65% of lenders say they are using information beyond the traditional credit report to make a lending decision. - 58% of consumers agree that having the ability to contribute payment history to their credit file make them feel empowered. - 83% of lenders agree that digitally connecting financial account data will create efficiencies in the lending process. These and other consumer and lender perceptions of alternative credit data are now launched with the latest edition of the State of Alternative Credit Data whitepaper. This year’s report rounds up the different types of alternative credit data (from alternative financial services data to consumer-permissioned account data, think Experian BoostTM), as well as an overview of the regulatory landscape, and a number of use cases across consumer and small business lending. In addition, consumers also have a lot to say about alternative credit data: With the rise of machine learning and big data, lenders can collect more data than ever, facilitating smarter and more precise decisions. Unlock your portfolio’s growth potential by tapping into alternative credit data to expand your consumer universe. Learn more in the 2019 State of Alternative Credit Data Whitepaper. Read Full Report View our 2020 State of Alternative Credit Data Report for an updated look at how consumers and lenders are leveraging alternative credit data.
It’s been over 10 years since the first rumblings of Great Recession started in 2008. Today, Americans are experiencing high levels of consumer confidence, marked by high employment rates and increasing credit balances over last year. What have we learned over the last decade? And how do we compare to our behaviors then? Experian released the 9th annual state of credit report, which provides a comprehensive look at the credit performance of consumers across America by highlighting consumer credit scores and borrowing behaviors. Who’s faring the best since the recession? According to the data, younger consumers. “We’re continuing to see the positive effects of economic recovery, especially among younger consumers,” said Michele Raneri, Vice President of Analytics and Business Development at Experian. “Since the recession, responsible credit card behaviors and lower debt among younger consumers is driving an upward trend in average credit scores across the nation. Over the last ten years, those 18 – 21 increased their credit scores by 23 points on average compared to those 18-21 ten years ago.” As a whole, 2018 was a year marked by financial reform, consumer protection and the return of volatility for the financial markets. A large portion of the analytics from this year’s report took a close look at the credit behaviors of today and compared them to 2008, the year the US headed into the worst recession in 80 years. 10-Year Lookback 2008 2017 2018 Average number of credit cards 3.40 3.06 3.04 Average credit card balances $7,101 $6,354 $6,506 Average number of retail credit cards 3.03 2.48 2.59 Average retail credit card balances $1,759 $1,841 $1,901 Average VantageScore[1,2] 685 675 680 Average revolving utilization 28% 30% 30% Average non-mortgage debt $23,929 $24,706 $25,104 Average mortgage debt $191,357 $201,811 $208,180 Average 30 days past due delinquency rates 5.4% 4.0% 3.9% Average 60 days past due delinquency rates 2.9% 1.9% 1.9% Average 90+ days past due delinquency rates 7.1% 7.3% 6.7% In regards to credit scores, the average VantageScore increased 5 points from last year, reaching 680 , while still down from 2008. Segmented by state and gender, Minnesota had the highest credit scores for both men and women. Data also showed that women had higher credit scores than men, consistent with 2017 and 2008. The past year has been flooded with headlines illustrating increased spending for American consumers. How do the numbers compare with 2008 data? In comparison with 10 years ago, the number of retail trades since 2008 are down, while average balance is up, according to Experian’s State of Credit Report. Additionally, the number of credit cards is down for all age groups, and balance is also down for consumers 22-71 years of age. Average revolving utilization has creeped up in the past decade, but only two percentage points from 28% to 30%, while both average non-mortgage and mortgage debt has increased 5% and 9% respectively. Not surprisingly, the report reflects that delinquency rates have also increased over 20% since 2008, though down from last year. In conclusion, there’s a lot to learn from both 2008 and 2018. One of the most important and resonating takeaways might be that while fortune may not seem to favor the young, younger consumers are exhibiting responsible behaviors and higher credit scores, setting a precedence for consistent and better financial health in the future. Learn more Experian Boost can help consumers instantly improve their credit score by incorporating their positive payment history from utility and phone bills, among other consumer-permissioned data. [1] VantageScore is a registered trademark of VantageScore Solutions, LLC. [2] VantageScore range is 300-850 VantageScore Calculated on the VantageScore 3.0 model. Your VantageScore 3.0 from Experian indicates your credit risk level and is not used by all lenders, so don’t be surprised if your lender uses a score that’s different from your VantageScore 3.0.
Day 2 at this year’s Vision conference was fueled with new technology and inspiration. The morning session opened with Robert Boxberger, Experian President, Decision Analytics, and also featured two live demos, one on Experian’s solution for the upcoming CECL compliance deadline and the second for mobile credit, including two use cases on instant issuance and lead generation, which has resulted in a 28% conversion rate of hot leads for one of Experian’s marquee clients. Keynote Speaker: Aimée Mullins \"Get comfortable with the uncomfortable\" was just one of the mantras shared on Tuesday morning by Aimée Mullins, an actor, Olympian, TEDTalk speaker, and one of the youngest honorees to be inducted into the National Women’s Hall of Fame, among many other accomplishments. “It is our uniqueness that’s our greatest asset that we can leverage for our greatest strength,” said Mullins during her keynote centered on achieving the “impossible.” As a bi-lateral amputee (or “double BK” also known as double below-the-knee amputee, as she referenced), Mullins had doctors and experts tell her and her parents what she would not be able to do. Instead, she encouraged Tuesday’s audience to never stop thinking like a child, to use their curiosity to find new ways where you want to go, and to practice curiosity like a sport to keep from getting comfortable, and therefore static. “It made my not knowing what I can do so much more powerful than an expert\'s presumption of what he thought I could do,” she said. Session Highlights – Day 2 Consumer Trust What engenders trust as consumers? And what does it take to build online trust? With 51% of new account fraud victims personally knowing the perpetrator and 3.4 billion total losses from fraudulent account openings (Javelin Feb 2019), there are five key components to building trust: digital adoption, transparency, fraud management, recognition and authentication. Today’s consumers want to use the digital channel, have both security and ease of access, be recognized, know how their personal information is being used, and engage and trust with biometrics. Artificial Intelligence – Chat Bots and Beyond According to Gartner, “\'Conversational AI-first\' will supersede ‘cloud-first,’ ‘mobile first’ as the most important high-level imperative for the next 10 years.” As evidenced by Google Duplex’s realistic conversations with humans, including the use of “uh” and “um,” conversational AI is positioned to redefine the next generation of human interface, aimed at achieving better customer satisfaction and elevate the customer relationship. Marketing Analytics The marketing analytics landscape is changing. Today’s marketing problems – including the always limited budget and need to produce greater ROI – require tactical strategies to target the right consumers. Enter Experian’s AscendTM marketing platform. Leveraging this tool, including its neural networks that were demonstrated Monday morning, helps gain new insights into consumer behavior. Fraud in the Digital Wild West A panel discussion featuring representatives from Merchant Risk Council, USAA and Alliance Data compared fighting fraud to herding cats. Challenges discussed included the ongoing struggle to find balance between limiting friction during the authentication process, while also protecting customers, as well as fraudsters’ tendencies to tap into victims’ emotions and curiosity (think phishing schemes). As one of the panelists offered as a piece of advice, “Fraudsters share best practices, so should we.” Visibility for the Invisibles People are more than the sum of their parts. The traditional credit score may show a consumer’s reputation, but layering trended and alternative data sets adds their character. Not only can trended data and alternative credit data – including leveraging education attributes – make invisible consumers visible, they can also reveal that a consumer with a presumably superlative credit score is actually a “credit zombie.” These data sets enable the opportunity to create first chances, drive second chances and re-evaluate risk, while also driving a strong growth strategy. CECL After reviewing the basics of CECL and the upcoming deadlines (ranging from Q1 2020 to Q1 2022), a review of CECL compliance challenges and potential product changes preceded a modeling techniques case study and a list of key impacts to businesses. Those impacts include: product profitability, loss forecasting methodology, data management and processes and capital ratios. Experian’s CECL forecasting solution leverages Experian’s extensive historical data and Ascend Analytical Sandbox. Using a best practice modeling pipeline to improve efficiency and reduce operational risks, the solution combines advanced machine learning, traditional model techniques and modeling experience to improve performance and reduce risk of overfitting. Keynote Speaker: Kobe Bryant Kobe Bryant closed out the day with stories from his highly-decorated 20-year career with the Los Angeles Lakers, some tips on trash talk and lessons in leadership. “I had to figure out how to be undeniable,” Bryant said, on competing for minutes at the start of his career. In addition to his basketball legacy, including wining five NBA championships, being named an NBA MVP, a two-time NBA Finals MVP and winning two Olympic gold medals, Bryant also launched the Kobe and Vanessa Bryant Family Foundation, hosts the Kobe Academy and has formed Kobe Inc. He’s a storyteller, an Oscar winner, and his name has become synonymous with standing for uncompromising excellence. How to be successful? “Make sure you have the right people on the team,” Bryant said. “Passionate. Borderline obsessive.” One of his key takeaways from his basketball career that translates to his leadership on and off the court happened when his pre-game and game time thinking shifted from internal to external. “You have to put yourself 2nd, 3rd, 4th…you have to put the team first,” Bryant said. For more coverage, follow #ExperianVision on Twitter or check the Experian Insights LinkedIn page.
“Experian is transforming our business from a traditional credit bureau to a true technology and software provider,” said Craig Boundy, CEO of Experian, North America, as part of his opening remarks Monday morning to kick off the 2019 Experian Vision Conference. “We are committed to working as a force of good.” Covering the themes of financial inclusion, giving consumers control of their lives and better outcomes, a digital-first society, and the latest trends in fraud and security, Boundy addressed a crowd of over 850. Alex Lintner, Experian’s Group President, gave a quick history of the past 3,000 years, from the first credit card, to the addition of wheels to a suitcase, to the iPhone and artificial intelligence. “Innovation is not invention,” Lintner said. He gave the example of the iPhone and how a tear down analysis revealed there were no new elements; however, it was the translation of an idea into a good or service that benefited everyone (as the entire audience raised their hand when asked who had a smart phone). Lintner’s mainstage presentation also featured three live demos, including how the Ascend Technology Platform takes complex model building and outputs from days and weeks to a few clicks, to the incorporation of Small Business Financial Exchange (SBFE) data into the Ascend Analytical Sandbox (incorporating more than 17 years of small business tradeline data and 150 predictive attributes) and lastly, Experian Boost, which according to a live tracker, has boosted consumer credit scores by a total of 3.2 million points, as of this morning, since its launch eight weeks ago. Keynote Speaker: Gary D. Cohn Gary D. Cohn, Former Director of the U.S. National Economic Council, was Monday morning’s keynote speaker. He weighed in on the domestic and global economy, policy issues, financial institutions’ responsibilities and some of his predictions. Cohn brought attention to the ever-changing financial services space, including new forms of encryption and the world of biometric security, calling the financial services industry the “tip of the spear” when it comes to the digitization of the world. Session Highlights - Day 1 Machine Learning From the building blocks of neural networks to artificial intelligence, machine learning has been used in the areas of financial services that do not have adverse actions – think fraud, ID, collections. As we look to harness machine learning for models and other spaces (including adverse action), it’s important to delineate descriptive data (what’s happening now); predictive data (what’s happening in the future); prescriptive data (what am I going to do now); and cognitive data (are we asking the right question?). In addition, it’s necessary to address the five advanced analytic drivers including customer experience, cost, risk and loss, growth and compliance. Home Equity & Lending US macroeconomic trends show consumer confidence is still on an upward trend. While investor confidence is a little volatile, the GDP remains strong (though slightly slowing down) and unemployment is low and forecasted to remain low. Since 2006, the US hasn’t returned in the HELOC space. Mortgage and personal loans are up 20% and 13% respectively, while mortgages have dropped 1% and HELOCs have dropped 2%. With an estimated market potential of over $700 billion, HELOCs may be an untapped credit line given the strength of the economy. Identity Evolution From dumpster divers, aka pulling receipts out of dumpsters behind businesses, to today’s identity-based authentication, there’s been an evolution of how identity is defined as well as its corresponding risks. According to Experian’s Global Fraud & Identity Report, 74% of consumers value security as the most important part of the online experience (over convenience and personalization). However, 74% of consumers abandoned a shopping session that required too much information, and 72% of consumers said they were willing to share more data if it meant a seamless experience. What does this mean? Consumers want it all. Identity today now includes proxies and activity, which can also mean greater risk. Because of aggregators and other associated entities acting on a consumer’s behalf, there are lots of nuances that will need to be looked through. Consumer-Permissioned Data In order to be more consumer-centric, there are four levers through which consumers are given control: data accuracy, knowing their financial profile, the ability to improve their scores (via Experian BoostTM and UltraFICOTM) and protecting consumers when they permission access to their identity credentials. Using Experian Boost, consumers have seen an average increase of 13 points for consumers with positive changes. Additionally, using alternative credit data, financial institutions can score more people and score more accurately. One hundred million consumers could gain greater access to credit with consumer-permissioned data sources. --- Meanwhile, the tech showcase featured over 20 demos covering alternative data, digital credit marketing, consumer empowerment, fraud and identity, integrated decisioning and technology. More insights from Vision to come. Follow @ExperianVision and #ExperianVision on Twitter to see more of the action.
Your consumers’ credit score plays an important role in how lenders and financial institutions measure their creditworthiness and risk. With a good credit score, which is generally defined as a score of 700 or above, they can quickly be approved for credit cards, qualify for a mortgage, and have easier access to loans with lower interest rates. In the spirit of Financial Literacy Month, we’ve rounded up what it takes for consumers to have a good credit score, in addition to some alternative considerations. Pay on Time Life gets busy and sometimes your consumers miss the “credit card payment due” note on their calendar squished between their work meetings and doctor’s appointment. However, payment history is one of the top factors in most credit scoring models and accounts for 35% of their credit score. As the primary objective of your consumers’ credit score is to illustrate to lenders just how likely they are to repay their debts, even one missed payment can be viewed negatively when reviewing their credit history. However, if there is a missed payment, consider checking their alternative financial services payments. They may have additional payment histories that will skew their creditworthiness more so than just their record according to traditional credit lines alone. Limit Credit Cards When your consumers apply for a new loan or credit card, lenders “pull” their credit report(s) to review their profile and weigh the risk of granting them credit or loan approval. The record of the access to their credit reports is known as a “hard” inquiry and has the potential to impact their credit score for up to 12 months. Plus, if they’re already having trouble using their card responsibly, taking on potential new revolving credit could impact their balance-to-limit ratio. For your customers that may be looking for new cards, Experian TAPSSM can be used to accurately estimate your consumers spend on all general-purpose credit and charge cards, so you can identify where there is additional wallet share and assign their credit lines based on actual spending need. Have a Lengthy Credit History The longer your consumers’ credit history, the more time they’ve spent successfully managing their credit obligations. When considering credit age, which makes up 21% of their credit score, credit scoring models evaluate the ages of your consumers’ oldest and newest accounts, along with the average age of all their accounts. Every time they open new credit cards or close an old account, the average age of their credit history is impacted. If your consumer’s score is being negatively affected by their credit history, consider adding information from alternative credit data sources for a more complete view. Manage Debt Wisely While some types of debt, such as a mortgage, can help build financial health, too much debt may lead to significant financial problems. By planning, budgeting, only borrowing when it makes sense, and setting themselves up for unexpected financial expenses, your consumers will be on the path to effective debt management. To get a better view of your consumers spending, consider Experian’s Trended3DTM, a trended attribute set that helps lenders unlock valuable insights hidden within their consumers’ credit scores. By using Trended3DTM data attributes, you’ll be able to see how much of your consumers’ credit line they typically utilize, whether they tend to revolve or transact, and if they are likely to transfer a balance. By adopting these habits and making smart financial decisions, your consumers will quickly realize that it’s never too late to rebuild their credit score. For example, they can potentially instantly improve their score with Experian Boost, an online tool that scans their bank account transactions to identify mobile phone and utility payments. The positive payments are then added to their Experian credit file and increase their FICO® Score in real time. Learn More About Experian Boost Learn More About Experian TAPS
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