Data & Analytics

To provide consumers with clear-cut protections against disturbance by debt collectors, the Consumer Financial Protection Bureau (CFPB) issued a Notice of Proposed Rulemaking (NPRM) to implement the Fair Debt Collection Practices Act (FDCPA) earlier this year. Among many other things, the proposal would set strict limits on the number of calls debt collectors may place to reach consumers weekly and clarify requirements for consumer-facing debt collection disclosures. A bigger discussion Deliberation of the debt collection proposal was originally scheduled to begin on August 18, 2019. However, to allow commenters to further consider the issues raised in the NPRM and gather data, the comment period was extended by 20 days to September 18, 2019. It is currently still being debated, as many argue that the proposed rule does not account for modern consumer preferences and hinders the free flow of information used to help consumers access credit and services. The Association of Credit and Collection Professionals (ACA International) and US House lawmakers continue to challenge the proposal, stating that it doesn’t ensure that debt collectors’ calls to consumers are warranted, nor does it do enough to protect consumers’ privacy. Many consumer advocates have expressed doubts about how effective the proposed measures will be in protecting debtors from debt collector harassment and see the seven-calls-a-week limit on phone contact as being too high. In fact, it’s difficult to find a group of people in full support of the proposal, despite the CFPB stating that it will help clarify the FDCPA, protect lenders from litigation and bring consumer protection regulation into the 21st century. What does this mean? Although we don’t know when, or if, the proposed rule will go into effect, it’s important to prepare. According to the Federal Register, there are key ways that the new regulation would affect debt collection through the use of newer technologies, required disclosures and limited consumer contact. Not only will the proposed rules apply to debt collectors, but its provisions will also impact creditors and servicers, making it imperative for everyone in the financial services space to keep watch on the regulation’s status and carefully analyze its proposed rules. At Experian, our debt collection solutions automate and moderate dialogues and negotiations between consumers and collectors, making it easier for collection agencies to connect with consumers while staying compliant. Our best-in-class data and analytics will play a key role in helping you reach the right consumer, in the right place, at the right time. Learn more

Retail banking leaders in a variety of industries (including risk management, credit, information technology and other departments) want to incorporate more data into their business strategies. By doing so, consumer banks and other financial companies benefit by expanding their markets, controlling risk, improving compliance and the customer experience. However, many companies don’t know how or where to start. The challenges? There’s just too much data – and it’s overwhelming. Technical integration issues Maintaining regulatory data and attribute governance and compliance The slow speed of adoption Join Jim Bander, PhD, analytics and optimization leader at Experian, in an upcoming webinar with the Consumer Bankers Association on Tuesday, Oct. 1, 2019 at 9:00-10:00 a.m. PT. The webinar will discuss how some of the country’s best banks – big and small – are making better, faster and more profitable decisions by using the right set of data sources, while avoiding data overload. Key topics will include: Technology Trends: Discover how the latest technology, including the cloud and machine learning, makes it easier than ever to access data, define and manage attributes throughout the enterprise and perform complex calculations in real time. Time to Market: Discover how consumer banks and other financial companies that have mastered data and attribute management are able to integrate data and attributes quickly and seamlessly. Business Benefits: Understand how advanced analytics helps financial institutions of all sizes make better business decisions. This includes growing their portfolios, mitigating fraud and credit risk, controlling operating expenses, improving compliance and enhancing the customer experience. Critical Success Factors: Learn how to stay ahead of ever-evolving business and data requirements and continuously improve your lending operations. Join us as we unveil the secrets to avoiding data overload in consumer banking. Special Offer For non-current CBA members, this webinar costs $95 to attend. However, with special discount code: EX1001, non-CBA members can attend for FREE. Register Now

The average new vehicle loan hit $32,119 in Q2 2019. Average used vehicle loan amounts reached $20,156 in Q2 2019.

The future is, factually speaking, uncertain. We don't know if we'll find a cure for cancer, the economic outlook, if we'll be living in an algorithmic world or if our work cubical mate will soon be replaced by a robot. While futurists can dish out some exciting and downright scary visions for the future of technology and science, there are no future facts. However, the uncertainty presents opportunity. Technology in today's world From the moment you wake up, to the moment you go back to sleep, technology is everywhere. The highly digital life we live and the development of our technological world have become the new normal. According to The International Telecommunication Union (ITU), almost 50% of the world's population uses the internet, leading to over 3.5 billion daily searches on Google and more than 570 new websites being launched each minute. And even more mind-boggling? Over 90% of the world's data has been created in just the last couple of years. With data growing faster than ever before, the future of technology is even more interesting than what is happening now. We're just at the beginning of a revolution that will touch every business and every life on this planet. By 2020, at least a third of all data will pass through the cloud, and within five years, there will be over 50 billion smart connected devices in the world. Keeping pace with digital transformation At the rate at which data and our ability to analyze it are growing, businesses of all sizes will be forced to modify how they operate. Businesses that digitally transform, will be able to offer customers a seamless and frictionless experience, and as a result, claim a greater share of profit in their sectors. Take, for example, the financial services industry - specifically banking. Whereas most banking used to be done at a local branch, recent reports show that 40% of Americans have not stepped through the door of a bank or credit union within the last six months, largely due to the rise of online and mobile banking. According to Citi's 2018 Mobile Banking Study, mobile banking is one of the top three most-used apps by Americans. Similarly, the Federal Reserve reported that more than half of U.S. adults with bank accounts have used a mobile app to access their accounts in the last year, presenting forward-looking banks with an incredible opportunity to increase the number of relationship touchpoints they have with their customers by introducing a wider array of banking products via mobile. Be part of the movement Rather than viewing digital disruption as worrisome and challenging, embrace the uncertainty and potential that advances in new technologies, data analytics and artificial intelligence will bring. The pressure to innovate amid technological progress poses an opportunity for us all to rethink the work we do and the way we do it. Are you ready? Learn more about powering your digital transformation in our latest eBook. Download eBook Are you an innovation junkie? Join us at Vision 2020 for future-facing sessions like:  -  Cloud and beyond - transforming technologies - ML and AI - real-world expandability and compliance

In today’s age of digital transformation, consumers have easy access to a variety of innovative financial products and services. From lending to payments to wealth management and more, there is no shortage in the breadth of financial products gaining popularity with consumers. But one market segment in particular – unsecured personal loans – has grown exceptionally fast. According to a recent Experian study, personal loan originations have increased 97% over the past four years, with fintech share rapidly increasing from 22.4% of total loans originated to 49.4%. Arguably, the rapid acceleration in personal loans is heavily driven by the rise in digital-first lending options, which have grown in popularity due to fintech challengers. Fintechs have earned their position in the market by leveraging data, advanced analytics and technology to disrupt existing financial models. Meanwhile, traditional financial institutions (FIs) have taken notice and are beginning to adopt some of the same methods and alternative credit approaches. With this evolution of technology fused with financial services, how are fintechs faring against traditional FIs? The below infographic uncovers industry trends and key metrics in unsecured personal installment loans: Still curious? Click here to download our latest eBook, which further uncovers emerging trends in personal loans through side-by-side comparisons of fintech and traditional FI market share, portfolio composition, customer profiles and more. Download now  

Experian has been named one of the 10 participants, and only credit bureau, in the initial rollout of the SSA's new eCBSV service.

Experian Boost provides a unique opportunity to help dealers build loyalty while helping consumers.

What do movie actors Adam Sandler and Hugh Grant, jazz singer Michael Bublé, Russian literary giant Leo Tolstoy, and Colonel Sanders, the founder of KFC, have in common? Hint, it’s not a Nobel Prize for Literature, a Golden Globe, a Grammy Award, a trademark goatee, or a “finger-lickin’ good” bucket of chicken. Instead, they were all born on September 9, the most common birth date in the U.S. Baby Boom According to real birth data compiled from 20 years of American births, September is the most popular month to give birth to a child in America – and December, the most popular time to make one. With nine of the top 10 days to give birth falling between September 9 and September 20, one may wonder why the birth month is so common. Here are some theories: Those who get to choose their child’s birthday due to induced and elective births tend to stay away from the hospital during understaffed holiday periods and may plan their birth date around the start of the school year. Several of the most common birth dates in September correspond with average conception periods around the holidays, where couples likely have more time to spend together. Some studies within the scientific community suggest that our bodies may actually be biologically disposed to winter conceptions. While you may not be feeling that special if you were born in September, the actual differences in birth numbers between common and less common birthdays are often within just a few thousand babies. For example, September 10, the fifth most common birthday of the year, has an average birth rate of 12,143 babies. Meanwhile, April 20, the 328th most common birthday, has an average birth rate of 10,714 newborns. Surprisingly, the least common birthdays fall on Christmas Eve, Christmas Day and New Year’s Day, with Thanksgiving and Independence Day also ranking low on the list. Time to Celebrate – but Watch out! Statistically, there’s a pretty good chance that someone reading this article will soon be celebrating their birthday. And while you should be getting ready to party, you should also be on the lookout for fraudsters attempting to ruin your big day. It’s a well-known fact that cybercriminals can use your birth date as a piece of the puzzle to capture your identity and commit identity theft – which becomes a lot easier when it’s being advertised all over social media. It’s also important for employers to safeguard their organization from fraudsters who may use this information to break into corporate accounts. While sharing your birthday with a lot of people could be a good or bad thing depending on how much undivided attention you enjoy – you’re in great company! Not only can you plan a joint party with Michelle Williams, Afrojack, Cam from Modern Family, four people I went to high school with on Facebook and a handful of YouTube stars that I’m too old to know anything about, but there will be more people ringing in your birthday than any other day of the year! And that’s pretty cool.

Pickups are the most common vehicle in operation at 20% share today and hold 16.5% of new vehicle registrations in the market in Q1 2019.

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.

Big Data, once thought to be overhyped consultant-speak, is now a term and business model so ubiquitous it underpins billions of dollars in revenue across nearly every industry. Similarly, the advanced analytics derived from big data are key to staying relevant in an everchanging global economy and to consumers with expanding expectations. But for many financial institutions, using big data and advanced analytics seemed to only be in reach for big banks with large, advanced data teams. With the expansion of the Experian Ascend Technology PlatformTM, the conversation is changing. Financial institutions of all sizes can now leverage advanced analytics, artificial intelligence and machine learning with new configurations in the award-winning platform. In a release earlier this week, Experian announced new tools and configurations in the Ascend Analytical SandboxTM to fit teams of every size and skill level. Now fintechs, banks and credit unions of every size can have access to Experian’s one-stop source for advanced analytics, business intelligence and ultimately, better decisions. The secure hybrid-cloud environment allows users to combine their own data sets with Experian’s exclusive data assets, including credit, alternative, commercial, auto and more. From there, users can build and test models across different stages of the lending cycle, including originations, prescreen, account management and collections, and seamlessly put their models into production. Experian’s Ascend Analytical Sandbox also allows users to benchmark their portfolios against the industry, identify credit trends and explore new product opportunities. All the insights gathered through the Ascend Analytical Sandbox can be viewed and shared through interactive dashboards and customizable reports that can be pulled in near real time. Additional use cases include: Reject inferencing – refine models, scorecards and strategies by analyzing trades opened by previous applicants who were rejected or approved but did not move forward Prescreen campaigns – design prescreen campaigns, evaluate results and improve strategies Cross-sell – identify cross-sell opportunities for existing customers and identify how they may be working with other lenders Collections strategies, stress testing and loss forecasting – build stronger models to identify customers that have ability and willingness to pay debts, stress test and forecast loss Peer benchmarking and industry trends – compare current portfolio against peers and the industry Recession planning – identify areas to adjust your portfolio to prepare for an economic downturn OneMain Financial, a large provider of personal installment loans serving 10 million total customers across more than 1,700 branches, turned to Experian to improve its risk modeling and credit portfolio management capabilities with the Ascend Analytical Sandbox. Since using the solution, the company has seen significant improvements in reject inferencing – a process that is traditionally expensive, manually-intensive and time consuming. According to OneMain Financial, the Ascend Analytical Sandbox has shortened the process to less than two weeks from up to 180 days. "Experian's Ascend Technology Platform and Analytical Sandbox is an industry gamechanger," said Michael Kortering, OneMain Financial's Senior Managing Director and Head of Model Development. "We're completing analyses that just weren't possible before and we're getting decisions to our clients faster, without compromising risk.” For more information on Ascend Analytical Sandbox SX – the latest solution for financial institutions of all sizes – or other enterprise-wide capabilities of the Experian Ascend Technology Platform, click here.

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.