Tag: data
Account management is a critical strategy during any type of economy (pro-cycle, counter-cycle, cycle neutral). In times like these, marked by economic volatility, it is an effective way to identify which parts of your portfolio and which of your consumers need the most attention. Check out this podcast where Cyndy Chang, Senior Director of Product Management, and Craig Wilson, Senior Director of Consulting, discuss the foundational elements of account management, best practices and use cases. Account management today looks very different than what it has been during over a decade of growth proactive; account review is a critical part of navigating the path forward. Questions that need to be addressed include: Do you have the right data? Are you monitoring between data loads? Are you reviewing accounts at the frequency that today’s changing demands require? Listen in on the discussion to learn more. Experian · Look Ahead Podcast
This is the third in a series of blog posts highlighting optimization, artificial intelligence, predictive analytics, and decisioning for lending operations in times of extreme uncertainty. The first post dealt with optimization under uncertainty and the second with predicting consumer payment behavior. In this post I will discuss how well credit scores will work for consumer lenders during and after the COVID-19 crisis and offer some recommendations for what lenders can be doing to measure and manage that model risk in a time like this. Perhaps no analytics innovation has created opportunity for more individuals than the credit score has. The first commercially available credit score was developed by MDS (now part of Experian) in 1987. Soon afterwards FICO® popularized the use of scores that evaluate the risk that a consumer would default on a loan. Prior to that, lending decisions were made by loan officers largely on the basis on their personal familiarity with credit applicants. Using data and analytics to assess risk not only created economic opportunity for millions of borrowers, but it also greatly improved the financial soundness of lending institutions worldwide. Predictive models such as credit scores have become the most critical tools for consumer lending businesses. They determine, among other things, who gets a loan and at what price and how an account such as a credit line is managed through its life cycle. Predictive models are in many cases critical for calculating loan and loss reserves, for stress testing, and for complying with accounting standards. Nearly all lenders rely on generic scores such as the FICO score and VantageScore®. Most larger companies also have a portfolio of custom scorecards that better predict particular aspects of payment behavior for the customers of interest. So how well are these scorecards likely to perform during and after the current pandemic? The models need to predict consumer credit risk even as: Nearly all consumers change their behaviors in response to the health crisis, Millions of people—in America and internationally—find their income suddenly reduced, and Consumers receive large numbers of accommodations from creditors, who have in turn temporarily changed some of their credit reporting practices in response to guidelines in the federal CARES Act. In an earlier post, I pointed out that there is good reason to believe that credit scores will tend to continue to rank order consumers from most likely to least likely to repay their debts even as we move from the longest economic expansion in history to a period of unforeseen and unexpected challenges. But the interpretation of the score (for example, the log odds or the bad rate) may need to be adjusted. Furthermore, that assumes that the model was working well on a lender’s population before this crisis started. If it has been a long time since a scorecard was validated, that assumption needs to be questioned. Because experts are considering several different scenarios regarding both the immediate and long-term economic impacts of COVID-19, it’s important to have a plan for ongoing monitoring as long as necessary. Some lenders have strong Model Risk Management (MRM) teams complying with requirements from the Federal Reserve, Federal Deposit Insurance Corporation (FDIC), the Office of the Comptroller of the Currency (OCC). Those resources are now stretched thin. Other institutions, with fewer resources for MRM, are now discovering gaps in their model inventories as they implement operational changes. In either case, now’s the time to reassess how well scorecards are working. Good model validation practices are especially critical now if lenders are to continue to make the sound data-driven decisions that promote fairness for consumers and financial soundness for the institution. If you’re a credit risk manager responsible for the generic or custom models driving your lending, servicing, or capital allocation policies, there are several things you can do--starting now--to be sure that your organization can continue to make fair and sound lending decisions throughout this volatile period: Assess your model inventory. Do you have good documentation showing when each of the models in your organization was built? When was it last validated? Assign a level of criticality to each model in use. Starting with your most critical models, perform a baseline validation to determine how the model was performing prior to the global health crisis. It may be prudent to conduct not only your routine validation (verifying that the model was continuing to perform at the beginning of the period) but also a baseline validation with a shortened performance window (such as 6-12 months). That baseline validation will be useful if the downturn becomes a protracted one—in which case your scorecard models should be validated more frequently than usual. A shorter outcome window will allow a timelier assessment of the relationship between the score and the bad rate—which will help you update your lending and servicing policies to prevent losses. Determine if any of your scorecards had deteriorated even before the global pandemic. Consider recalibrating or rebuilding those scorecards. (Use metrics such as the Population Stability Index, the K-S statistic and the Gini Coefficient to help with that decision.) Many lenders chose not to prioritize rebuilding their behavioral scorecards for account management or collections during the longest period of economic growth in memory. Those models may soon be among the most critical models in your organization as you work to maintain the trust of your accountholders while also maintaining your institution’s financial soundness. Once the CARES accommodation period has expired, it will be important to revalidate your models more frequently than in the past—for as long as it takes until consumer behavior normalizes and the economy finds its footing. When you find it appropriate to rebuild a scorecard model, consider whether now is the time to implement ethical and explainable AI. Some of our clients are finding that Machine Learned models are more predictive than traditional scorecards. Early Experian research using data from the last recession indicates this will continue to be true for the foreseeable future. Furthermore, Experian has invested in Research and Development to help these clients deliver FCRA-compliant Adverse Action reasons to their consumers and to make the models explainable and transparent for model risk governance and compliance purposes. The sudden economic volatility that has resulted from this global health crisis has been a shock to all organizations. It is important for lenders to take the pulse of their predictive models now and throughout the downturn. They are especially critical tools for making sound data-driven business decisions until the economy is less volatile. Experian is committed to helping your organization during times of uncertainty. For more resources, visit our Look Ahead 2020 Hub. Learn more
When running a credit report on a new applicant, you must ensure Fair Credit Reporting Act (FCRA) compliance before accessing, using and sharing the collected data. The Coronavirus Aid, Relief, and Economic Security (CARES) Act has impacted credit reporting under the FCRA, as has new guidance from the Consumer Financial Protection Bureau (CFPB). Recent updates include: The CARES Act amended the FCRA to require furnishers who agree to an “accommodation,”1 to report the account as current, although it is permitted to continue to report the account as delinquent if the account was delinquent before the accommodation was made. Although not legally obligated, data furnishers should continue furnishing information to the credit reporting agencies (CRAs) during the COVID-19 crisis, and make sure that information reported is complete and accurate. Below is a brief FCRA-related compliance overview2 covering various FCRA requirements3 when requesting and using consumer credit reports for an extension of credit permissible purpose. For more information regarding your responsibilities under the FCRA as a user of consumer reports, please consult your Legal Counsel and the Notice to Users of Consumer Reports: Obligations of Users Under the FCRA handbook located on our website. Before obtaining a consumer report you have… Reviewed your federal and state regulations and laws related to consumer reports, scores, decisions, etc. Made sure you have a valid permissible purpose for pulling the consumer report. Certified compliance to the CRA from which you are getting the consumer report. You have certified that you complied with all the federal and state requirements. After you take an adverse action based on a consumer report you… Provide the consumer with an oral, written or electronic notice of the adverse action. Provide written or electronic disclosure of the numerical credit score used to take the adverse action, or when providing a “risk-based pricing” notice. Provide the consumer with an oral, written or electronic notice, which includes the below information: Name, address and telephone number of CRA that supplied the report, if nationwide. A statement that the CRA did not make the adverse decision and therefore can’t explain why the decision was made. Notice of the consumer’s right to a free copy of their report from the CRA, if requested within 60 days. Notice of the consumer’s right to dispute with the CRA the accuracy or completeness of any information in a consumer report provided by the CRA. Provide the consumer with a “risk-based pricing” notice if credit was granted but on less favorable terms based on information in their consumer report. We understand how challenging it is to understand and meet all your obligations as a data furnisher – we’re here to make it a little easier. Click below to speak with a representative and gain more insight on how the CARES Act impacts FCRA reporting. Download overview Speak with a representative 1An “accommodation” is defined as “an agreement to defer one or more payments, make a partial payment, forbear any delinquent amounts, modify a loan or contract, or any other assistance or relief” granted to a consumer affected by COVID-19 during the covered period. 2This FCRA overview is not legal guidance and does not enumerate all your requirements under the FCRA as a user of consumer reports. Additionally, this FCRA Overview is not intended to provide legal advice or counsel you regarding your obligations under the FCRA or any other federal or state law or regulation. Should you have any questions about your institution’s specific obligations under the FCRA or any other federal or state law or regulation, you should consult with your Legal Counsel. 3This FCRA overview is intended to be used solely by financial service providers when extending credit to consumers and does not include all FCRA regulatory obligations. You are responsible for regulatory compliance when requesting and using consumer reports, which includes adhering to all applicable federal and state statutes and regulations and ensuring that you have the correct policies and procedures in place.
Last week, the unemployment rate soared past 20%, with over 30 million job losses attributed to the COVID-19 pandemic. As a result, many consumers are facing financial stress, which has raised many questions and discussions around how credit history and reporting should be treated at this time. Since the initial start of the pandemic, credit reporting companies and data furnishers have been put under the spotlight to ensure that consumers are able to get the assistance that they need. Numerous questions and concerns have also been raised around the extent of which consumers have access to fair and affordable credit. On March 27th, 2020, Congress signed the Coronavirus Aid, Relief, and Economic Security (CARES) Act into law, which was a bill created to provide support and relief for American workers, families, and small businesses. This newly proposed Act also provides guidelines on how creditors and data furnishers should report information to credit bureaus, to ensure that lenders remain flexible as consumers navigate the current pandemic. The Act requires that creditors must provide “accommodations” to consumers affected by COVID-19 during “covered periods.” According to the National Credit Union Administration, “The CARES Act requires credit reporting agency data providers, including credit unions, to report loan modifications resulting from the COVID-19 pandemic as ‘current’ or as the status reported before the accommodation unless the consumer becomes current,” as stated in Section 4021. Section 4021 of the CARES Act also provides other guidelines for accurate data reporting. During this time, lenders can use attributes to determine risk during COVID-19. Attributes within custom scores can also capture consumer behavior and help lenders determine the best treatments. Payment attributes, debt burden attributes, inquiry attributes, credit extensions and originations are all key indicators to keep an eye on at this time as lenders monitor risk in their portfolios. Listen in as our panel of experts explore the areas related to data reporting that impact you the most. In addition to a regulatory update and discussions around programs to help support consumers and businesses, we’ll also review what other lenders are doing and early indicators of credit trends. You’ll also be able to walk away with key strategies around what your organization can do right now. Discover the latest information on: Data reporting and CDIA regulations Regulatory updates, including the CARES Act, a breakdown of Section 4021, and guidelines to remember Credit attribute trends and highlights, treatment of scores and attributes, as well as recommended attributes Watch the webinar
The coronavirus (COVID-19) outbreak is causing widespread concern and economic hardship for consumers and businesses across the globe – including financial institutions, who have had to refine their lending and downturn response strategies while keeping up with compliance regulations and market changes. As part of our recently launched Q&A perspective series, Shannon Lois, Experian’s Head of DA Analytics and Consulting and Bryan Collins, Senior Product Manager, tackled some of the tough questions for lenders. Here’s what they had to say: Q: What trends and triggers should lenders be prepared to react to? BC: Lenders are still trying to figure out how to assess risk between the broader, longer-term impacts of the pandemic and the near-term Coronavirus Aid, Relief, and Economic Security (CARES) Act that extends relief funds and deferment to consumers and small businesses. Traditional lending processes are not possible, lenders will have to adjust underwriting strategies and workflows as they deploy hardship programs while complying with the Act. From a utilization perspective, lenders need to look for near-term trends on payments, balances and skipped payments. From an extension standpoint, they should review limits extended or reduced by other lenders. Critical trends to look for would be missed or late auto payments, non-traditional credit shopping and rental payment delinquencies. Q: What should lenders be doing to plan for an uptick in delinquencies? SL: First, lenders should make sure they have a complete picture of how credit risk and losses are evolving, as well as any changes to their consumers’ affordability status. This will allow a pointed refinement of their customer management strategies (I.e. payment holidays, changing customer to cheaper product, offering additional services, re-pricing, term amendment and forbearance management.) Second, given the increased stress on collection processes and regulations guidelines, they should ensure proper and prepared staffing to handle increased call volumes and that agency outsourcing and automation is enabled. Additionally, lenders should migrate to self-service and interactive communication channels whenever possible while adopting new segmentation schemas/scores/attributes based on fresh data triggers to queue lower risk accounts entering collections. Q: How can lenders best help their customers? SL: Lenders should understand customers’ profiles with vulnerability and affordability metrics allowing changes in both treatment and payment. Payment Holidays are common in credit card management, consider offering payment freezes on different types of credit like mortgage and secured loans, as well as short term workout programs with lower interest rates and fee suppression. Additionally, lenders should offer self-service and FAQ portals with information about programs that can help customers in times of need. BC: Lenders can help by complying with aspects of the CARES Act guidance; they must understand how to deploy payment relief and hardship programs effectively and efficiently. Data integrity and accuracy of loan reporting will be critical. Financial institutions should adjust their collection and risk strategies and processes. Additionally, lenders must determine a way to address the unbanked population with relief checks. We understand how challenging it is to navigate the changing economic tides and will continue to offer support to both businesses and consumers alike. Our advanced data and analytics can help you refine your lending processes and better understand regulatory changes. Learn more About Our Experts: Shannon Lois, Head of DA Analytics and Consulting, Experian Data Analytics, North America Shannon and her team of analysts, scientists, credit, fraud and marketing risk management experts provide results-driven consulting services and state-of-the-art advanced analytics, science and data products to clients in a wide range of businesses, including banking, auto, credit, utility, marketing and finance. Shannon has been a presenter at many credit scoring and risk management conferences and is currently leading the Experian Decision Analytics advisory board. Bryan Collins, Senior Product Manager, Experian Consumer Information Services, North America Bryan is a member of Experian\'s CIS product management team, focusing on the Acquisitions suite and our evolving Ascend Identity Services Platform. With more than 20 years of experience in the financial services and credit industries, Bryan has established strong partnerships and a thorough understanding of client needs. He was instrumental in the launch of CIS\'s segmentation suite and led product management for lender and credit-related initiatives in Auto. Prior to joining Experian, Bryan held marketing and consumer experience roles in consumer finance, business lending and card services.
As financial institutions and other organizations scramble to formulate crisis response plans, it’s important to consider the power of data and analytics. Jim Bander, PhD, Experian’s Analytics and Optimization Market Lead discusses the ways that data, analytics and models can help during a crisis. Check out what he had to say: What implications does the global pandemic have on financial institutions’ analytical needs? JB: COVID-19 is a humanitarian crisis, one that parallels Hurricanes Sandy and Katrina and other natural disasters but which far exceeds their magnitude. It is difficult to predict the impact as huge parts of the global economy have shut down. Another dimension of this disaster is the financial impact: in the US alone, more than 17 million people applied for unemployment in the first 6 weeks of the COVID-19 crisis. That compares to 15 million people in 18 months during the Great Recession. Data and analytics are more important than ever as financial institutions formulate their responses to this crisis. Those institutions need to focus on three key things: safety, soundness, and compliance. Safety: Financial institutions are taking immediate action to mitigate safety risks for their employees and their customers. Soundness: Organizations need to mitigate credit and fraud risk and to evaluate capital and liquidity. Some executives may need a better understanding of how their bank’s stress scenarios were calculated in the past to understand how they must be updated for the future. Important analytic functions include performing portfolio monitoring and benchmarking—quantifying the effects not only of consumer distress, but also of low interest rates. Compliance: Understanding and meeting complex regulatory and compliance requirements is crucial at this time. Companies have to adapt to new credit reporting guidelines. CECL requirements have been relaxed but lenders should assess the effects of COVID, and not only during their annual stress tests. As more consumers seek credit, from an analytics perspective, what considerations should financial institutions make during this time? JB: During this volatile time, analytics will help financial institutions: Identify financially stressed consumers with early warning indicators Predict future consumer behavior Respond quickly to changes Deliver the best treatments at the right time for individual customers given their specific situations and their specific behavior. Financial institutions should be reevaluating where their organizations have the most vulnerability and should be taking immediate action to mitigate these risks. Some important areas to keep an eye on include early warning indicators, changes in fraudulent behavior (with the increase in digital engagements), and changes in customer behavior. Banks are already offering payment flexibility, deferments, and credit reporting accommodations. If volatility continues or increases, they may need to offer debt forgiveness plans. These organizations should also be prepared to understand their own changing constraints—such as budget, staffing levels, and liquidity requirements— especially as consumers accelerate their move to digital channels. In the near future, lenders should be optimizing their operations, servicing treatments, and lending policies to meet a number of possibly conflicting objectives in the presence of changing constraints and somewhat unpredictable transaction volumes. What is the smartest next play for financial institutions? JB: I see our smartest clients doing four things: Adapting to the new normal Maintaining engagement with existing customers by refreshing data that companies have on-hand for these consumers, and obtain additional views of these customers for analytics and data-driven decisioning Reallocating operational resources and anticipating the need for increased capacity in various servicing departments in the future Improving their risk management practices What is Experian doing to help clients improve their risk management? JB: During this time, banks and other financial institutions are searching for ways to predict consumer behavior, especially during a crisis that combines aspects of a natural disaster with characteristics of a global recession. It is more important than ever to use analytics and optimization. But some of the details of the methodology is different now than during a time of economic expansion. For example, while credit scores (like FICO® and VantageScore®) will continue to rank consumers in terms of their probability to pay, those scores must be interpreted differently. Furthermore, those scores should be combined with other views of the consumer—such as trends in consumer behavior and with expanded FCRA-compliant data (data that isn’t reported to traditional credit bureaus). One way we’re helping clients improve their credit risk management is to provide them with a list of 140 consumer credit data attributes in 10 categories. With this list, companies will be able to better manage portfolio risk, to better understand consumer behavior, and to select the next best action for each consumer. Four other things we’re doing: We’re quickly updating our loss forecasting and liquidity management offerings to account for new stress scenarios. We’re helping clients review their statistical models’ performance and their customer segmentation practices, and helping to update the models that need refreshing. Our consulting team—Experian Advisory Services—has been meeting with clients virtually--helping them update, execute their crisis and downturn responses, and whiteboard new or updated tactical plans. Last but not least, we’re helping lenders and consumers defend themselves against a variety of fraud and identity theft schemes. Experian is committed to helping your organization during these uncertain times. For more resources, visit our Look Ahead 2020 Hub. Learn more Jim Bander, PhD, Analytics and Optimization Market Lead, Decision Analytics, Experian North America Jim Bander, PhD joined Experian in April 2018 and is responsible for solutions and value propositions applying analytics for financial institutions and other Experian business-to-business clients throughout North America. Jim has over 20 years of analytics, software, engineering and risk management experience across a variety of industries and disciplines. He has applied decision science to many industries including banking, transportation and the public sector. He is a consultant and frequent speaker on topics ranging from artificial intelligence and machine learning to debt management and recession readiness. Prior to joining Experian, he led the Decision Sciences team in the Risk Management department at Toyota Financial Services.
This is the second in a series of blog posts highlighting optimization, artificial intelligence, predictive analytics, and decisioning for lending operations in times of extreme uncertainty. The first post dealt with optimization under uncertainty. The word \"unprecedented\" gets thrown around pretty carelessly these days. When I hear that word, I think fondly of my high school history teacher. Mr. Fuller had a sign on his wall quoting the philosopher-poet George Santayana: \"Those who cannot remember the past are condemned to repeat it.\" Some of us thought it meant we had to memorize as many facts as possible so we wouldn\'t have to go to summer school. The COVID-19 crisis--with not only health consequences but also accompanying economic and financial impacts--certainly breaks with all precedents. The bankers and other businesspeople I\'ve been listening to are rightly worried that This Time is Different. While I\'m sure there are history teachers who can name the last time a global disaster led to a widescale humanitarian crisis and an economic and financial downturn, I\'m even more sure times have changed a lot since then. But there are plenty of recent precedents to guide business leaders and other policymakers through this crisis. Hurricanes Katrina and Sandy impacted large regions of the United States, with terrible human consequences followed by financial ones. Dozens of local disasters—floods, landslides, earthquakes—devastated smaller numbers of people in equally profound ways. The Great Recession, starting in 2008, put millions of Americans and others around the world out of work. Each of those disasters, like this one, broke with all precedents in various ways. Each of those events was in many ways a dress rehearsal, as bankers and other lenders learned to provide assistance to distressed businesses and consumers, while simultaneously planning for the inevitable changes to their balance sheets and income statements. Of course, the way we remember the past has changed. Just as most of us no longer memorize dates--we search for them on the web--businesspeople turn to their databases and use analytics to understand history. I\'ve been following closely as the data engineers and data scientists here at Experian have worked on perhaps their most important problem ever. Using Experian\'s Ascend Analytical Sandbox--named last year as the Best Overall Analytics Platform, they combed through over eighteen years of anonymized historical data covering every credit report in the United States. They asked--using historical experience, wisdom, time-consuming analytics, a little artificial intelligence, and a lot of hard work--whether predicting credit performance during and after a crisis is possible. They even considered scenarios regarding what happens as creditors change the way they report consumer delinquencies to the credit bureaus. After weeks of sleepless nights, they wrote down their conclusions. I\'ve read their analysis carefully and I’m pleased to report that it says…Drumroll, please…Yes, but. Yes, it\'s possible to predict consumer behavior after a disaster. But not in precisely the same way those predictions are made during a period of economic growth. For a credit risk manager to review a lending portfolio and to predict its credit losses after a crisis requires looking at more data--and looking at it a little differently--than during other periods. Yes, after each disaster, credit scores like FICO® and VantageScore® continued to rank consumers from most likely to least likely to repay debts. But the interpretation of the score changes. Technically speaking, there is a substantial shift in the odds ratio that is particularly pronounced when a score is applied to subprime consumers. To predict borrower behavior more accurately, our scientists found that it helps to look at ten additional categories of data attributes and a few additional types of mathematical models. Yes, there are attributes on the credit report that help lenders identify consumer distress, willingness, and ability to pay. But, the data engineers identified that during times like these it is especially helpful to look beyond a single point in time; trends in a consumer\'s payment history help understand whether that customer is changing their typical behavior. Yes, the data reported to the credit bureaus is predictive, especially over time. But when expanded FCRA data is available beyond what is traditionally reported to a bureau, that data further improves predictions. All told, the data engineers found over 140 data attributes that can help lenders and others better manage their portfolio risk, understand consumer behavior, appreciate how the market is changing, and choose their next best action. The list of attributes might be indispensable to a credit data specialist whose institution needs to weather the coming storm. Because Experian knows how important it is to learn from historical precedents, we\'re sharing the list at no charge with qualified risk managers. To get the latest Experian data and insights or to request the Crisis Response Attributes recommendation, visit our Look Ahead 2020 page. Learn more
With new legislation, including the Coronavirus Aid, Relief, and Economic Security (CARES) Act impacting how data furnishers will report accounts, and government relief programs offering payment flexibility, data reporting under the coronavirus (COVID-19) outbreak can be complicated. Especially when it comes to small businesses, many of which are facing sharp declines in consumer demand and an increased need for capital. As part of our recently launched Q&A perspective series, Greg Carmean, Experian’s Director of Product Management and Matt Shubert, Director of Data Science and Modelling, provided insight on how data furnishers can help support small businesses amidst the pandemic while complying with recent regulations. Check out what they had to say: Q: How can data reporters best respond to the COVID-19 global pandemic? GC: Data reporters should make every effort to continue reporting their trade experiences, as losing visibility into account performance could lead to unintended consequences. For small businesses that have been negatively affected by the pandemic, we advise that when providing forbearance, deferrals be reported as “current”, meaning they should not adversely impact the credit scores of those small business accounts. We also recommend that our data reporters stay in close contact with their legal counsel to ensure they follow CARES Act guidelines. Q: How can financial institutions help small businesses during this time? GC: The most critical thing financial institutions can do is ensure that small businesses continue to have access to the capital they need. Financial institutions can help small businesses through deferral of payments on existing loans for businesses that have been most heavily impacted by the COVID-19 crisis. Small Business Administration (SBA) lenders can also help small businesses take advantage of government relief programs, like the Payment Protection Program (PPP), available through the CARES Act that provides forgiveness on up to 75% of payroll expenses and 25% of other qualifying expenses. Q: How do financial institutions maintain data accuracy while also protecting consumers and small businesses who may be undergoing financial stress at this time? GC: Following bureau recommendations regarding data reporting will be critical to ensure that businesses are being treated fairly and that the tools lenders depend on continue to provide value. The COVID-19 crisis also provides a great opportunity for lenders to educate their small business customers on their business credit. Experian has made free business credit reports available to every business across the country to help small business owners ensure the information lenders are using in their credit decisioning is up-to-date and accurate. Q: What is the smartest next play for financial institutions? GC: Experian has several resources that lenders can leverage, including Experian’s COVID-19 Business Risk Index which identifies the industries and geographies that have been most impacted by the COVID crisis. We also have scores and alerts that can help financial institutions gain greater insights into how the pandemic may impact their portfolios, especially for accounts with the greatest immediate exposure and need. MS: To help small businesses weather the storm, financial institutions should make it simple and efficient for them to access the loans and credit they need to survive. With cash flow to help bridge the gap or resume normal operations, small businesses can be more effective in their recovery processes and more easily comply with new legislation. Finances offer the support needed to augment currently reduced cash flows and provide the stability needed to be successful when a return to a more normal business environment occurs. At Experian, we’re closely monitoring the updates around the coronavirus outbreak and its widespread impact on both consumers and businesses. We will continue to share industry-leading insights to help data furnishers navigate and successfully respond to the current environment. Learn more About Our Experts Greg Carmean, Director of Product Management, Experian Business Information Services, North America Greg has over 20 years of experience in the information industry specializing in commercial risk management services. In his current role, he is responsible for managing multiple product initiatives including Experian’s Small Business Financial Exchange (SBFE), domestic and international commercial reports and Corporate Linkage. Recently, he managed the development and launch of Experian’s Global Data Network product line, a commercial data environment that provides a single source of up to date international credit and firmographic information from Experian commercial bureaus and Tier 1 partners across the globe. Matt Shubert, Director of Data Science and Modelling, Experian Data Analytics, North America Matt leads Experian’s Commercial Data Sciences Team which consists of a combination of data scientists, data engineers and statistical model developers. The Commercial Data Science Team is responsible for the development of attributes and models in support of Experian’s BIS business unit. Matt’s 15+ years of experience leading data science and model development efforts within some of the largest global financial institutions gives our clients access to a wealth of knowledge to discover the hidden ROI within their own data.
In uncertain times, we need to find ways to adapt to our situation. We want to help you manage through this unprecedented period.
For financial marketers, long gone are the days of branded coffee mugs, teddy bears and the occasional print ad. Financial marketers are charged with customizing messaging and offerings at a customer level, increasing conversion rates, and moving beyond digital while keeping an eye on traditional channels. Additionally, financial marketing teams are having to do it all with less; according to CMO Survey, marketing budgets have remained stagnant for the last 6 years. Accordingly, competing in today’s world requires transforming your organization to address rapidly increasing complexity while containing costs. Here are four tactics leading-edge firms are using to respond to changes in the market and better serve customers. More data, fewer problems Financial institutions ingest a mind-boggling variety of data, transaction details, transaction history, credit scores, customer preferences, etc. It can be difficult to know where to start or what to do with what is often terabytes of data. But the savviest teams are mining their unique data, along with bureau data, and other alternative and third-party data for rich decision making that drives differentiation. Getting analytical In financial institutions, advanced analytics has traditionally lived with lenders, underwriters, risk and fraud, departments, etc. But marketers too can find the value in the volume, velocity and variety of new data sources available to financial institutions. Using advanced analytics allows the most forward-thinking financial marketers to better target customers, personalize experiences, respond in near-real-time or even predict actions, and measure the impact of marketing investments. Customized quality time with customers Thanks to the likes of Google and Amazon, consumers have become accustomed to individualized interactions with firms they utilize. And this desire is just as present when it comes to their financial institution. But banks, credit unions and fintechs have been historically slow to respond. According to a recent Capgemini study, 70% of US consumers feel like their financial institution doesn’t understand their needs. The most dynamic financial marketing teams tailor quality experiences that increase consumer engagement and long-term relationships. All the channels, all the time The financial marketer’s job doesn’t stop at creating bespoke experiences for customers. Firms are also having to leverage an omnichannel approach to reach these clients, across an ever-growing number of channels and touchpoints. If that wasn’t enough, campaign cycles are shortening to match consumers changing demands and need for instant gratification—again, thanks Amazon. But the best teams determine which media or interaction resonates most effectively with clients, whether face-to-face, via an app, chatbot, or social media and have conversations across all of them seamlessly. It’s clear, financial firms must transform their approach to address increasing market complexity without increasing costs. Financial marketers are saddled with stagnant marketing budgets, proliferating media channels and shorter campaign cycles, with an expectation to continue delivering results. It’s a very tall order, especially if your financial institution is not leveraging data, analytics and insights as the differentiators they could be. CMOs and their marketing teams must invest in new technologies, strategies and data sources that best reflect the expectations of their customers. How is your bank or credit union responding to these financial marketing challenges? Watch our 2020 Credit Marketing Trends On-Demand Webinar
According to Experian’s Q3 2019 State of the Automotive Finance Market report, used vehicle financing increased across all credit tiers.
The challenges facing today’s marketers seem to be mounting and they can feel more pronounced for financial institutions. From customizing messaging and offerings at an individual customer level, increasing conversion rates, moving beyond digital while keeping an eye on traditional channels, and more, financial marketers are having to modernize their approach to customer acquisition. The most forward-thinking financial firms are turning to customer acquisition engines to help them best build, test and optimize their custom channel targeting strategies faster than ever before. But what functionality is right for your company? Here are 5 capabilities you should look for in a modern customer acquisition engine. Advanced Segmentation It’s without question that targeting and segmentation are vital to a successful financial marketing strategy. Make sure you select a tool that allows for advanced segmentation, ensuring the ability to uncover lookalike groups with similar attributes or behaviors and then customize messages or offerings accordingly. With the right customer acquisition engine, you should be able to build filters for targeted segments using a range of data including demographic, past behavior, loyalty or transaction history, offer response and then repurpose these segments across future campaigns. Campaign Design With the right campaign design, your team has the ability to greatly affect customer engagement. The right customer acquisition engine will allow your team to design a specific, optimized customer journey and content for each of the segments you create. When you’re ready to apply your credit criteria to the audience to generate a pre-screen, the best tools will allow you to view the size of your list adjusted in real-time. Make sure to look for an acquisition engine that can do all of this easily with a drag and drop user experience for faster and efficient campaign design. Rapid Deployment Once you finalize your audience for each channel or offer, the clock starts ticking. From bureau processing, data aggregation, targeting and deployment, the data that many firms are currently using for prospecting can be at least 60-days. When searching for a modern customer acquisition engine, make sure you choose a tool that gives you the option to fetch the freshest data (24-48 hours) before you deploy. If you’re sending the campaign to an outside firm to execute, timing is even more important. You’ll also want a system that can encrypt and decrypt lists to send to preferred partners to execute your marketing campaign. Support Whether you have an entire marketing department at your disposal or a lean, start-up style team, you’re going to want the highest level of support when it comes to onboarding, implementation and operational success. The best customer acquisition solution for your company will have a robust onboarding and support model in place to ensure client success. Look for solutions that offer hands-on instruction, flexible online or in-person training and analytical support. The best customer acquisition tool should be able to take your data and get you up and running in less than 30 days. Data, Data and more Data Any customer acquisition engine is only as good as the data you put into it. It should, of course, be able to include your own client data. However, relying exclusively on your own data can lead to incomplete analysis, missed opportunities and reduced impact. When choosing a customer acquisition engine, pick a system that gives your company access to the most local, regional and national credit data, in addition to alternative data and commercial data assets, on top of your own data. The optimum solutions can be fueled by the analytical power of full-file, archived tradeline data, along with attributes and models for the most robust results. Be sure your data partner has accounted for opt-outs, excludes data precluded by legal or regulatory restrictions and also anonymizes data files when linking your customer data. Data accuracy is also imperative here. Choose a marketing and technology partner who is constantly monitoring and correcting discrepancies in customer files across all bureaus. The best partners will have data accuracy rates at or above 99.9%.
With the growing need for authentication and security, fintechs must manage risk with minimal impact to customer experience. When implementing tactical approaches for fraud risk strategy operations, keeping up with the pace of fraud is another critical consideration. How can fintechs be proactive about future-proofing fraud strategies to stay ahead of savvy fraudsters while maintaining customer expectations? I sat down with Chris Ryan, Senior Fraud Solutions Business Consultant with Experian Decision Analytics, to tap into some of his insights. Here’s what he had to say: How have changes in technology added to increased fraud risk for businesses operating in the online space? Technology introduces many risks in the online space. As it pertains to the fintech world, two stand out. First, the explosion in mobile technology. The same capabilities that make fintech products broadly accessible makes them vulnerable. Anyone with a mobile device can attempt to access a fintech and try their hand at committing fraud with very little risk of being caught or punished. Second, the evolution of an interconnected, digital ‘marketplace’ for stolen data. There’s an entire underground economy that’s focused on connecting the once-disparate pieces of information about a specific individual stolen from multiple, unrelated data breaches. Criminal misrepresentations are more complete and more convincing than ever before. What are the major market drivers and trends that have attributed to the increased risk of fraud? Ultimately, the major market drivers and trends that drive fraud risk for fintechs are customer convenience and growth. In terms of customer convenience, it’s a race to meet customer needs in real time, in a single online interaction, with a minimally invasive request for information. But, serving the demands of good customers opens opportunities for identity misuse. In terms of growth, the pressure to find new pockets of potential customers may lead fintechs into markets where consumer information is more limited, so naturally, there are some risks baked in. Are fintechs really more at risk for fraud? If so, how are fintechs responding to this dynamic threat? The challenge for many fintechs has been the prioritization of fraud as a risk that needs to be addressed. It’s understandable that fintech’s initial emphasis had to be the establishment of viable products that meet the needs of their customers. Obviously, without customers using a product, nothing else matters. Now that fintechs are hitting their stride in terms of attracting customers, they’re allocating more of their attention and innovative spirit to other areas, like fraud. With the right partner, it’s not hard for fintechs to protect themselves from fraud. They simply need to acquire reliable data that provides identity assurance without negatively impacting the customer experience. For example, fintechs can utilize data points that can be extracted from the communications channel, like device intelligence for example, or non-PII unique identifiers like phone and email account data. These are valuable risk indicators that can be collected and evaluated in real time without adding friction to the customer experience. What are the major fraud risks to fintechs and what are some of the strategies that Risk Managers can implement to protect their business? The trends we’ve talked about so far today have focused more on identity theft and other third-party fraud risks, but it’s equally important for fintechs to be mindful of first party fraud types where the owner of the identity is the culprit. There is no single solution, so the best strategy recommendation is to plan to be flexible. Fintechs demonstrate an incredible willingness to innovate, and they need to make sure the fraud platforms they pick are flexible enough to keep pace with their needs. From your perspective, what is the future of fraud and what should fintechs consider as they evolve their products? Fraud will continue to be a challenge whenever something of value is made available, particularly when the transaction is remote and the risk of any sort of prosecution is very low. Criminals will continue to revise their tactics to outwit the tools that fintechs are using, so the best long-term defense is flexibility. Being able to layer defenses, explore new data and analytics, and deploy flexible and dynamic strategies that allow highly tailored decisions is the best way for fintechs to protect themselves. Digital commerce and the online lending landscape will continue to grow at an increasing pace – hand-in-hand with the opportunities for fraud. To stay ahead of fraudsters, fintechs must be proactive about future-proofing their fraud strategies and toolkits. Experian can help. Our Fintech Digital Onboarding Bundle provides a solid baseline of cutting-edge fraud tools that protect fintechs against fraud in the digital space, via a seamless, low-friction customer experience. More importantly, the Fintech Digital Onboarding Bundle is delivered through Experian’s CrossCore platform—the premier platform in the industry recognized specifically for enabling the expansion of fraud tools across a wide range of Experian and third-party partner solutions. Click here to learn more or to speak with an Experian representative. Learn More About Chris Ryan: Christopher Ryan is a Senior Fraud Solutions Business Consultant. He delivers expertise that helps clients make the most from data, technology and investigative resources to combat and mitigate fraud risks across the industries that Experian serves. Ryan provides clients with strategies that reduce losses attributable to fraudulent activity. He has an impressive track record of stopping fraud in retail banking, auto lending, deposits, consumer and student lending sectors, and government identity proofing. Ryan is a subject matter expert in consumer identity verification, fraud scoring and knowledge-based authentication. His expertise is his ability to understand fraud issues and how they impact customer acquisition, customer management and collections. He routinely helps clients review workflow processes, analyze redundancies and identify opportunities for process improvements. Ryan recognizes the importance of products and services that limit fraud losses, balancing expense and the customer impact that can result from trying to prevent fraud.
As the holiday shopping season kicks off, it’s prime time for fraudsters to prey on consumers who are racking up rewards points as they spend. Find out how fraud trends in loyalty and rewards programs can impact your business: Are you ready to prevent fraud this holiday season? Get started today
In today’s ever-changing and hypercompetitive environment, the customer experience has taken center-stage – highlighting new expectations in the ways businesses interact with their customers. But studies show financial institutions are falling short. In fact, a recent study revealed that 94% of banking firms can’t deliver on the “personalization promise.” It’s not difficult to see why. Consumer preferences have changed, with many now preferring digital interactions. This has made it difficult for financial institutions to engage with consumers on a personal level. Nevertheless, customers expect seamless, consistent, and personalized experiences – that’s where the power of advanced analytics comes into play. It’s no secret that using advanced analytics can enable businesses to turn rich data into insights that lead to confident business decisions and strategy development. But these business tools can actually help financial institutions deliver on that promise of personalization. According to an Experian study, 90% of organizations say that embracing advanced analytics is critical to their ability to provide an excellent customer experience. By using data and analytics to anticipate and respond to customer behavior, companies can develop new and creative ways to cater to their audiences – revolutionizing the customer experience as a whole. It All Starts With Data Data is the foundation for a successful digital transformation – the lack of clean and cohesive datasets can hinder the ability to implement advanced analytic capabilities. However, 89% of organizations face challenges on how to effectively manage and consolidate their data, according to Experian’s Global Data Management Research Benchmark Report of 2019. Because consumers prefer digital interactions, companies have been able to gather a vast amount of customer data. Technology that uses advanced analytic capabilities (like machine learning and artificial intelligence) are capable of uncovering patterns in this data that may not otherwise be apparent, therefore opening doors to new avenues for companies to generate revenue. To start, companies need a strategy to access all customer data from all channels in a cohesive ecosystem – including data from their own data warehouses and a variety of different data sources. Depending on their needs, the data elements can come from a third party data provider such as: a credit bureau, alternative data, marketing data, data gathered during each customer contact, survey data and more. Once compiled, companies can achieve a more holistic and single view of their customer. With this single view, companies will be able to deliver more relevant and tailored experiences that are in-line with rising customer expectations. From Personalized Experiences to Predicting the Future The most progressive financial institutions have found that using analytics and machine learning to conquer the wide variety of customer data has made it easier to master the customer experience. With advanced analytics, these companies gain deeper insights into their customers and deliver highly relevant and beneficial offers based on the holistic views of their customers. When data is provided, technology with advanced analytic capabilities can transform this information into intelligent outputs, allowing companies to optimize and automate business processes with the customer in mind. Data, analytics and automation are the keys to delivering better customer experiences. Analytics is the process of converting data into actionable information so firms can understand their customers and take decisive action. By leveraging this business intelligence, companies can quickly adapt to consumer demand. Predictive models and forecasts, increasingly powered by machine learning, help lenders and other businesses understand risks and predict future trends and consumer responses. Prescriptive analytics help offer the right products to the right customer at the right time and price. By mastering all of these, businesses can be wherever their customers are. The Experian Advantage With insights into over 270 million customers and a wealth of traditional credit and alternative data, we’re able to drive prescriptive solutions to solve your most complex market and portfolio problems across the customer lifecycle – while reinventing and maintaining an excellent customer experience. If your company is ready for an advanced analytical transformation, Experian can help get you there. Learn More
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