Tag: financial services
Retailers are already starting to display their Christmas decorations in stores and it’s only early November. Some might think they are putting the cart ahead of the horse, but as I see this happening, I’m reminded of the quote by the New York Yankee’s Yogi Berra who famously said, “It gets late early out there.” It may never be too early to get ready for the next big thing, especially when what’s coming might set the course for years to come. As 2019 comes to an end and we prepare for the excitement and challenges of a new decade, the same can be true for all of us working in the lending and credit space, especially when it comes to how we will approach the use of alternative data in the next decade. Over the last year, alternative data has been a hot topic of discussion. If you typed “alternative data and credit” into a Google search today, you would get more than 200 million results. That’s a lot of conversations, but while nearly everyone seems to be talking about alternative data, we may not have a clear view of how alternative data will be used in the credit economy. How we approach the use of alternative data in the coming decade is going to be one of the most important decisions the lending industry makes. Inaction is not an option, and the time for testing new approaches is starting to run out – as Yogi said, it’s getting late early. And here’s why: millennials. We already know that millennials tend to make up a significant percentage of consumers with so-called “thin-file” credit reports. They “grew up” during the Great Recession and that has had a profound impact on their financial behavior. Unlike their parents, they tend to have only one or two credit cards, they keep a majority of their savings in cash and, in general, they distrust financial institutions. However, they currently account for more than 21 percent of discretionary spend in the U.S. economy, and that percentage is going to expand exponentially in the coming decade. The recession fundamentally changed how lending happens, resulting in more regulation and a snowball effect of other economic challenges. As a result, millennials must work harder to catch up financially and are putting off major life milestones that past generations have historically done earlier in life, such as homeownership. They more often choose to rent and, while they pay their bills, rent and other factors such as utility and phone bill payments are traditionally not calculated in credit scores, ultimately leaving this generation thin-filed or worse, credit invisible. This is not a sustainable scenario as we enter the next decade. One of the biggest market dynamics we can expect to see over the next decade is consumer control. Consumers, especially millennials, want to be in the driver’s seat of their “credit journey” and play an active role in improving their financial situations. We are seeing a greater openness to providing data, which in turn enables lenders to make more informed decisions. This change is disrupting the status quo and bringing new, innovative solutions to the table. At Experian, we have been testing how advanced analytics and machine learning can help accelerate the use of alternative data in credit and lending decisions. And we continue to work to make the process of analyzing this data as simple as possible, making it available to all lenders in all verticals. To help credit invisible and thin-file consumers gain access to fair and affordable credit, we’ve recently announced Experian Lift, a new suite of credit score products that combines exclusive traditional credit, alternative credit and trended data assets to create a more holistic picture of consumer creditworthiness that will be available to lenders in early 2020. This new Experian credit score may improve access to credit for more than 40 million credit invisibles. There are more than 100 million consumers who are restricted by the traditional scoring methods used today. Experian Lift is another step in our commitment to helping improve financial health of consumers everywhere and empowers lenders to identify consumers who may otherwise be excluded from the traditional credit ecosystem. This isn’t just a trend in the United States. Brazil is using positive data to help drive financial inclusion, as are others around the world. As I said, it’s getting late early. Things are moving fast. Already we are seeing technology companies playing a bigger role in the push for alternative data – often powered by fintech startups. At the same time, there also has been a strong uptick in tech companies entering the banking space. Have you signed up for your Apple credit card yet? It will take all of 15 seconds to apply, and that’s expected to continue over the next decade. All of this is changing how the lending and credit industry must approach decision making, while also creating real-time frictionless experiences that empower the consumer. We saw this with the launch of Experian Boost earlier this year. The results speak for themselves: hundreds of thousands of previously thin-file consumers have seen their credit scores instantly increase. We have also empowered millions of consumers to get more control of their credit by using Experian Boost to contribute new, positive phone, cable and utility payment histories. Through Experian Boost, we’re empowering consumers to play an active role in building their credit histories. And, with Experian Lift, we’re empowering lenders to identify consumers who may otherwise be excluded from the traditional credit ecosystem. That’s game-changing. Disruptions like Experian Boost and newly announced Experian Lift are going to define the coming decade in credit and lending. Our industry needs to be ready because while it may seem early, it’s getting late.
It seems like artificial intelligence (AI) has been scaring the general public for years – think Terminator and SkyNet. It’s been a topic that’s all the more confounding and downright worrisome to financial institutions. But for the 30% of financial institutions that have successfully deployed AI into their operations, according to Deloitte, the results have been anything but intimidating. Not only are they seeing improved performance but also a more enhanced, positive customer experience and ultimately strong financial returns. For the 70% of financial institutions who haven’t started, are just beginning their journey or are in the middle of implementing AI into their operations, the task can be daunting. AI, machine learning, deep learning, neural networks—what do they all mean? How do they apply to you and how can they be useful to your business? It’s important to demystify the technology and explain how it can present opportunities to the financial industry as a whole. While AI seems to have only crept into mainstream culture and business vernacular in the last decade, it was first coined by John McCarthy in 1956. A researcher at Dartmouth, McCarthy thought that any aspect of learning or intelligence could be taught to a machine. Broadly, AI can be defined as a machine’s ability to perform cognitive functions we associate with humans, i.e. interacting with an environment, perceiving, learning and solving problems. Machine learning vs. AI Machine learning is not the same thing as AI. Machine learning is the application of systems or algorithms to AI to complete various tasks or solve problems. Machine learning algorithms can process data inputs and new experiences to detect patterns and learn how to make the best predictions and recommendations based on that learning, without explicit programming or directives. Moreover, the algorithms can take that learning and adapt and evolve responses and recommendations based on new inputs to improve performance over time. These algorithms provide organizations with a more efficient path to leveraging advanced analytics. Descriptive, predictive, and prescriptive analytics vary in complexity, sophistication, and their resulting capability. In simplistic terms, descriptive algorithms describe what happened, predictive algorithms anticipate what will happen, and prescriptive algorithms can provide recommendations on what to do based on set goals. The last two are the focus of machine learning initiatives used today. Machine learning components - supervised, unsupervised and reinforcement learning Machine learning can be broken down further into three main categories, in order of complexity: supervised, unsupervised and reinforcement learning. As the name might suggest, supervised learning involves human interaction, where data is loaded and defined and the relationship to inputs and outputs is defined. The algorithm is trained to find the relationship of the input data to the output variable. Once it delivers accurately, training is complete, and the algorithm is then applied to new data. In financial services, supervised learning algorithms have a litany of uses, from predicting likelihood of loan repayment to detecting customer churn. With unsupervised learning, there is no human engagement or defined output variable. The algorithm takes the input data and structures it by grouping it based on similar characteristics or behaviors, without a defined output variable. Unsupervised learning models (like K-means and hierarchical clustering) can be used to better segment or group customers by common characteristics, i.e. age, annual income or card loyalty program. Reinforcement learning allows the algorithm more autonomy in the environment. The algorithm learns to perform a task, i.e. optimizing a credit portfolio strategy, by trying to maximize available rewards. It makes decisions and receives a reward if those actions bring the machine closer to achieving the total available rewards, i.e. the highest acquisition rate in a customer category. Over time, the algorithm optimizes itself by correcting actions for the best outcomes. Even more sophisticated, deep learning is a category of machine learning that involves much more complex architecture where software-based calculators (called neurons) are layered together in a network, called a neural network. This framework allows for much broader, complex data ingestion where each layer of the neural network can learn progressively more complex elements of the data. Object classification is a classic example, where the machine ‘learns’ what a duck looks like and then is able to automatically identify and group images of ducks. As you might imagine, deep learning models have proved to be much more efficient and accurate at facial and voice recognition than traditional machine learning methods. Whether your financial institution is already seeing the returns for its AI transformation or is one of the 61% of companies investing in this data initiative in 2019, having a clear picture of what is available and how it can impact your business is imperative. How do you see AI and machine learning impacting your customer acquisition, underwriting and overall customer experience?
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
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.
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
Preparation is key – whether you’re an amateur/professional sports, free-soloing up El Capitan, or business contingency planning as part of a recession readiness strategy. It’s not so much predicting when events will occur, or trying to foresee and pivot for every possible outcome, but rather, acting now so that your business can act faster and smarter in the future. There are certain priorities that have come to be associated with what are widely accepted as the three environments the economy can sustain at any one time: As with recessions throughout the country’s history, those periods have often been characterized by layoffs, charge-offs, delinquencies, and other behaviors as the economy turns to a counter-cycle environment. Rather than wait to implement reactive strategies , the time to manage accounts, plan, stress test and implement contingency plans for when the next economic correction comes, is now. While economists and financial services industry experts argue over when a recession will hit and how severe its implications may be (in comparison with the Great Recession of 2008), there’s a need to start tactical business discussions now. Even in the face of a strong economy, that has seen high employment levels and increased spending, 45% of Americans (112.5 million) say they do not have enough savings to cover at least three months of living expenses, according to a 2018 survey by the Center for Financial Services Innovation. Regardless of the economic environment – pro-cycle, counter-cycle, and cycle-neutral – those statistics paint an alarming picture of consumers\' financial health as a whole. These are four crucial considerations you should be taking now: Create individualized treatments while reducing manual interactions Meet the growing expectation for digital consumer self-service Understand your customer to ensure fair treatment React quickly and effectively to market changes While it may not be on the immediate horizon just yet, it’s important to prepare. For more information, including portfolio mixes, collections considerations and macroeconomic trends, download our latest white paper on recession readiness. Download white paper now
First impressions are always important – whether it’s for a job interview, a first date or when pitching a client. A good first impression in the financial services industry – specifically frictionless onboarding – is critical when it comes to onboarding new users and clients, as it’s an opportunity to set the stage for lifetime loyalty. As a result, financial institutions are on the hunt now more than ever for frictionless digital ID verification, to validate genuine customers and maintain positive customer experiences during the online onboarding process. In a predominantly digital-first world, financial companies are increasingly focused on the customer experience and creating the most seamless and frictionless online onboarding process. The number of banking users (online and mobile) exceeded 2 billion in 2018 and has an expected 11% compound annual growth rate between 2019-2023, according to Experian’s 2019 Global Identity and Fraud Report. That’s a lot of people to impress – no pressure. And as technology continues to advance, digital onboarding services for financial industries will, not surprisingly, increase the demand for fraud protection and authentication methods – namely with digital ID verification processes. Now consider this – mobile banking users are expected to be 58% of the global banked population in 2019. According to Experian’s report, 74% of consumers see security as the most important element of their online experience, followed by convenience. Again, no pressure. So how can companies guarantee a frictionless online onboarding process while executing proper authentication methods and maintaining security and fraud detection? The answer? While a “frictionless” experience can seem like a bit of a unicorn, there are some ways to get close: Utilizing better data - Digital devices offer an extensive amount of data that’s useful in determining risk. Characteristics that allow the identification of a specific device, the behaviors associated with the device and information about a device’s owner can be captured without adding friction for the user. Analytics – Once the data is collected, advanced analytics uses information based on behavioral data, digital intelligence, phone intelligence and email intelligence to analyze for risk. While there’s friction in the initial ask for the input data, the risk prediction improves with more data. Document verification and biometric identity verification – Real-time document verification used in conjunction with facial biometrics, behavioral biometrics and other physical characteristics allows for rapid onboarding and helps to maintain a low friction customer journey. Financial institutions can utilize document verification to replace manual long-form applications for rapid onboarding and immediately verify new data at the point of entry. Using their mobile phones, customers can photograph and upload identity documents that can be used to pre-fill applications. Document authenticity can be verified in real-time. Biometrics, including facial, behavioral, or other physical characteristics (like fingerprints), are low-touch methods of customer authentication that can be used synchronously with document verification. These elements can help create a frictionless digital ID verification process. Experian understands how critical identity management and fraud protection is when it comes to the online onboarding process and identity verification. That’s why we created layered digital identity verification and risk segmentation solutions to help legitimize your customers with confidence while improving the customer experience. Our identity verification solutions use advanced technology and capabilities to correctly identify and verify real customers while mitigating fraud and maintaining frictionless customer experiences. Learn More
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
What is CECL? CECL (Current Expected Credit Loss) is a new credit loss model, to be leveraged by financial institutions, that estimates the expected loss over the life of a loan by using historical information, current conditions and reasonable forecasts. According to AccountingToday, CECL is considered one of the most significant accounting changes in decades to affect entities that borrow and lend money. To comply with CECL by the assigned deadline, financial institutions will need to access much more data than they’re currently using to calculate their reserves under the incurred loss model, Allowance for Loan and Lease Losses (ALLL). How does it impact your business? CECL introduces uncertainty into accounting and growth calculations, as it represents a significant change in the way credit losses are currently estimated. The new standard allows financial institutions to calculate allowances in a variety of ways, including discounted cash flow, loss rates, roll-rates and probability of default analyses. “Large banks with historically good loss performance are projecting increased reserve requirements in the billions of dollars,” says Experian Advisory Services Senior Business Consultant, Gavin Harding. Here are a few changes that you should expect: Larger allowances will be required for most products As allowances will increase, pricing of the products will change to reflect higher capital cost Losses modeling will change, impacting both data collection and modeling methodology There will be a lower return on equity, especially in products with a longer life expectancy How can you prepare? “CECL compliance is a journey, rather than a destination,” says Gavin. “The key is to develop a thoughtful, data-driven approach that is tested and refined over time.” Financial institutions who start preparing for CECL now will ultimately set their organizations up for success. Here are a few ways to begin to assess your readiness: Create a roadmap and initiative prioritization plan Calculate the impact of CECL on your bottom line Run altered scenarios based on new lending policy and credit decision rules Understand the impact CECL will have on your profitability Evaluate current portfolios based on CECL methodology Run different loss methods and compare results Additionally, there is required data to capture, including quarterly or monthly loan-level account performance metrics, multiple year data based on loan product type and historical data for the life of the loan. How much time do you have? Like most accounting standards, CECL has different effective dates based on the type of reporting entity. Public business entities that file financial statements with the Security and Exchange Commission will have to comply by 2020, non-public entity banks must comply by 2022 and non-SEC registered companies have until 2023 to adopt the new standard. How can we help: Complying with CECL may require you to gather, store and calculate more data than before. Experian can help you comply with CECL guidelines including data needs, consulting and loan loss calculation. Experian industry experts will help update your current strategies and establish an appropriate timeline to meet compliance dates. Leveraging our best-in-class industry data, we will help you gain CECL compliance quickly and effectively, understand the impacts to your business and use these findings to improve overall profitability. Learn more
Do more with less. Once the mantra of the life-hacking movement, it seems to be the charge given to marketers across the globe. Reduce waste; increase conversion rates; customize messages at a customer level; and do it all faster and more efficiently (read cheaper) than you did last quarter. The marketing challenges facing all companies seem to be more pronounced for financial institutions – not surprising for an industry with a reputation for late adoption. But doing more with less is not just a catchphrase thrown around by lean-obsessed consultants, it’s a response to key changes and challenges in the market. Here are 3 of the top marketing challenges creating business problems for financial institutions today. Budget constraints and misalignment As someone charged with the marketing remit in your firm, this probably comes as no surprise to you. Marketing budgets are stagnant, if not shrinking. Based on a 2018 report from CMO Survey, marketing budgets represent just over 11% of firm expenditures, a level which has remained largely constant over the last six years.Meanwhile, budgets at many financial firms appear to be out-of-touch with today’s ever-evolving market. In this Financial Brand report, virtually no financial institution committed more than 40% of their budget to mobile marketing, a stat unchanged from the prior two years. More channels mean even more segmentation Gone are the days where a company can rely heavily on traditional media to reach targets and clients. Now more than ever, your customers have access to a compounding amount of media on a proliferating number of channels. Some examples: In 2018, the Pew Research Center found most Americans (68%) get their news from social media. Cable companies recently followed streaming services to offer seamless service and experience across TV, desktop and mobile. Apple and Disney are two of several media juggernauts who are throwing their new streaming services and networks into the ring.This level of access is driving a shift in customers’ expectations for how, when and where they consume content. They want custom messages delivered in a seamless experience across the various channels they use. Shorter campaign cycles According to a recent study by Microsoft, humans now have shorter attention spans, at 8 seconds, than goldfish at 9 seconds. This isn’t surprising considering the levels of digital reach and access your customers are presented with. But this is also forcing a shortening of content and campaign cycles in response. Marketers are now expected to plan, launch and analyze engaging campaigns to meet and stay ahead of customer need and expectation. Ironically, while there’s an intentional shortening of campaign cycles, there’s also a corporate focus to prolong and grow the customer relationship. It’s clear, competing in today’s world requires transforming your organization to address rapidly increasing complexity while containing costs. Competing against stagnant marketing budgets, proliferating media channels and shorter campaign cycles while delivering results is a formidable task, especially if your financial institution is not effectively leveraging data and analytics as differentiators. CMOs and their marketing teams must invest in new technologies and revisit product and channel strategies that reflect the expectations of their customers. How is your bank or credit union responding to these financial marketing challenges? Download Customer Acquisition eBook
How can fintech companies ensure they’re one step ahead of fraudsters? Kathleen Peters discusses how fintechs can prepare for success in fraud prevention.
With delinquencies on the rise, financial institutions are looking for new tools to evaluate and improve the financial lives of customers and members. As the consumer’s bureau, Experian is also committed to improving the financial well-being of consumers. As part of that commitment, Experian supports the mission of the Center for Financial Services Innovation (CFSI), an organization focused on improving the financial health of Americans, especially the underserved, through innovative financial products and services. Experian recently spoke with CFSI’s Thea Garon, a Director on CFSI’s Program Team to learn more about a new free, open-source tool the organization will be launching in June to help financial institutions drive consumer financial health. Here are some insights she shared about the new tool. Can you provide an overview of the CFSI Financial Health Score™ and how it is calculated? The CFSI Financial Health Score™ is designed to help financial service providers, employers, and other organizations diagnose and measure the financial health of their customers, clients, and employees. The framework provides a holistic, moment-in-time snapshot of an individual’s financial health based on eight multiple-choice questions that align with CFSI’s eight indicators of financial health. It includes one Financial Health Score and four sub-scores (Spend, Save, Borrow, and Plan). A set of nationally representative benchmarks offers comparisons across peer groups. CFSI has designed the framework to be free, open-source, simple, and easy-to-use. It’s intended to be a starting point; a proof point that financial health can be quantified, measured, and ultimately improved. Why did CFSI decide to develop this framework? At CFSI, we believe, and have recently released research to support the concept that financial institutions have a business incentive to help their customers lead financially healthy lives. Financial health comes about when your daily financial systems allow you to be resilient and pursue opportunities over time. As a financial service provider, you can help your customers lead financially healthy lives by helping them spend wisely, build savings, borrow responsibly, and plan for the future. To do this, you need a measurement framework to understand and track your customers’ financial health over time. The CFSI Financial Health Score™ is one way to do this. You can use the methodology to diagnose your customers’ financial needs and use these insights to develop products, programs, and solutions to help them improve their financial health over time. You can also share financial health scores directly with your customers to help them understand the actions they can take to improve their own financial health. Ongoing tracking will allow you to assess whether your company is making a meaningful difference in your customers’ lives over time. Can you provide any early examples of how CFSI Health Network members have adopted and incorporated this framework? Approximately 100 financial service providers have downloaded the framework, representing a diverse range of companies, including banks, credit unions, fintechs, non-profits, payment networks, and B2B technology providers. At least 14 companies are actively using the Financial Health Score to measure and track their customers’ financial health and have committed to sharing data and insights with us through CFSI’s Financial Health Leaders program. Some companies, are using the framework to assess their customers’ financial health for strategic planning purposes. Other companies, such as Wright-Patt Credit Union, are using the financial health score to engage their customers in a dialogue about financial health. The credit union has incorporated the framework into their MoneyMagnifier program, a financial coaching program designed to provide free, one-on-one advice and guidance to members in a judgment-free environment. Financial coaches have been trained to use the framework to start a conversation with members to help them improve their spending, saving, borrowing, and planning behaviors. Coaches help members set goals and develop personalized action plans to achieve those goals toward a better financial future, following up with them after six months to measure improvement and advance the conversation. What have you learned from companies who have started measuring and improving their customers’ financial health with the CFSI Financial Health Score™? While interest in advice is high, uptake can be slow. Making the interaction quick and easy, whether online or in person, is critical. The health check lengthens the interaction, so conducting the health check by appointment rather than with walk-in customers, can help set customer expectations for a lengthier interaction, but may reduce the number of potential participants. Enabling customers to expedite the session by taking the survey online can be helpful, but requires development resources to implement. Many companies are exploring the pros and cons of sharing customers’ scores with them. A single score can help motivate individuals to take action that will improve their financial well-being. However, sharing a low score can also be demoralizing to some, and focusing on the number itself can divert attention from behavioral changes and action steps. Some organizations are choosing to use customers’ response patterns to drive recommendations without sharing the score. Others are opting for a middle ground, sharing an indicator (such as green, yellow, red) instead of a specific number. The most effective measurement and improvement strategies go beyond the CFSI Financial Health Score™. While the framework can help you get started identifying high-level needs, targeted recommendations often require a more nuanced understanding of behaviors and challenges. Combining survey data with account or transaction data can provide a more holistic view into a customer’s full financial life. Each organization must find a balance between the comprehensiveness required to provide meaningful advice and the simplicity required to engage both customers and staff. How can interested companies start using the CFSI Financial Health Score™? We will be publicly releasing the CFSI Financial Health Score™ at the EMERGE: Financial Health Forum (June 6 -8 in Los Angeles). The score will be easy to download and completely free to use. 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Direct mail is not dead, but it\'s 2017. Financial services companies need to acknowledge there might be other ways to deliver credit offers and capture consumer eyeballs. There are multiple screens competing for our attention, including one of the originals - TV. Advertising and TV have been married forever, but addressable TV allows marketers to target on a much more sophisticated level. Welcome to credit marketing in the digital age. To help financial services companies understand the addressable TV channel, Experian marketing expert Brienna Pinnow answered the following questions in a short interview. What is addressable TV? Addressable TV is an amazing 1-to-1 direct marketing capability. To put it simply, addressable TV is the ability for an advertiser to deliver a TV ad to a specific household. From a consumer perspective, that means even if you and your next door neighbor are watching the latest episode of The Voice, you may see an ad for a mini-van while your neighbor sees an ad for upcoming one-day sale from their favorite retailer. With addressable TV, brands can define their target audience based on 1st, 2nd or 3rd party data (like Experian’s). With the help of satellite and cable companies, they can deliver a personalized, measurable experience. This is an exciting departure from the way that TV advertising has been planned and targeted for nearly 70 years. Instead of focusing on the program, marketers can now focus on the person. Addressable TV makes reaching a precise audience – the same way you would with a direct mail piece or an email – a marketing reality. How long have marketers been leveraging addressable TV? Experian has been an pivotal player in the development of the addressable TV space. Since the first addressable TV trials back in 2004, nearly 13 years ago, Experian has provided the audience targeting data and privacy-compliant matching capabilities that make addressable TV possible. The past 3 years, however, have demonstrated unprecedented, hockey-stick growth in addressable TV. In 2016 alone, the volume of addressable campaigns doubled from the previous year accounting for nearly $300 million spend. That trajectory remains the same in 2017 and beyond. So why are we seeing this growth now? Here are a few reasons addressable TV is continuing to grow… Scale: Millions of households can now be targeted using addressable technology, and the footprint continues to grow with smart TVs and additional cable operators. Data: As organizations put data at the heart of their business, addressable TV enables them to infuse their most important customer information into the targeting. Education: Agencies, data providers, and TV providers have invested time educating brands on the process and power of addressable TV. And now, advertisers are becoming more experienced at making this a consistent part of their marketing plan. Accountability: You’ll be hard pressed to find a marketer that doesn’t have to demonstrate ROI on their marketing campaigns. The measurement capabilities that addressable TV provides adds a layer of accountability and insight that was not previously possible. Technology: Experian has developed an audience management platform, the Audience Engine, which makes addressable TV possible in a matter of clicks. In the past year alone, our platform has distributed over 1,800 audiences for addressable advertising campaigns. What types of companies have been utilizing addressable TV? Have you seen many financial services companies test this channel? The early adopters of addressable TV were primarily automotive advertisers. Compared to other verticals, auto advertisers still spend the largest proportion of their budgets across TV. For that reason, they know it’s a necessity to see if their dollars are actually driving sales for their big-ticket items. Addressable TV solves that problem for auto advertisers. In a DIRECTV campaign leveraging Experian’s automotive data for audience targeting and post-campaign sales reporting, one major auto OEM saw a 26.2% lift in sales for the advertised model compared to the control group. In the past few years, Experian has worked closely with advertisers across verticals – from retail to travel to finance – to launch addressable campaigns. Financial services clients particularly find Experian’s financial related segments, such as income or net worth, to be accurate and powerful in creating qualified target audiences that improve campaign performance. I’ve read that millennials are abandoning cable and TV providers in favor of services like Hulu and Netflix. Does this mean the market for addressable TV will shrink in the coming years? There is a segment of consumers who are abandoning traditional cable services. However, this doesn’t mean they are abandoning content. In fact, content consumption is at an all-time high with offerings from Roku, Hulu, Netflix, Sling TV, CBS, and beyond. All this shift in behavior means is that the definition of TV is becoming more fluid. “TV” doesn’t have to be a big screen sitting in your living room; it can be a laptop on a red-eye flight. And from a marketing perspective, the concept of addressable, 1-to-1 targeting is already moving into some of these products and services. The footprint of addressable TV will only continue to rise as consumers stay connected to the content they love. How can companies measure the success of utilizing addressable TV as a channel? Not only does addressable TV provide laser-targeted ad delivery, but it also opens up measurement capabilities that were never possible for TV advertisers in the past. Traditionally, TV audience measurement has focused simply on eyeballs and not revenue impact, with little insight into how TV advertising converts into sales. The primary source for audience measurement in the TV world has been program ratings and expensive brand studies. With addressable TV, that story is changing. With companies that collect second-by-second viewership data linked to households, marketers now have the ability to tie this data back to their online and offline sales. Experian is pivotal in making closed-loop TV reporting possible. As a data and matching safe-haven, we link together the viewing information from the target audience with the sales data provided by the advertiser. The end result is a privacy compliant report that clearly demonstrates the impact of the campaign on the target audience. Did the targeted audience visit a bank location? Email customer service? Sign up for a new account? Spend a certain amount? These are all questions our TV attribution reporting answers for clients. If a company wants to begin marketing in addressable TV, what is required in terms of set-up? Addressable TV may sound new, exciting or even complex. But it doesn’t have to be. Getting started is as simple as defining the target audience. Decide whether you would like to leverage your own CRM data, a custom model, third-party data or a combination of these data sources. If you’re still not sure where to start, ask yourself a very simple question, “Who am I sending a direct mail piece or email to in the next month?” There’s your audience. Better yet, you will be amplifying your message, reaching the customer with a consistent message and meeting them wherever they are. After you’ve determined who you want to target, a matching partner like Experian can work with you to show you the reach of your audience across TV providers. You’ll finalize your budget, creative and media plan while Experian distributes your audience to the selected media destinations. Before you know it, your campaign will be live, and reaching your target audience whether they’re watching Shark Tank or Sharknado. When the campaign wraps, you’ll be on your way to measuring results like never before. Are there any additional trends you see emerging in the addressable TV space? The future of addressable TV is related to both the targeting and measurement capabilities. More advertisers are working with Experian, for example, to launch coordinated campaigns. That doesn’t just mean launching a digital campaign and TV campaign at the same time. It really means targeting the same exact people for the digital and TV campaign. We like to consider this a \"surround sound\" approach where the customer or prospect experiences a consistent message across channels. As for measurement, Experian is working closely with advertisers to explore the power of mobile data. Recently, Experian partnered with Ninth Decimal and DIRECTV to incorporate mobile location data into the post-campaign measurement process for Toyota. The results proved a 19% lift in dealership visits for those exposed to the campaign. This is an exciting development because this approach can translate well for any other advertiser who wants to measure metrics like location visitation. If you’d like to learn more, check out our Addressable TV whitepaper.
As 2016 comes to a close, many in the financial services industry are trying to assess the impact the Trump administration and Republican controlled Congress will have on regulatory issues. Answers to these questions may be clearer after President-elect Trump is inaugurated on Jan. 20. However, those in the federal regulatory environment are already exploring oversight and regulation of the FinTech and marketplace lending sector. Warning on alternative credit risk models Inquiries by federal and state policymakers over the past year have centered on how FinTech and marketplace lenders are assessing credit risk. In particular, regulators have asked about how credit models different from traditional credit scoring models and what, if any, new attributes or data are being incorporated into credit risk models for consumers and small businesses. On Dec. 2, Federal Reserve Governor Lael Brainard signaled that policymakers continue to be interested in this area during a wide-ranging speech on the potential opportunities and risks associated with FinTech. In particular, Brainard warned that “While nontraditional data may have the potential to help evaluate consumers who lack credit histories, some data may raise consumer protection concerns” and that nontraditional data “… may not necessarily have a broadly agreed upon or empirically established nexus with creditworthiness and may be correlated with characteristics protected by fair lending laws.” Brainard also suggested that there are transparency concerns with alternative scoring models, saying that “alternative credit scoring methods present new challenges that could raise questions of fairness and transparency” given that consumers may not always understand what data is used utilized and how it impacts a consumer’s ability to access credit at an affordable price. Look for regulators and Congress to continue to focus on the fairness and accuracy of new credit risk models and the data underpinning those models in debates surrounding FinTech and Marketplace lending in 2017. A national charter for FinTech? Earlier this month, the Office of the Comptroller of the Currency (OCC) announced that it was considering the creation of a national charter for FinTech lenders. There has long been speculation that the OCC would offer a national charter for FinTech. Analysts have suggested that the creation of a charter could help increase regulatory oversight of the growing market and also provide additional regulatory certainty for the emerging FinTech industry. The OCC’s proposal would create a special purpose national bank charter for FinTech businesses that are engaged in at least one of three core banking activities: receiving deposits; paying checks; or lending money. The OCC will be developing a formal agency policy for evaluating special purpose bank charters for Fintech companies that will designate the specific criteria that companies applying for a charter will have to meet for approval. OCC has suggested that this will likely focus on safety and soundness; financial inclusion; consumer protection; and community reinvestment. The OCC is collecting comments on the proposed policy through Jan. 15, 2017.
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