While electric vehicles remain a relatively niche part of the market, with only 0.9 percent of the total vehicle registrations through June 2018, consumer demand has grown quite significantly over the past few years. As I mentioned in a previous blog post, electric vehicles held just 0.5 percent in 2016. Undoubtedly, manufacturers and retailers will look to capitalize on this growing segment of the population. But, it’s not enough to just dig into the sales number. If the automotive industry really wants to position itself for success, it’s important to understand the consumers most interested in electric vehicles. This level of data can help manufacturers and retailers make the right decisions and improve the bottom line. Based on our vehicle registration data, below is detailed look into the electric vehicle consumer. Home Value Somewhat unsurprisingly, the people most likely to purchase an electric vehicle tend to own more expensive homes. Consumers with homes valued between $450,000-$749,000 made up 25 percent of electric vehicle market share. And, as home values increase, these consumers still make up a significant portion of electric vehicle market. More than 15 percent of the electric vehicle market share was made up by those with homes valued between $750,000-$999,000, and 22.5 percent of the share was made up by those with home values of more than $1 million. In fact, consumers with home values of more than $1 million are 5.9 times more likely to purchase an electric vehicle than the general population.  Education Level Breaking down consumers by education level shows another distinct pattern. Individuals with a graduate degree are two times more likely to own an electric vehicle. Those with graduate degrees made up 28 percent of electric vehicle market share, compared to those with no college education, which made up just 11 percent. Consumer Lifestyle Segmentation Diving deeper into the lifestyles of individuals, we leveraged our Mosaic® USA consumer lifestyle segmentation system, which classifies every household and neighborhood in the U.S. into 71 unique types and 19 overachieving groups. Findings show American Royalty, who are described as wealthy, influential couples and families living in prestigious suburbs, led the way with a 17.8 percent share. Following them were Silver Sophisticates at 11.9 percent. Those in this category are described as mature couples and singles living an upscale lifestyle in suburban homes. Rounding out the top three were Cosmopolitan Achiever, described as affluent middle-aged and established couples and families who enjoy a dynamic lifestyle in metro areas. Their share was 10.1 percent. If manufacturers and retailers go beyond just the sales figures, a clearer picture of the electric vehicle market begins to form. They have an opportunity to understand that wealthier, more established individuals with higher levels of education and home values are much more likely to purchase electric vehicles. While these characteristics are consistent, the different segments represent a dynamic group of people who share similarities, but are still at different stages in life, leading different lifestyles and have different needs. As time wears on, the electric vehicle segment is poised for growth. If the industry wants to maximize its potential, they need to leverage data and insights to help make the right decisions and adapt to the evolving marketplace.

I believe it was George Bernard Shaw that once said something along the lines of, “If economists were laid end-to-end, they’d never come to a conclusion, at least not the same conclusion.” It often feels the same way when it comes to big data analytics around customer behavior. As you look at new tools to put your customer insights to work for your enterprise, you likely have questions coming from across your organization. Models always seem to take forever to develop, how sure are we that the results are still accurate? What data did we use in this analysis; do we need to worry about compliance or security? To answer these questions and in an effort to best utilize customer data, the most forward-thinking financial institutions are turning to analytical environments, or sandboxes, to solve their big data problems. But what functionality is right for your financial institution? In your search for a sandbox solution to solve the business problem of big data, make sure you keep these top four features in mind. Efficiency: Building an internal data archive with effective business intelligence tools is expensive, time-consuming and resource-intensive. That’s why investing in a sandbox makes the most sense when it comes to drawing the value out of your customer data.By providing immediate access to the data environment at all times, the best systems can reduce the time from data input to decision by at least 30%. Another way the right sandbox can help you achieve operational efficiencies is by direct integration with your production environment. Pretty charts and graphs are great and can be very insightful, but the best sandbox goes beyond just business intelligence and should allow you to immediately put models into action. Scalability and Flexibility: In implementing any new software system, scalability and flexibility are key when it comes to integration into your native systems and the system’s capabilities. This is even more imperative when implementing an enterprise-wide tool like an analytical sandbox. Look for systems that offer a hosted, cloud-based environment, like Amazon Web Services, that ensures operational redundancy, as well as browser-based access and system availability.The right sandbox will leverage a scalable software framework for efficient processing. It should also be programming language agnostic, allowing for use of all industry-standard programming languages and analytics tools like SAS, R Studio, H2O, Python, Hue and Tableau. Moreover, you shouldn’t have to pay for software suites that your analytics teams aren’t going to use. Support: Whether you have an entire analytics 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 sandbox solution for your company will have a robust 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. Look for solutions and data partners that also offer the consultative help of industry experts when your company needs it. Data, Data and More Data: Any analytical environment is only as good as the data you put into it. It should, of course, 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 sandbox solution, pick a system that will include 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 will have years 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 big data 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%. Solving the business problem around your big data can be a daunting task. However, investing in analytical environments or sandboxes can offer a solution. Finding the right solution and data partner are critical to your success. As you begin your search for the best sandbox for you, be sure to look for solutions that are the right combination of operational efficiency, flexibility and support all combined with the most robust national data, along with your own customer data. Are you interested in learning how companies are using sandboxes to make it easier, faster and more cost-effective to drive actionable insights from their data? Join us for this upcoming webinar. Register for the Webinar

This is an exciting time to work in big data analytics. Here at Experian, we have more than 2 petabytes of data in the United States alone. In the past few years, because of high data volume, more computing power and the availability of open-source code algorithms, my colleagues and I have watched excitedly as more and more companies are getting into machine learning. We’ve observed the growth of competition sites like Kaggle, open-source code sharing sites like GitHub and various machine learning (ML) data repositories. We’ve noticed that on Kaggle, two algorithms win over and over at supervised learning competitions: If the data is well-structured, teams that use Gradient Boosting Machines (GBM) seem to win. For unstructured data, teams that use neural networks win pretty often. Modeling is both an art and a science. Those winning teams tend to be good at what the machine learning people call feature generation and what we credit scoring people called attribute generation. We have nearly 1,000 expert data scientists in more than 12 countries, many of whom are experts in traditional consumer risk models — techniques such as linear regression, logistic regression, survival analysis, CART (classification and regression trees) and CHAID analysis. So naturally I’ve thought about how GBM could apply in our world. Credit scoring is not quite like a machine learning contest. We have to be sure our decisions are fair and explainable and that any scoring algorithm will generalize to new customer populations and stay stable over time. Increasingly, clients are sending us their data to see what we could do with newer machine learning techniques. We combine their data with our bureau data and even third-party data, we use our world-class attributes and develop custom attributes, and we see what comes out. It’s fun — like getting paid to enter a Kaggle competition! For one financial institution, GBM armed with our patented attributes found a nearly 5 percent lift in KS when compared with traditional statistics. At Experian, we use Extreme Gradient Boosting (XGBoost) implementation of GBM that, out of the box, has regularization features we use to prevent overfitting. But it’s missing some features that we and our clients count on in risk scoring. Our Experian DataLabs team worked with our Decision Analytics team to figure out how to make it work in the real world. We found answers for a couple of important issues: Monotonicity — Risk managers count on the ability to impose what we call monotonicity. In application scoring, applications with better attribute values should score as lower risk than applications with worse values. For example, if consumer Adrienne has fewer delinquent accounts on her credit report than consumer Bill, all other things being equal, Adrienne’s machine learning score should indicate lower risk than Bill’s score. Explainability — We were able to adapt a fairly standard “Adverse Action” methodology from logistic regression to work with GBM. There has been enough enthusiasm around our results that we’ve just turned it into a standard benchmarking service. We help clients appreciate the potential for these new machine learning algorithms by evaluating them on their own data. Over time, the acceptance and use of machine learning techniques will become commonplace among model developers as well as internal validation groups and regulators. Whether you’re a data scientist looking for a cool place to work or a risk manager who wants help evaluating the latest techniques, check out our weekly data science video chats and podcasts.

Electric vehicles are here to stay – and will likely gain market share as costs reduce, travel ranges increase and charging infrastructure grows.

There’s no shortage of buzz around fintechs shifting from marketplace challengers to industry collaborators. Regardless of fintech’s general reputation as market disruptors, a case can certainly be made for building partnerships with traditional financial institutions by leveraging the individual strengths of each organization. According to the World FinTech Report 2018, 75.5% of fintechs surveyed selected “collaborate with traditional firms” as their main objective. Whereas fintechs have agility, a singular focus on the customer, and an absence of legacy systems, traditional Financial Institutions have embedded infrastructure, scale, reach, and are well-versed with regulatory requirements. By partnering together, fintechs and other Financial Institutions can combine strengths to generate real business results and impact the customer experience. New stories are emerging – stories that illustrate positive outcomes beyond efforts exerted by one side alone. A recent report sponsored by Experian and conducted by the Filene Research Institute further explores the results of fintech and traditional FI partnerships by examining the experiences of six organizations: The outcomes of these relationships are sure to encourage more collaborative partnerships. And while leveraging each organization’s strength is a critical component, there’s much more to consider when developing a strategic approach. In the fast-moving, disruptive world of fintech, just what are the key elements to building a successful collaboration with traditional Financial Institutions? Click here to learn more. More Info on Marketplace Lending Read the Filene Report

Vehicle prices are going up, yet consumers seem unfazed. Despite consumers taking out larger loan amounts, they continue to make their monthly payments on time. But, affordability remains a point of industry interest.  As vehicle prices hit record highs, how long will consumers have an appetite for them? According to Experian’s latest State of Automotive Finance Market report, delinquency rates continued a downward trend, as 30- and 60-day delinquencies were 2.11 and 0.64 percent, respectively, at the end of Q2. Those numbers demonstrate that car owners are making timely payments despite rising vehicle costs, which is an encouraging sign for the market. The average loan amount for a new vehicle is now $30,958, a $724 increase from last year. Additionally, consumers are now making monthly payments of about $525 on a new car loan, an all-time high that has seen a $20 year over year increase. The auto market shows little to no sign of declining costs, but vehicles aren’t the only cost to consider – interest rates have increased by 56 basis points since last year.  When combined with the rising manufacturer costs, long-term affordability is a continued concern within the industry. The data points to consumers offsetting the expense by taking out longer loan terms. In Q2, the most common loan length was 72 months—which equates to six years—for both new and used financing. While this lowers the monthly payment, it leaves them subject to paying higher interest over time, as well as the potential for individuals to be upside down on their loan for a longer period of time. The key takeaway from this data is that costs continue to rise, but consumers appear to be doing a better job of managing their finances. This insight can help OEMs, dealers, and lenders make strategic decisions with a better understanding of consumer borrowing and credit habits, and think about how to make car ownership more inviting, through incentive or loyalty programs. For consumers, continuing to take steps to actively improve your credit score is one of the key ways to ensure that you’re able to negotiate the right deal when it comes to financing. Ultimately, for everyone involved, it comes down to leveraging the power of data to make more informed decisions, which can help make vehicle ownership more accessible and affordable. To learn more about the State of the Automotive Finance Market report, or to watch the webinar, click here.

Fintechs take on banks, technology, and finance as we know It. In the credit space, their reputation as a market disruptor precedes their definition. But now, as they infiltrate headlines and traditional finance as many know it – serving up consumer-centric, convenience-touting, access-for-all online marketplace lending – fintechs aren’t just becoming a mainstay within the financial spectrum’s vernacular. With their increasing foothold in the marketplace, they are here and they are gaining momentum. Since their initial entry to the marketplace in 2006, these technology-driven online platforms flaunt big data, actionable analytics and originations growing at exponential rates. Fintechs hang their hats on their ability to be the “anti-bank” of sorts. The brainchild of finance plus technology, their brands promise simple but powerful deliverables – all centered on innovation. And they market themselves as filling in the gaps commonly accepted as standard practices by traditional financial institutions. Think paperwork, less-than-instant turnaround times, a history of unwavering tradition, etc. Fintechs deliver a one-two punch, serving the marketplace as both lending companies and technology gurus – two pieces that financial institutions want and consumers crave. Now, as they grow more prominent within the marketplace, some are starting to pivot to test strategic partnerships and bring their strengths – technological infrastructure, speed and agility – to credit unions and other traditional financial institutions. According to the World FinTech Report 2018, 75.5% of fintechs surveyed want to collaborate with traditional financial services firms. The challenge, is that both fintechs and traditional financial institutions struggle with finding the right partners, efficiently working together and effectively scaling innovation. From competitors to collaborators, how can fintechs and traditional institutions strike a partnership balance? A recent report sponsored by Experian and conducted by the Filene Research Institute, explores this conundrum by examining the experiences of six financial institutions – some fintechs and some traditional FIs – as they seek to collaborate under the common goal of better serving customers. The results offer up key ingredients for fostering a successful collaboration between fintechs and traditional financial institutions – to generate real impact to the customer experience and the bottom-line. Rest assured, that in the fast-moving, disruptive world of fintech, effective partnerships such as these will continue to push boundaries and redefine the evolving financial services marketplace. Learn More About Online Marketplace Lending Download the Filene Report

How a business prices its products is a dynamic process that drives customer satisfaction and loyalty, as well as business success.  In the digital age, pricing is becoming even more complex.  For example, companies like Amazon may revise the price of a hot item several times per day. Dynamic pricing models for consumer financial products can be especially difficult for at least four reasons: A complex regulatory environment. Fair lending concerns. The potential for adverse selection by risky consumers and fraudsters. The direct impact the affordability of a loan may have on both the consumer’s ability to pay it and the likelihood that it will be prepaid. If a lender offered the same interest rate and terms to every customer for the same loan product, low-risk customers would secure better rates elsewhere, and high-risk customers would not. The end result? Only the higher-risk customers would select the product, which would increase losses and reduce profitability. For this reason, the lending industry has established risk-based pricing. This pricing method addresses the above issue, since customers with different risk profiles are offered different rates. But it’s limited. More advanced lenders also understand the price elasticity of customer demand, because there are diverse reasons why customers decide to take up differently priced loans. Customers have different needs and risk profiles, so they react to a loan offer in different ways. Many factors determine a customer’s propensity to take up an offer — for example, the competitive environment and availability of other lenders, how time-critical the decision is, and the loan terms offered. Understanding the customer’s price elasticity allows a business to offer the ideal price to each customer to maximize profitability. Pricing optimization is the superior method assuming the lender has a scientific, data-driven approach to predicting how different customers will respond to different prices. Optimization allows an organization to determine the best offer for each customer to meet business objectives while adhering to financial and operational constraints such as volume, margin and credit risk. The business can access trade-offs between competing objectives, such as maximizing revenue and maximizing volume, and determine the optimal decision to be made for each individual customer to best meet both objectives. In the table below, you can see five benefits lenders realize when they improve their pricing segmentation with an optimization strategy. Interested in learning more about pricing optimization? Click here to download our full white paper, Price optimization in retail consumer lending.

Unsecured lending is increasing. And everyone wants in. Not only are the number of personal loans increasing, but the share of those loans originated by fintech companies is increasing. According to Experian statistics, in August 2015, 890 new trades were originated by fintechs (or 21% of all personal loans). Two years later, in August 2017, 1.1 million trades belonged to fintechs (making up 36% of trades). This increase is consistent over time even though the spread of average loan amount between traditional loans and fintech is tightening. While convenience and the ability to apply online are key, interest rates are the number one factor in choosing a lender. Although average interest rates for traditional loans have stabilized, fintech interest rates continue to shift higher – and yet, the upward momentum in fintech loan origination continues. So, who are the consumers taking these loans? A common misconception about fintechs is that their association with market disruption, innovation and technology means that they appeal vastly to the Millennial masses. But that’s not necessarily the case. Boomers represent the second largest group utilizing fintech Marketplace loans and, interestingly, Boomers’ average loan amount is higher than any other generational group – 85.9% higher, in fact, from their Millennial counterparts. The reality is the personal loan market is fast-paced and consumers across the generational spectrum appear eager to adopt convenience-based, technology-driven online lending methods – something to the tune of $35.7 million in trades. For more lending insights and statistics, download Experian’s Q2 2018 Personal Loans Infographic here.   Learn More About Online Marketplace Lending Download Lending Insights

The concept of the credit card was originally envisioned by utopian novelist Edmond Bellamy in 1887 in his utopian novel “Looking Backward.” And ever since the first credit card was introduced almost 70 years ago, people have been absolutely crazy for them. The average American has roughly three of them in her wallet, each with an average balance of $6354 ($1841 for retail cards). Total US credit card debt tipped over $1 trillion in 2017 and continues to climb at around 5% a year. With all of that consumer enthusiasm, you’d be right to assume that it’s a fantastic business to be in. But the credit card industry of today is nothing if not competitive and, with literally thousands of credit card products out there, it’s exceptionally hard to stand out. Our wallets are overflowing with cards and our mailboxes are awash with card offers, yet few people could explain the differences between them. In addition, the industry has lost ground to an ever-proliferating list of alternative payment methods, including mobile peer-to-peer payment services and prepaid debit cards. Furthermore, the advent of big data and alternative underwriting models could allow some tech upstarts to refinance balances at lower interest rates – especially if they’re willing to accept slightly lower returns than credit card companies have become accustomed to. So while the industry as a whole appears to be quite healthy, it’s clear that in order to differentiate credit card companies need to be more innovative than they are today. And the first step towards coming up with new, innovative ideas is acknowledging your vulnerabilities. Six vulnerabilities in the credit card industry Credit card companies face threats on many sides, making it hard to know where to start initiating change. Here are some of the top vulnerabilities that face the credit card industry today. 1. Retailers are starting to balk at high fees In 2016, Costco concluded its exclusive partnership with American Express in favor of Visa and Citibank. While that transition was painful at times, analysts from BMO Capital Markets estimated that switch would save the retailer between $110 million and $220 million in interchange fees. Later that year, Walmart Canada announced that it intended to stop accepting Visa credit cards in its 400 stores, citing high transaction fees. The two companies resolved the dispute after six months, and neither company disclosed the new terms. But it wouldn’t be the last time it happened. Foods Co., a California-based Kroger family company, stopped accepting Visa credit cards in its 21 stores and five gas stations in August 2018 over a fee dispute. Its parent company stated that it’s considering following suit. When large retailers stop accepting certain payment networks or changing their preferred payment network over fee disputes, it’s not just the payment networks that suffer. Credit card issuers also miss out when their cardholders can no longer use certain cards at their favorite retailer. 2. Fintech companies competing for loyalty Fintech companies are providing many services that credit cardholders can’t always get with their card issuer. Some, for example, provide credit monitoring services that help consumers build or rebuild their credit. Other fintech companies are using alternative and trended credit data in their underwriting process. Earnest, for example, not only checks applicants’ credit scores but also looks at savings patterns, investment balances, and employment growth potential. Fannie Mae, the largest source of funding for mortgage lenders, began using trended credit data, which provides a deeper look at a borrower’s credit history, for single-family mortgage applications in 2016. By using alternative and trended credit data to evaluate prospective borrowers, these and other companies can find new customer markets and achieve more predictive decisions than the traditional way of measuring risk. 3. Mobile payment services bypassing credit card companies Apple Pay, Samsung Pay and Google Pay make it easier and safer for cardholders to use their credit cards when shopping online and at retail stores. That said, these services could start using their own payment infrastructure in the future, bypassing credit cards entirely. Peer-to-peer mobile payment services including PayPal, Venmo and Square, already do this. In fact, they charge a fee for credit card payments, which effectively forces most users to use a debit card or checking account instead. 4. Increased use of debit cards undercuts credit cards Consumers made 73.8 billion payments with a debit card in 2016, according to the Federal Reserve, with a value of $2.7 trillion. That’s roughly three times the volume and value of debit card payments a decade earlier. During that same time, the volume and value of credit card payments increased by closer to 1.5 times. While that’s still an upward trend, debit cards use is gaining more steam. Younger consumers are likely driving this trend toward debit instead of credit. A study conducted by Harris Poll recently found that Millennials carry fewer credit cards than older generations and appear far more debt warry. Also, according to a TD Bank survey, Millennials spend more than twice as much using cash, debit cards and checks than the average American. Some banks including Discover and American Express, have begun offering cash-back rewards to their debit and prepaid debit cardholders. These rewards programs may start to catch on with other banks, making debit cards a reasonable alternative to credit card holders who prefer debit but don’t want to miss out on cash back. 5. Challenger brands are targeting underserved customers Many major credit card issuers focus more on the prime and near-prime market, opening up the way for challenger brands to capture market share among consumers who are new to credit or looking to rebuild. Deserve, for instance, has raised more than $78 million to provide a credit card to international students with no Social Security number requirement. It also offers an unsecured credit card designed for consumers with no credit history. Another example is Petal, which has raised close to $17 million from investors to provide a no-fee, unsecured credit card to help consumers build credit — all with no credit score requirement. 6. A persistent lack of security in credit card transactions Credit card fraud was the most common form of identity theft reported to the Federal Trade Commission in 2017, according to a report by Experian. And while credit card companies have made strides to prevent fraudsters from accessing credit card information, perpetrators are getting smarter and more sophisticated, making it hard for card issuers to keep up. With consumer credit card debt rapidly growing and APR’s on the rise, the current credit card boon simply can’t last forever. The market will eventually shrink and a game of “Survivor” will ensue. So it would be wise for credit card companies to take stock of their vulnerabilities now and start getting ahead of the pack. Visit our website for more information on identity protection products you can offer your customers.

If your company is like many financial institutions, it’s likely the discussion around big data and financial analytics has been an ongoing conversation. For many financial institutions, data isn’t the problem, but rather what could or should be done with it. Research has shown that only about 30% of financial institutions are successfully leveraging their data to generate actionable insights, and customers are noticing. According to a recent study from Capgemini,  30% of US customers and 26% of UK customers feel like their financial institutions understand their needs. No matter how much data you have, it’s essentially just ones and zeroes if you’re not using it. So how do banks, credit unions, and other financial institutions who capture and consume vast amounts of data use that data to innovate, improve the customer experience and stay competitive? The answer, you could say, is written in the sand. The most forward-thinking financial institutions are turning to analytical environments, also known as a sandbox, to solve the business problem of big data. Like the name suggests, a sandbox is an environment that contains all the materials and tools one might need to create, build, and collaborate around their data. A sandbox gives data-savvy banks, credit unions and FinTechs access to depersonalized credit data from across the country. Using custom dashboards and data visualization tools, they can manipulate the data with predictive models for different micro and macro-level scenarios. The added value of a sandbox is that it becomes a one-stop shop data tool for the entire enterprise. This saves the time normally required in the back and forth of acquiring data for a specific to a project or particular data sets. The best systems utilize the latest open source technology in artificial intelligence and machine learning to deliver intelligence that can inform regional trends, consumer insights and highlight market opportunities. From industry benchmarking to market entry and expansion research and campaign performance to vintage analysis, reject inferencing and much more. An analytical sandbox gives you the data to create actionable analytics and insights across the enterprise right when you need it, not months later. The result is the ability to empower your customers to make financial decisions when, where and how they want. Keeping them happy keeps your financial institution relevant and competitive. Isn’t it time to put your data to work for you? Learn more about how Experian can solve your big data problems. >> Interested to see a live demo of the Ascend Sandbox? Register today for our webinar “Big Data Can Lead to Even Bigger ROI with the Ascend Sandbox.”

Shawn Hanson, CEO of Marine Credit Union in Wisconsin, knows a thing or two about growth.  Over the past 18 years as CEO, Shawn and his team have the grown the credit union significantly, both organically and through acquisitions. In addition, he has developed a clear vision to reach the underserved. I spoke with Shawn to get his perspective and insights about growth, risk and the underserved. Here’s what he had to say: Marine Credit Union has grown from $120M to $789M over the past 18 years under your leadership.  What have been the top 2-3 actions you’ve taken to fuel this growth? The past two decades of growth have included a lot of successes, but also some key failures. Failures that taught us some hard lessons in who we are – and who we are not. If I can point to one action that has had the most impact on our growth, it is the refinement of our focus. We clarified our mission, vision and strategy and aligned our business decisions accordingly. Over the past 18 years as CEO, what has been your proudest moment? (Or proudest moments?) I reach out to employees on a regular basis and ask them to share with me a story of how they impacted a member’s life. I hear stories of people who never thought they would dig themselves out of a financial hole, and people we are helping to save thousands of dollars each month in bill payments. I feel so fortunate that I get to hear these stories every day. So, to answer your question, my proudest moment will happen today when I hear that next story. Then again tomorrow. And again, the next day. What drove Marine’s decision to focus on serving the underserved? I started my career in the consumer finance industry, so it is where my roots lie. Over time, we have come to discover that serving the underserved is not only a good business to be in, it is a business that is good. A business that is doing well while doing good – performing financially while giving back to its communities – is a business that people want to be around. How does your credit union define underserved?  What services does your staff offer members that are unique? We define the underserved as people who cannot typically get help down the block. While this most often means individuals, who are credit-challenged, it is more than that. Our underserved can be an overleveraged borrower who needs some help simplifying their life and streamlining bill payments. We have a debt consolidation product that’s a perfect fit for that situation. Our underserved can be a self-employed borrower whose income statements don’t fit inside a neat box, a homebuyer with an unconventional property. or an immigrant with alternative documentation. Our in-house underwriting and decentralized decision-making structure give us more flexibility to serve our underserved. Given your credit union’s history of growth through acquisitions, how have you preserved the culture of reaching the underserved? We are experienced, but we are not perfect. When it comes to the integration of employees, we learn through each acquisition. Our strategy is very different from other financial institutions, and we know this creates a learning curve for merging employees. Cultural integration is incredibly important to us. We have taken this too slow, too fast and everywhere in between. What we know for certain is that one size does not fit all. Whatever approach we decide on for a cultural integration, we do it with intention and two key principles in mind: do what’s best for the employees and the members. Why do you think credit unions are uniquely positioned to reach & serve the underserved? Talk about roots; this is where we were born. Serving the underserved is in our credit union DNA. Beyond our history, it is what we are known for: people helping people. Credit unions have built a legacy of trust with the communities we serve. Trust has become a coveted commodity. What is the biggest misperception among credit unions regarding the topic of serving the underserved? It’s too risky. One of the underpinnings of the credit union movement is providing a path to affordable credit.  What should risk-adverse credit unions think about when evaluating their mission? Think about the role you play in your community; how would the world be poorer, but for your presence? If you can answer with clarity, you're serving a need. Everybody seems to be chasing the most qualified borrowers today. We're focused on being there for the rest. Marine’s mission is to “create a better future for themselves and their families”.  What has been the biggest surprise for you serving the underserved? We call it “the snowball effect.” Repeatedly, we have seen one small “yes” turn into a remarkably different life for a member we have helped. A car loan led to transportation to work, which led to a steady job, which led to a promotion, which led to buying a home. I never underestimate the power of a chance. How has your board helped to accelerate the mission to reach the underserved?  What advice do you have for boards who are concerned of taking on more perceived risk? I feel very fortunate to work with a Board of Directors who has accelerated our mission in many ways, but most importantly, by having an open mind and allowing themselves to think differently. Our Board is always learning and always pushing me, one another and the credit union to be better. Strategic planning season is upon us.  What advice do you have for credit unions looking to lend deeper? Hone your focus. Know who you are and who you are not. Know who you serve and who you do not. Get aligned on where you want to be 5, 10 and 20 years from now, and work backward. What do you need to be focusing on in 2019 to achieve your long-term goals, and what do you need to stop wasting energy on? Ensure your people, products and processes are aligned and scaled to support a diversification or transition. This can take years to build or evolve. Walk, don’t run.   About Shawn Hanson Shawn Hanson is the CEO of Marine Credit Union. He has been with the credit union since April 2000 when the credit union had two offices and $37 million in assets. Hanson’s vision for the future is a differentiated financial institution that provides services to a broad geographic base with the best service. Hanson has also held positions at Citizens Community Federal Credit Union and AVCO Financial Services. Learn more about the array of alternative credit data sources available to financial institutions to reach your underserved populations.  

In the aftermath of Hurricane Florence, Experian is here to help. As a first line of defense against purchasing a flood-damaged vehicle, people can download our free Vehicle Flood Risk Check app.

Big Data is no longer a new concept. Once thought to be an overhyped buzzword, it now underpins and drives billions in dollars of revenue across nearly every industry. But there are still companies who are not fully leveraging the value of their big data and that’s a big problem. In a recent study, Experian and Forrester surveyed nearly 600 business executives in charge of enterprise risk, analytics, customer data and fraud management. The results were surprising: while 78% of organizations said they have made recent investments in advanced analytics, like the proverbial strategic plan sitting in a binder on a shelf, only 29% felt they were successfully using these investments to combine data sources to gather more insights. Moreover, 40% of respondents said they still rely on instinct and subjectivity when making decisions. While gut feeling and industry experience should be a part of your decision-making process, without data and models to verify or challenge your assumptions, you’re taking a big risk with bigger operations budgets and revenue targets. Meanwhile, customer habits and demands are quickly evolving beyond a fundamental level. The proliferation of mobile and online environments are driving a paradigm shift to omnichannel banking in the financial sector and with it, an expectation for a customized but also digitized customer experience. Financial institutions have to be ready to respond to and anticipate these changes to not only gain new customers but also retain current customers. Moreover, you can bet that your competition is already thinking about how they can respond to this shift and better leverage their data and analytics for increased customer acquisition and engagement, share of wallet and overall reach. According to a recent Accenture study, 79% of enterprise executives agree that companies that fail to embrace big data will lose their competitive position and could face extinction. What are you doing to help solve the business problem around big data and stay competitive in your company?

With Hispanic Heritage Awareness Month underway and strategic planning season in full swing, the topic of growing membership continues to take front stage for credit unions. Miriam De Dios Woodward (CEO of Coopera Consulting) is an expert on the Hispanic opportunity, working with credit unions to help them grow by expanding the communities they serve. I asked Miriam if she could provide her considerations for credit unions looking to further differentiate their offerings and service levels in 2019 and beyond.   There’s never been a better time for credit unions to start (or grow) Hispanic engagement as a differentiation strategy. Lending deeper to this community is one key way to do just that. Financial institutions that don’t will find it increasingly difficult to grow their membership, deposits and loan balances. As you begin your 2019 strategic planning discussions, consider how your credit union could make serving the Hispanic market a differentiation strategy. Below are nine ways to start. 1.  Understand your current membership and market through segmentation and analytics. The first step in reaching Hispanics in your community is understanding who they are and what they need. Segment your existing membership and market to determine how many are Hispanic, as well as their language preferences. Use this segmentation to set a baseline for growth of your Hispanic growth strategy, measure ongoing progress and develop new marketing and product strategies. If you don’t have the bandwidth and resources to conduct this segmentation in-house, seek partners to help. 2.  Determine the product gaps that exist and where you can deepen relationships. After you understand your current Hispanic membership and market, you will want to identify opportunities to improve the member experience, including your lending program. For example, if you notice Hispanics are not obtaining mortgages at the same rate as non-Hispanics, look at ways to bridge the gaps and address the root causes (i.e., more first-time homebuyer education and more collaboration with culturally relevant providers across the homebuying experience). Also, consider how you might adapt personal loans to meet the needs of consumers, such as paying for immigration expenses or emergencies with family in Latin America. 3.  Explore alternative credit scoring models. Many credit products accessible to underserved consumers feature one-size-fits-all rates and fees, which means they aren’t priced according to risk. Just because a consumer is unscoreable by most traditional credit scoring models doesn’t mean he or she won’t be able to pay back a loan or does not have a payment history. Several alternative models available today can help  lenders better evaluate a consumer’s ability to repay. Alternative sources of consumer data, such as utility records, cell phone payments, medical payments, insurance payments, remittance receipts, direct deposit histories and more, can be used to build better risk models. Armed with this information – and with the proper programs in place to ensure compliance with regulatory requirements and privacy laws – credit unions can continue making responsible lending decisions and grow their portfolio while better serving the underserved. 4.  Consider how you can help more Hispanic members realize their desire to become homeowners. In 2017, more than 167,000 Hispanics purchased a first home, taking the total number of Hispanic homeowners to nearly 7.5 million (46.2 percent of Hispanic households). Hispanics are the only demographic to have increased their rate of homeownership for the last three consecutive years. What’s more, 9 percent of Hispanics are planning to buy a house in the next 12 months, compared to 6 percent of non-Hispanics. This means Hispanics, who represent about 18 percent of the U.S. population, may represent 22 percent of all new home buyers in the next year. By offering a variety of home loan options supported by culturally relevant education, credit unions can help more Hispanics realize the dream of homeownership.   5.  Go beyond indirect lending for auto loans. The number of cars purchased by Hispanics in the U.S. is projected to double in the period between 2010 and 2020. It’s estimated that new car sales to Hispanics will grow by 8 percent over the next five years, compared to a 2 percent decline among the total market. Consider connecting with local car dealers that serve the Hispanic market. Build a pre-car buying relationship with members rather than waiting until after they’ve made their decision. Connect with them after they’ve made the purchase, as well.   6.  Consider how you can help Hispanic entrepreneurs and small business owners. Hispanics are nine times more likely than whites to take out a small business loan in the next five years. Invest in products and resources to help Hispanic entrepreneurs, such as small business-friendly loans, microloans, Individual Taxpayer Identification Number (ITIN) loans, credit-building loans and small-business financial education. Also, consider partnering with organizations that offer small business assistance, such as local Hispanic chambers of commerce and small business incubators.   7.  Rethink your credit card offerings. Credit card spending among underserved consumers has grown rapidly for several consecutive years. The Center for Financial Services Innovation (CFSI) estimates underserved consumers will spend $37.6 billion on retail credit cards, $8.3 billion on subprime credit cards and $0.4 billion on secured credit cards in 2018. Consider mapping out a strategy to evolve your credit card offerings in a way most likely to benefit the unique underserved populations in your market. Finding success with a credit-builder product like a secured card isn’t a quick fix. Issuers must take the necessary steps to comply with several regulations, including Ability to Repay rules. Cards and marketing teams will need to collaborate closely to execute sales, communication and, importantly, cardmember education plans. There must also be a good program in place for graduating cardmembers into appropriate products as their improving credit profiles warrant. If offering rewards-based products, ensure the rewards include culturally relevant offerings. Work with your credit card providers.­   8.  Don’t forget about lines of credit. Traditional credit lines are often overlooked as product offerings for Hispanic consumers. These products can provide flexible funding opportunities for a variety of uses such as making home improvements, helping family abroad with emergencies, preparing families for kids entering college and other expenses. Members who are homeowners and have equity in their homes have a potential untapped source to borrow cash.   9.  Get innovative. Hispanic consumers are twice as likely to research financial products and services using mobile apps. Many fintech companies have developed apps to help Hispanics meet immediate financial needs, such as paying off debt and saving for short-term goals. Others encourage long-term financial planning. Still other startups have developed new plans that are basically mini-loans shoppers can take out for specific purchases when checking out at stores and online sites that participate. Consider how your credit union might partner with innovative fintech companies like these to offer relevant, digital financial services to Hispanics in your community.   Next Steps Although there’s more to a robust Hispanic outreach program than we can fit in one article, credit unions that bring the nine topics highlighted above to their 2019 strategic planning sessions will be in an outstanding position to differentiate themselves through Hispanic engagement.   Experian is proud to be the only credit bureau with a team 100% dedicated to the Credit Union movement and sharing industry best practices from experts like Miriam De Dios Woodward. Our continued focus is providing solutions that enable credit unions to continue to grow, protect and serve their field of membership. We can provide a more complete view of members and potential members credit behavior with alternative credit data. By pulling in new data sources that include alternative financing, utility and rental payments, Experian provides credit unions a more holistic picture, helping to improve credit access and decisioning for millions of consumers who may otherwise be overlooked.   About Miriam De Dios Woodward Miriam De Dios Woodward is the CEO of Coopera, a strategy consulting firm that helps credit unions and other organizations reach and serve the Hispanic market as an opportunity for growth and financial inclusion. She was named a 2016 Woman to Watch by Credit Union Times and 2015 Latino Business Person of the Year by the League of United Latin American Citizens of Iowa. Miriam earned her bachelor’s degree from Iowa State University, her MBA from the University of Iowa and is a graduate of Harvard Business School’s Leading Change and Organizational Renewal executive program.