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.  

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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.

Traditional credit data has long been the end-all-be-all ruling the financial services space. Like the staple black suit or that little black dress in your closet, it’s been the quintessential go-to for decades. Sure, the financial industry has some seasonality, but traditional credit data has reigned supreme as the reliable pillar. It’s dependable. And for a long time, it’s all there was to the equation. But as with finance, fashion and all things – evolution has occurred. Specifically, how consumers are managing their money has evolved, which calls for deeper insights that are still defensible and disputable. Alternative credit data is the new black. It's increasingly integrated in credit talks for lenders across the country. Much like that LBD, it's become a lending staple – that closet (or portfolio) must-have – to leverage for better decisioning when determining creditworthiness. What is alternative data? In our data-driven industry, “alternative” data as a whole may best be summed up as FCRA-compliant credit data that isn't typically included in traditional credit reports. For traditional data, think loan and inquiry data on bankcards, auto, mortgage and personal loans; typically trades with a term of 12 months or greater. Some examples of alternative credit data include alternative financial services data, rental data, full-file public records and account aggregation. These insights can ultimately improve credit access and decisioning for millions of consumers who may otherwise be overlooked. Alternative or not, every bit of information counts FCRA-compliant, user permissioned data allows lenders to easily verify assets and income electronically, thereby giving lenders more confidence in their decision and allowing consumers to gain access to lower-cost financing. From a risk management perspective, alternative credit data can also help identify riskier consumers by identifying information like the number of payday loans acquired within a year or number of first-payment defaults. Alternative credit data can give supplemental insight into a consumer’s stability, ability and willingness to repay that is not available on a traditional credit report that can help lenders avoid risk or price accordingly. From closet finds that refresh your look to that LBD, alternative credit data gives lenders more transparency into their consumers, and gives consumers seeking credit a greater foundation to help their case for creditworthiness. It really is this season’s – and every season’s – must-have. Learn more

Machine learning (ML), the newest buzzword, has swept into the lexicon and captured the interest of us all. Its recent, widespread popularity has stemmed mainly from the consumer perspective. Whether it’s virtual assistants, self-driving cars or romantic matchmaking, ML has rapidly positioned itself into the mainstream. Though ML may appear to be a new technology, its use in commercial applications has been around for some time. In fact, many of the data scientists and statisticians at Experian are considered pioneers in the field of ML, going back decades. Our team has developed numerous products and processes leveraging ML, from our world-class consumer fraud and ID protection to producing credit data products like our Trended 3DTM attributes. In fact, we were just highlighted in the Wall Street Journal for how we’re using machine learning to improve our internal IT performance. ML’s ability to consume vast amounts of data to uncover patterns and deliver results that are not humanly possible otherwise is what makes it unique and applicable to so many fields. This predictive power has now sparked interest in the credit risk industry. Unlike fraud detection, where ML is well-established and used extensively, credit risk modeling has until recently taken a cautionary approach to adopting newer ML algorithms. Because of regulatory scrutiny and perceived lack of transparency, ML hasn’t experienced the broad acceptance as some of credit risk modeling’s more utilized applications. When it comes to credit risk models, delivering the most predictive score is not the only consideration for a model’s viability. Modelers must be able to explain and detail the model’s logic, or its “thought process,” for calculating the final score. This means taking steps to ensure the model’s compliance with the Equal Credit Opportunity Act, which forbids discriminatory lending practices. Federal laws also require adverse action responses to be sent by the lender if a consumer’s credit application has been declined. This requires the model must be able to highlight the top reasons for a less than optimal score. And so, while ML may be able to deliver the best predictive accuracy, its ability to explain how the results are generated has always been a concern. ML has been stigmatized as a “black box,” where data mysteriously gets transformed into the final predictions without a clear explanation of how. However, this is changing. Depending on the ML algorithm applied to credit risk modeling, we’ve found risk models can offer the same transparency as more traditional methods such as logistic regression. For example, gradient boosting machines (GBMs) are designed as a predictive model built from a sequence of several decision tree submodels. The very nature of GBMs’ decision tree design allows statisticians to explain the logic behind the model’s predictive behavior. We believe model governance teams and regulators in the United States may become comfortable with this approach more quickly than with deep learning or neural network algorithms. Since GBMs are represented as sets of decision trees that can be explained, while neural networks are represented as long sets of cryptic numbers that are much harder to document, manage and understand. In future blog posts, we’ll discuss the GBM algorithm in more detail and how we’re using its predictability and transparency to maximize credit risk decisioning for our clients.

The August 2018 LinkedIn Workforce Report states some interesting facts about data science and the current workforce in the United States. Demand for data scientists is off the charts, but there is a data science skills shortage in almost every U.S. city — particularly in the New York, San Francisco and Los Angeles areas. Nationally, there is a shortage of more than 150,000 people with data science skills. One way companies in financial services and other industries have coped with the skills gap in analytics is by using outside vendors. A 2017 Dun & Bradstreet and Forbes survey reported that 27 percent of respondents cited a skills gap as a major obstacle to their data and analytics efforts. Outsourcing data science work makes it easier to scale up and scale down as needs arise. But surprisingly, more than half of respondents said the third-party work was superior to their in-house analytics. At Experian, we have participated in quite a few outsourced analytics projects. Here are a few of the lessons we’ve learned along the way: Manage expectations: Everyone has their own management style, but to be successful, you must be proactively involved in managing the partnership with your provider. Doing so will keep them aligned with your objectives and prevent quality degradation or cost increases as you become more tied to them. Communication: Creating open and honest communication between executive management and your resource partner is key. You need to be able to discuss what is working well and what isn’t. This will help to ensure your partner has a thorough understanding of your goals and objectives and will properly manage any bumps in the road. Help external resources feel like a part of the team: When you’re working with external resources, either offshore or onshore, they are typically in an alternate location. This can make them feel like they aren’t a part of the team and therefore not directly tied to the business goals of the project. To help bridge the gap, performing regular status meetings via video conference can help everyone feel like a part of the team. Within these meetings, providing information on the goals and objectives of the project is key. This way, they can hear the message directly from you, which will make them feel more involved and provide a clear understanding of what they need to do to be successful. Being able to put faces to names, as well as having direct communication with you, will help external employees feel included. Drive engagement through recognition programs: Research has shown that employees are more engaged in their work when they receive recognition for their efforts. While you may not be able to provide a monetary award, recognition is still a big driver for engagement. It can be as simple as recognizing a job well done during your video conference meetings, providing certificates of excellence or sending a simple thank-you card to those who are performing well. Either way, taking the extra time to make your external workforce feel appreciated will produce engaged resources that will help drive your business goals forward. Industry training: Your external resources may have the necessary skills needed to perform the job successfully, but they may not have specific industry knowledge geared towards your business. Work with your partner to determine where they have expertise and where you can work together to providing training. Ensure your external workforce will have a solid understanding of the business line they will be supporting. If you’ve decided to augment your staff for your next big project, Experian® can help. Our Analytics on DemandTM service provides senior-level analysts, either onshore or offshore, who can help with analytical data science and modeling work for your organization.

Federal legislation makes verifying an individual’s identity by scanning identity documents during onboarding legal in all 50 states Originally posted on Mitek blog The Making Online Banking Initiation Legal and Easy (MOBILE) Act officially became law on May 24, 2018, authorizing a national standard for banks to scan and retain information from driver’s licenses and identity cards as part of a customer online onboarding process, via smartphone or website. This bill, which was proposed in 2017 with bipartisan support, allows financial institutions to fully deploy mobile technology that can make digital account openings across all states seamless and cost efficient. The MOBILE Act also stipulates that the digital image would be destroyed after account opening to further ensure customer data security. As an additional security measure, section 213 of the act mandates an update to the system to confirm matches of names to social security numbers. “The additional security this process could add for online account origination was a key selling point with the Equifax data breach fresh on everyone’s minds,” Scott Sargent, of counsel in the law firm Baker Donelson’s financial service practice, recently commented on AmericanBanker.com. Read the full article here. Though digital banking and an online onboarding process has already been a best practice for financial institutions in recent years, the MOBILE Act officially overrules any potential state legislation that, up to this point, has not recognized digital images of identity documents as valid. The MOBILE Act states: “This bill authorizes a financial institution to record personal information from a scan, copy, or image of an individual’s driver’s license or personal identification card and store the information electronically when an individual initiates an online request to open an account or obtain a financial product. The financial institution may use the information for the purpose of verifying the authenticity of the driver’s license or identification card, verifying the identity of the individual, or complying with legal requirements.” Why adopt online banking? The recently passed MOBILE Act is a boon for both financial institutions and end users. The legislation: Enables and encourages financial institutions to meet their digital transformation goals Makes the process safe with digital ID verification capabilities and other security measures Reduces time, manual Know Your Customer (KYC) duties and costs to financial institutions for onboarding new customers Provides the convenient, on-demand experience that customers want and expect The facts: 61% of people use their mobile phone to carry out banking activity.1 77% of Americans have smartphones.2 50 million consumers who are unbanked or underbanked use smartphones.3 The MOBILE Act doesn’t require any regulatory implementation. Banks can access this real-time electronic process directly or through vendors. Read all you need to know about the MOBILE Act here. Find out more about a better way to manage fraud and identity services.   References 1Mobile Ecosystem Forum, MEF Mobile Money Report (https://mobileecosystemforum.com/mobile-money-report/), Feb. 5, 2018. 2Pew Research Center, Mobile Fact Sheet (http://www.pewinternet.org/fact-sheet/mobile/), Jan. 30, 2017. 3The Federal Reserve System, Consumers and Mobile Financial Services 2015 (https://www.federalreserve.gov/econresdata/consumers-and-mobile-financial-services-report-201503.pdf), March 2015.

With credit card openings and usage increasing, now is the time to make sure your financial institution is optimizing its credit card portfolio. Here are some insights on credit card trends: 51% of consumers obtained a credit card application via a digital channel. 42% of credit card applications were completed on a mobile device. The top incentives when selecting a rewards card are cash back (81%), gas rewards (74%) and retail gift cards (71%). Understanding and having a full view of your customers’ activity, behaviors and preferences can help maximize your wallet share. More credit card insight>

Millennials have been accused of “killing” a lot of things. From napkins and fabric softener to cable and golf, the generation which makes up the largest population of the United States (aka Gen Y) is cutting a lot of cords. Despite homeowning being listed as one of the notorious generational group’s casualties, it’s one area that millennials want to keep alive, according to recent statistics. In fact, a new Experian study revealed 86% of millennials believe that buying a house is a good financial investment. However, only 15% have a mortgage today. One explanation for this gap may be that they appear too risky. Younger millennials (age 22-28) have an average near prime score of 652 and older millennials (age 29-35) have a prime score of 665. Both subsets fall below the average VantageScore® credit score* of U.S. consumers – 677. Yes, with the majority of millennials having near prime or worse credit scores, we can agree that they will need need to improve their financial hygiene to improve their overall credit rankings. But their dreams of homeownership have not yet been dashed. Seemingly high aspirations (of homeownership), disrupted by a reality of limited assets, low scores, and thin credit files, create a disconnect that suggests a lack of resources to get into their first homes – rather than a lack of interest. Or, maybe not. Maybe, after surviving a few first-time credit benders that followed soon after opening the floodgates to credit, millennials feel like the combination of low scores and the inability to get any credit is only salt in their wounds from their lending growing pains. Or maybe it’s all the student loans. Or maybe it’s the fact that so many of them are underemployed. But maybe there’s still more to the story. This emerging generation is known for having high expectations for change and better frictionless experiences in all areas of their life. It turns out, their borrowing behavior is no different. Recent research by Experian reveals consumers who use alternative financial services (AFS) are 11 years younger on average than those that do not. What’s the attraction? Financial technology companies have contributed to the explosive growth of AFS lenders and millennials are attracted to those online interactions. The problem is many of these trades are alternative finance products and are not reported to traditional credit bureaus. This means they do nothing to build credit experience in the eyes of traditional lenders and millennials with good credit history find it difficult to get access to credit well into their 20s. Alternative credit data provides a deeper dive into consumers, revealing their transactions and ability to pay as evidenced by alternative finance data, rental, utility and telecom payments. Alt data may make some millennials more favorable to lenders by revealing that their three-digit credit score (or lack there of) may not be indicative of their financial stability. By incorporating alternative financial services data (think convenient, tech-forward lenders that check all the boxes for bank removed millennials, not just payday loan recipients), credit-challenged millennials have a chance at earning recognition for their experience with alternative financial services that may help them get their first mortgage. Society may have preconceived notions about millennials, but lenders may want to consider giving them a second look when it comes to determining creditworthiness. In a national Experian survey, 53% of consumers said they believe some of these alternative sources would have a positive effect on their credit score. We all grow up sometime and as our needs change, there may come a day when millennials need more traditional financial services. Lenders who take a traditional view of risk may miss out on opportunities that alternative credit data brings to light. As lending continues to evolve, combining both traditional credit scores and alternative credit data appears to offer a potentially sweet (or rather, home sweet home) solution for you and your customers.   *Calculated on the VantageScore® credit score model. Your VantageScore® credit score from Experian indicates your credit risk level and is not used by all lenders, so don't be surprised if your lender uses a score that's different from your VantageScore® credit score.

First-party fraud is an identity-centric risk that changes over time. And the fact that no one knows the true size of first-party fraud is not the problem. It’s a symptom. First-party fraud involves a person making financial commitments or defaulting on existing commitments using their own identity, a manipulated version of their own identity or a synthetic identity they control. With the identity owner involved, a critical piece of the puzzle is lost. Because fraud “treatments” tend to be all-or-nothing and rely on a victim, the consequences of applying traditional fraud strategies when first-party fraud is suspected can be too harsh and significantly damage the customer relationship. Without feedback from a victim, first-party fraud hides in plain sight — in credit losses. As a collective, we’ve created lots of subsets of losses that nibble around the edges of first-party fraud, and we focus on reducing those. But I can’t help thinking if we were really trying to solve first-party fraud, we would collectively be doing a better job of measuring it. As the saying goes, “If you can’t measure it, you can’t improve it.” Because behaviors exhibited during first-party fraud are difficult to distinguish from those of legitimate consumers who’ve encountered catastrophic life events, such as illness and unemployment, individual account performance isn’t typically a good measurement. First-party fraud is a person-level event rather than an account-level event and needs to be viewed as such. So why does first-party fraud slip through the cracks? Existing, third-party fraud prevention tools aren’t trained to detect it. Underwriting relies on a point-in-time assessment, leaving lenders blind to intentions that may change after booking. When first-party fraud occurs, the different organizations that suffer losses attach different names to it based on their account-level view. It’s hidden in credit losses, preventing you from identifying it for future analysis. As an industry, we aren’t going to be able to solve the problem of first-party fraud as long as three different organizations can look at an individual and declare, “Never pay!” “No. Bust-out!” “No! Charge-off!” So, what do we need to stop doing? Stop thinking that it’s a different problem based on when you enter the picture. Whether you opened an account five years ago or 5 minutes ago doesn’t change the problem. It’s still first-party fraud if the person who owns the identity is the one misusing it. Stop thinking that the financial performance of an account you maintain is the only relevant data. And what do we need to start doing? See and treat first-party fraud as a continuous Leverage machine learning techniques and robust data (including your own observations) to monitor for emerging risk over Apply multiple levels of treatments to respond and tighten controls/reduce exposure as risk Define first-party fraud using a broader set of elements beyond your individual observations.

Identity-related fraud exposure and losses are increasing, and the underlying schemes are becoming more complex. To make better decisions on the need for step-up authentication in this dynamic environment, you should take a layered approach to the services you need. Some of these services include: Identity verification and reverification checks for ongoing reaffirmation of your customer identity data quality and accuracy. Targeted identity risk scores and underlying attributes designed to isolate identity theft, first-party fraud and synthetic identity. Layered, passive or more active authentication, such as document verification, biometrics, knowledge-based authentication and alternate data sources. Bad guys are more motivated, and they’re getting better at identity theft and synthetic identity attacks. Fraud prevention needs to advance as well. Future-proof your investments. More fraud prevention strategies to consider>

Consumer confidence is nearing an 18-year high. Unemployment figures are at record lows. Retail spend is healthy, and expected to stay that way through the back-to-school and holiday shopping booms. Translation for credit card issuers? The swiping and spending continue. In fact, credit card openings were up 4% in the first quarter of 2018 compared to the same time last year, and card utilization is hovering around 20.5%. Even with the Fed’s gradual 2018 rate hikes, consumers are shopping. In a new Mintel report, outstanding credit card debt is now $1.03 trillion (as of the end of Q1, 2018), and the number of consumers with credit cards is growing fastest among people aged 18 to 34. In the retail card arena specifically, boomers and Gen X’ers are leading the charge, opening 45% and 27% of new retails cards, respectively. “A stronger economy always bodes well for credit cards,” said Kelley Motley, director of analytics for Experian. “Now is the time for card issuers to zero in on their most loyal consumers and ensure they are treating them with the right offers, rewards and premium benefits.” Consumer data reveals the top incentives when selecting a rewards-based card includes cash back, gas rewards and retail cards (including travel rewards and airfare). In fact, for younger consumers, offering rewards has proven to be the most effective way to get them to switch from debit to credit cards. Cash back was the most preferred reward for consumers aged 18 to 44 when asked about their motivation to apply for a new card. For individuals 45 and older, 0% interest was the top motivator. Of course, beyond credit card opens, the ideal is to engage with the consumers who are utilizing the card the most. From a segmentation standpoint, the loyal retail cardholder has an average VantageScore® credit score of 671 with an average total balance of $1,633. They use the card regularly and consistently make payments. Finding more loyalists is the goal and can be achieved with informed segmentation insights and targeted prescreen campaigns. On the flip side, insights can inform card issuers with data, helping them to avoid wasting marketing dollars on consumers who merely want to game a quick credit card offer and then close an account. A batch and blast marketing approach no longer works in the credit card marketing game. “Consumers expect you to know them and their financial needs,” said Paul DeSaulniers, senior director of Experian’s segmentation solutions. “The data exists and tells you exactly who to target and how to structure the offer – you just need to execute.”

Consumer credit scores A recent survey* released by the Consumer Federation of America and VantageScore Solutions, LLC, shows that potential borrowers are more likely to have obtained their credit score than nonborrowers. 70% of those intending to take out a consumer or mortgage loan in the next year received their credit score in the past year, compared with 57% of those not planning to borrow. Consumers who obtained at least one credit score in the past year were more likely to say their knowledge of scores is good or excellent compared with those who haven’t (68% versus 45%). While progress is being made, there’s still a lot of room for improvement. By educating consumers, lenders can strengthen consumer relationships and reduce loss rates. It’s a win-win for consumers and financial institutions. Credit education for your customers>