For most businesses, the customer experience is at the heart of every strategy. Debt collection shouldn’t be different. Here’s why: 21% of visits to an online debt recovery system were made outside the traditional working hours of 8 a.m. to 8 p.m. Of the consumers who committed to a repayment plan, only 56% did so in a single visit. PricewaterhouseCoopers reported that 46% of consumers use only digital channels to conduct banking, avoiding traditional offline channels. Conversely, data collected by Gallup between 2013 and 2016 showed that 48% of American banking customers would only consider using a bank that offered physical branches. The debt collection process is an often-overlooked opportunity to build customer relationships and loyalty. Leverage data and technology to replace outdated approaches, minimize charge-offs and create environments that value each customer. Learn more>

It’s no secret. Consumers engage and interact with brands through a variety of channels, including email, direct mail, websites and mobile. And since most organizations work to keep the consumer experience at the core, they tend to invest in an omnichannel approach that caters to the consumer’s preferences. The lone exception may be during the collections process. Often, once an account falls behind on payment, the consumer experience falls behind with it. But should it? While many banks and financial institutions view the collections process merely as an opportunity to collect outstanding debt, the potential is much more. If treated effectively, the collections process can present an opportunity to develop a positive customer relationship that builds loyalty over time. If handled poorly, the collections process could cost an organization a number of lifetime customers. To correct this, banks and financial institutions need to implement the same omnichannel approach in the collections process as they do with every other consumer interaction. Collections can no longer be treated as a linear process that leads from one channel to the next. There needs to be a more personalized touch — communicating with consumers through preferred channels, contacting them at the most opportune times. Sound complex? Sure. But consider a recent Experian analysis that invited consumers to establish a nonthreatening dialogue with an online debt recovery system. The analysis revealed 21 percent of visits to an organization’s website were outside the traditional working hours of 8 a.m. to 8 p.m. Furthermore, of the consumers who committed to a repayment plan, only 56 percent did so in a single visit. Each consumer is different. So is each situation. And banks and financial institutions need to acknowledge those differences. Luckily, technology can address the complexities of an omnichannel and personalized approach. Platforms such as Experian’s PowerCurve® Collections enable banks and financial institutions to simplify the collections process for both the consumer and the organization. By treating the collections process the same as any other stage in the consumer journey, organizations have an opportunity to build a relationship. And to do so, banks and financial institutions need to leverage the data and technology at their disposal. If they do so appropriately, they’ll minimize their charge-offs and also create a lifetime customer. To learn more about leveraging the collections process to build customer loyalty, download our white paper Getting in front of the shift to omnichannel collections.

Experian on the State of Identity podcast In today’s environment, any conversation on the identity management industry needs to include some mention of synthetic identity risk. The fact is, it’s top of mind for almost everyone. Institutions are trying to scope their risk level and identify losses, while service providers are innovating ways to solve the problem. Even consumers are starting to understand the term, albeit via a local newscast designed to scare the heck out of them. With all this in mind, I was very happy to be invited to speak with Cameron D’Ambrosi at One World Identity (OWI) on the State of Identity podcast, focusing on synthetic identity fraud. Our discussion focused on some of the unique findings and recommended best practices highlighted in our recently published white paper on the subject, Synthetic identities: getting real with customers. Additionally, we discussed how a lack of agreement on the definition and size of the synthetic identity problem further complicates the issue. This all stems from inconsistent loss reporting, a lack of confirmable victims and an absence of an exact definition of a synthetic identity to begin with. Discussions must continue to better align us all. I certainly appreciate that OWI dedicated the podcast to this subject. And I hope listeners take away a few helpful points that can assist them in their organization’s efforts to better identify synthetic identities, reduce financial losses and minimize reputation risks.

The credit card marketplace is a crowded and complex landscape. Recent research by Experian shows the average U.S. consumer has 3.1 credit cards and 2.5 retail cards, with an average balance of $6,354 and $1,841, respectively. So how can you build upon your existing customer relationships and offer the right products to the right people at the right time? By understanding consumer behavior. Pretty simple concept. But targeting viable consumers and making enticing offers takes some detective work. Gone are the days of demographic-based approach to audience segmentation for credit marketing campaigns. Consumers are now engaged on their smartphones, laptops, tablets, fitness bands, across countless apps, browsers, emails and more. Simply knowing a person’s gender and age doesn’t provide any information about how he spends the day, his consumer behaviors, personal interests, unique wants or needs. Developing rich consumer personas based on transaction credit data can be a powerful tool to understanding consumers so lenders can design more relevant and personalized credit offers, experiences and products to a very targeted audience. Experian DataLabs can help by analyzing transaction data to understand the consumers in your portfolio. For example, looking at your portfolio of 40-year-olds in the U.S. provides basic demographic information. A closer look at transaction data could reveal unique details within the age group to help you group and target, such as: Frequent travelers: These road warriors log serious miles. If they’re not traveling for work, they’re cashing in miles for vacation. This unique group leads your portfolio in airfare, cruise line, car rental, hotel and travel agency spend. With so much time spent away from home, this group is rarely found in grocery stores. Local business owners: Advertising, computer equipment, and software are typical expenses of this segmented group. There may be an opportunity to capture spend outside their business activity or to ensure they have the right card to fit their business needs. Constant commuters: These consumers use their card for local travel and transportation. And they are less likely to use their card for expenses related to other types of travel or maintaining a vehicle. After a long day, they like to grab a drink while waiting for the train. Online Shoppers: Consumers in this group use their card with various online merchants, including Amazon, Etsy, iTunes, and PayPal. Online shoppers are also above average spenders in elementary education, child care services, and family clothing. Social hipsters: They can be found meeting with friends for coffee and drinks, and are more likely to rely on local transportation and tend to eat out instead of cooking in. Effective audience segmentation ensures that your marketing dollars are invested in real people who are most likely to respond on certain media, have already expressed an interest in your product, and are geographically accessible to a specific retail location. Every campaign should be as dynamic and unique as its consumers. The powerful combination of consumer and transaction data allows you to customize audience segments to maximize customer engagement and drive campaign success.

Sophisticated criminals work hard to create convincing, verifiable personas they can use to commit fraud. Here are the 3 main ways fraudsters manufacture synthetic IDs: Credit applications and inquiries that build a synthetic credit profile over time. Exploitation of authorized user processes to take over or piggyback on legitimate profiles. Data furnishing schemes to falsify regular credit reporting agency updates. Fraudsters are highly motivated to innovate their approaches rapidly. You need to implement a solution that addresses the continuing rise of synthetic IDs from multiple engagement points. Learn more

As we enter the holiday season, headlines abound around the shifts and trends in retail. How are consumers shopping? What are they buying online versus in-store? How can retailers maintain share and thrive? To gain some fresh perspective on the retail space, we interviewed John Squire, CEO and co-founder of DynamicAction, a business featuring advanced analytics solutions designed specifically for eCommerce, store and omnichannel retail teams. Squire has had a tenured career in the retail and technology sectors serving in key executive roles for IBM Smarter Commerce and Coremetrics. He has spent the past decade guiding nearly every retail brand to a better understanding of their customers and utilization of their data to make profitable decisions.  Business headlines claim we are in the midst of a retail apocalypse. Is this statement a reality?  The reality is that retail is in a renaissance – a revolution driven by the most empowered, connected consumer in history, a burgeoning technology infrastructure and retail tech innovators who have disrupted the status quo. The most agile of retailers and brands are leaning forward to serve their customer with remarkable experiences in the store, online and anywhere the customer decides to interact with the brand. And for those retailers, the days ahead are filled with newfound opportunity. However, the retailers and brands who don’t have a strong core purpose beyond being filler between anchor stores may no longer have a place in this new world of retail. The strongest retailers and brands will tap into their wealth of customer data to better understand, and therefore better serve their customers, creating long-term relationships. They should only continue gain in strength as consumers concentrate more and more of their time (and wallets) with businesses that passionately focus on their unique needs and buying patterns. It seems like shoppers are increasingly turning online to make their purchases. Is this the case, and do we see seasonal spikes with this trend? The key for successful retailers is to understand that customers aren’t just searching, browsing, buying and returning online OR in-store. They are shopping online AND in-store … and even online while in-store. Shoppers simply do not see channels, and the sooner that retailers reorganize their mindset, their organizations and their data understanding around this reality, the more successful they will become. Shoppers are indeed moving online with increasing frequency and larger amounts of their overall spending. Connecting data across the enterprise, across their partners and across social channels is critical in enabling their retailing teams to make decisions on how best to simultaneously serve their customers and their company’s shareholders. If retailers have a store credit card to offer to consumers, how can they encourage use and get them to maximize spend? Are there particular strategies they should employ? As with any loyalty program or service item, consumers are looking for tools and offers they value. Therein lies the opportunity and the challenge. Value can come in many forms, depending on the individual. Does the credit card offer travel or retail points, or dollars that they can accumulate? Does the credit card save them time? Provide them with additional purchasing power? Reduce their friction of making large purchases? Increase the security of the initial purchase and long-time use of the product or service? The competition for just a consumer’s current and future wallet is being upended by retailing offers that are serving up entertainment, services, convenience and broader product selections. Understanding the high-value activities correlated to their VIP consumers generating the highest amount of profit for the business is the essential to building strategies for encouraging card use. Beyond online shopping, are there other retail trends you see emerging in the coming year? What excites you about the space? Online shopping is not a trend; it is retail’s greatest disruption of the last 100 years. Digitization of shopping in both the online and store setting is what thrills me. One to watch is Wal-mart. The company is taking a highly energized track to build a business of next-gen brands and using their supply chain acumen to battle Amazon, while simultaneously gaining huge amounts of market share from other less sophisticated and strong retailers. In addition, seeing how next-gen brands like Warby Parker, Everlane, Untuckit, Bonobos, Indochino and Rent the Runway are rapidly building out a store experience, albeit radically different than the stores of the past, is exciting to watch. Seeing the growth in Drone deliveries outside the US for retail and commercial applications is surely the next big jump for ‘Next Hour’ in-home delivery. Made-to-order with a very short lead-time is also a big trend to keep an eye on. However, what excites me most in the industry is the universal mind shift that is becoming undeniable in retail: that data understanding and action will be the very basis for customer centricity and companies’ growth. Retailers have had access to these data pools for ages, but the ability to sync the data sets across channels, make sense of the findings and take action at the speed the consumer expects is truly the next leap forward for great retailers. To learn more about the state of retail credit cards, access our latest report.

With 81% of Americans having a social media profile, you may wonder if social media insights can be used to assess credit risk. When considering social media data as it pertains to financial decisions, there are 3 key concerns to consider. The ECOA requires that credit must be extended to all creditworthy applicants regardless of race, religion, gender, marital status, age and other personal characteristics. Social media can reveal these characteristics and inadvertently affect decisions. Social media data can be manipulated. Individuals can represent themselves as financially responsible when they’re not. On the flip side, consumers can’t manipulate their payment history. When it comes to credit decisions, always remember that the FCRA trumps everything. Data is essential for all aspects of the financial services industry, but it’s still too early to click the “like” button for social media. Make more insightful decisions with credit attributes>

The sheer range of dynamic and emerging fraud tactics can impede agencies from achieving security. These threats must be met with a variety of identity proofing and management tactics. Without monitoring, performance assessments and tuning, a singular and static identity proofing strategy can be exposed by evolving schemes and the use of high-quality compromised identity data. Traditional verification and validation parameters alone are simply too obtuse and can be circumvented easily by those with criminal intent. Static rules based on overly simplistic verification and validation checks can be outsmarted by intelligent fraudsters. Conversely, those same static rules must also have built-in mechanisms to accommodate true-name users who initially may not meet that criteria for identity proofing. Vast and diverse user populations, more arduous — and arguably more difficult to achieve — digital identity guidelines put forth by the National Institute of Standards and Technology, and operational constraints all pose significant challenges for government. But there are ways for government to modernize identity proofing successfully. Modern fraud and identity strategies There are many emerging trends and best practices for modern fraud and identity strategies, including: Applying right-sized fraud and identity proofing solutions. To reduce user friction or service disruption and manage fraud risk appropriately, agencies need to apply fraud mitigation strategies. Such strategies reflect the cost, measured risk and level of confidence, as well as compliance needed, for each interaction. This is called right-sizing the fraud solution. For example, agencies can cater a fraud solution that ensures a seamless experience when a citizen is calling a service center, versus an online interaction, versus a face-to-face one. Maintaining a universal view of the user. Achieved by employing a diverse breadth and depth of data assets and applied analytics, this tactic is the core of modern fraud mitigation and identity management. Knowing the individual user extends beyond a traditional 360-degree view. It means having knowledge of a person’s offline and online behavior, not only with your agency, but also with other agencies with which that user has a relationship. Expanding user view through a blended ecosystem. Increasingly, agencies are participating in a blended ecosystem — working with vendors, peer agencies and partners. There exists a collaborative culture in identity and fraud management that doesn’t exist in more competitive commercial environments. Fraudsters easily share information with one another, so those combatting it need to share information as well. Achieving agility and scale using service-based models. More agencies are adopting service-based models that provide greater agility and response to dynamic fraud threats, diverse population changes, and evolving compliance requirements or guidance. Service-based identity proofing provides government agencies the benefit of regularly updated data assets, analytics and expertise in strategy design. These assets are designed to respond to fraud or identity intelligence observed across various markets and industries, often protecting proactively rather than reactively. Future-proofing fraud solution choices. Technical and operational resources are always in relatively short supply compared to demand. Agencies need the ability to “code once” in order to expand and evolve their fraud strategies with ease. Future-proofing solutions must also be combined with an ever-changing set of identity proofing requirements and best practices, powered by a robust and innovative marketplace of service providers. The future of identity proofing in the public sector is more than just verifying individual identities. New standards in digital identity proofing are a responsive result of mass data compromise and failures in legacy techniques. Achieving compliant and confident identity assurance requires a layered approach, flexibly designed and orchestrated to accommodate diverse identity assertions, evidence, and contextual invocation of technologies and data assets. Government must now use risk-based approaches and mitigation strategies to identity threats quickly and determine the type of fraud before damage is done. Download our recent report in which we discuss the primary challenges of identity proofing in the public sector and what modernization of identity proofing looks like.

  Juniper Research recently recognized Experian as a Fraud Detection and Prevention Market Leader in its Online Payment Fraud Whitepaper. Juniper also shared important market insights in the report. The transactional value of card-not-present fraud is estimated to reach $19.3 billion in 2022. Online payment fraud is anticipated to grow 13.7% annually from 2017 to 2022. Digital banking fraud should reach $7.9 billion by 2022. $50.9 billion is expected to be spent on fraud detection and prevention software between 2017 and 2022. Fraud’s not going away anytime soon. Protecting your organization and customers is the new cost of doing business. Don’t wait until 2022 to start protecting yourself. Read the report>

The data to create synthetic identities is available. And the marketplace to exchange and monetize that data is expanding rapidly. The fact that hundreds of millions of names, addresses, dates of birth, and Social Security numbers (SSNs) have been breached in the last year alone, provides an easy path for criminals to surgically target new combinations of data. Armed with an understanding of the actual associations of these personally identifiable information (PII) elements, fraudsters can better navigate the path to perpetrate identity theft, identity manipulation, or synthetic identity fraud schemes on a grand scale. Using information such as birth dates and addresses in combination with Social Security numbers, criminals can target new combinations of data to yield better results with lower risk of detection. Some examples of this would be: identity theft, existing account takeovers, or the deconstruction and reconstruction of those PII elements to better create effective synthetic identities. Experian has continued to evolve and innovate against fraud risks and attacks with an understanding of attack rates, vectors, and the shifting landscape in data availability and security. In doing so, we’ve historically operated under the assumption that all PII is already compromised in some way or is easily done so. Because of this, we employ a layered approach, providing a more holistic view of an identity and the devices that are used over time by that identity. Relying solely on PII to validate and verify an identity is simply unwise and ineffective in this era of data compromise. We strive to continuously cultivate the broadest and most in-depth set of traditional, innovative and alternative data assets available. To do this, we must enable the integration of diverse identity attributes and intelligence to balance risk, while maintaining a positive customer experience. It’s been quite some time since the use of basic PII verification alone has been predictive of identity risk or confidence.  Instead, validation and verification is founded in the ongoing definition and association of identities, the devices commonly used by those individuals, and the historical trends in their behavior. Download our newest White Paper, Synthetic Identities: Getting real with customers, for an in-depth Experian perspective on this increasingly significant fraud risk.

If someone asked you for stats on your retail card portfolio, would you respond with the number of accounts? Average spend per month? Or maybe you know the average revolving balance and profitability. Notice something about that list? Too many lenders think of their portfolio and customers as numbers when in reality these are individuals expressing themselves through their transactions. In an age where consumers increasingly expect customized experiences, marketing to account #5496115149251 is likely to fall on deaf ears. Credit card transaction data including bankcard, retail, and debit cards holds a wealth of information about your consumers' tastes and preferences. Think about all the purchases you made using a credit card this past month. Did you shop at high-end retail stores or discount stores? Expensive restaurants or fast food? Did you buy new clothes for your kids? Maybe you went to the movies, or met friends at a bar. How you use your card paints a picture of who you are. The trick is turning all those numbers into insights. You may have been swept up in all the excitement around Apple’s announcement of the iPhone X in August. However, you may have overlooked the incorporation of Neural Embedding, or machine learning, as one of the most powerful features of the new phone. Experian DataLabs has developed an innovative approach to analyzing transaction data using similar techniques. Unstructured machine learning is applied and patterns begin to emerge around customer spending. The patterns are highly intuitive and give personality to what was previously an indecipherable stream of data. For example, one group may be more likely to spend on children’s clothing, child care services, and theme parks while another spends on expensive restaurants, airlines, and golf courses. If these two consumers happened to spend approximately the same each month on your card, you’d probably treat them as category. But understanding one is a young family and their other is jet setter allows you to tailor messaging, offers, and terms to their needs and use of your products. Further, you can ensure they have the best product based on their lifestyle to minimize silent attrition as their needs evolve. But it’s not just about marketing. When your latest attrition dashboard is updated, what period are you measuring? Do you analyze account closures from the previous month? Maybe a few months back? Understanding churn is important, but it’s inherently reactive and backward looking. You wouldn’t drive a car looking in the rearview mirror, would you? Experian enables clients to actively monitor the portfolio for attrition risk by analyzing usage patterns and predicting future spend. Transactions are then monitored up to daily and, when spend doesn’t occur as expected, an alert is sent so you can proactively attempt to save the account before it closes. These algorithms are finely tuned to reduce false positives that can come from seasonality or predictable gaps in spend such as only using a card at certain times during the week. Most importantly, it gives you an opportunity to manage each account and address changing customer needs instead of waiting for customers to call to cancel. So how well do you know your customers? If you’re still looking at them as numbers, it may be time to explore new capabilities that allow you to act small, no matter how large your portfolio. Transaction Data Insights brings cutting-edge machine learning capabilities to lenders of all sizes. By digging into behavioral segments and having tools to monitor and send alerts when a consumer is showing signs of attrition risk, card portfolios can suddenly treat customers like people, providing the customized experience they increasingly expect.  

Despite rising concerns about identity theft, most Americans aren’t taking basic steps to make it harder for their information to be stolen, according to a survey Experian conducted in August 2017: Nearly 3 in 4 consumers said they’re very or somewhat concerned their email, financial accounts or social media information could be hacked. This is up from 69% in a similar survey Experian conducted in 2015. Nearly 80% of survey respondents are concerned about using a public Wi-Fi network. Yet, barely half said they take the precaution of using a password-protected Wi-Fi network when using mobile devices. 59% of respondents are annoyed by safety precautions needed to use technology — up 12% from 2015. When your customer’s identity is stolen, it can negatively impact the consumer and your business. Leverage the tools and resources that can help you protect both. Protect your customers and your business>

Synthetic identity fraud is on the rise across financial services, ecommerce, public sector, health and utilities markets. The long-term impact of synthetic identity remains to be seen and will hinge largely upon forthcoming efforts across the identity ecosystem made up of service providers, institutions and agencies, data aggregators and consumers themselves. Making measurement more challenging is the fact that much of the assumed and confirmed losses are associated with credit risk and charge offs, and lack of common and consistent definitions and confirmation criteria. Here are some estimates on the scope of the problem: Losses due to synthetic identity fraud are projected to reach more than $800 million in 2017.* Average loss per account is more than $10,000.* U.S. synthetic credit card fraud is estimated to reach $1.257 billion in 2020.* As with most fraud, there is no miracle cure. But there are best practices, and topping that list is addressing both front- and back-end controls within your organization. Synthetic identity fraud webinar> *Aite Research Group

In 2017, 81 percent of U.S. Americans have a social media profile, representing a five percent growth compared to the previous year. Pick your poison. Facebook. Instagram. Twitter. Snapchat. LinkedIn. The list goes on, and it is clear social media is used by all. Grandma and grandpa are hooked, and tweens are begging for accounts. Factor in the amount of data being generated by our social media obsession – one report claims Americans are using 2,675,700 GB of Internet data per minute – and it makes some lenders wonder if social media insights can be used to assess credit risk. Can banks, credit unions and online lenders look at social media profiles when making a loan decision and garner intel to help them make a credit decision? After all, in some circles, people believe a person’s character is just as important as their income and assets when making a lending decision. Certainly, some businesses are seeing value in collecting social media insights for marketing purposes. An individual’s interests, likes and click-throughs reveal a lot about their lifestyle and potential brand linkages. But credit decisions are different. In fact, there are two key concerns when considering social media data as it pertains to financial decisions. There is that little rule called the Equal Credit Opportunity Act, which states credit must be extended to all creditworthy applicants regardless of race, religion, gender, marital status, age and other personal characteristics. A quick scan of any Facebook profile can reveal these things, and more. Credit applications do not ask for these specific details for this very reason. Social media data can also be manipulated. One can “like” financial articles, participate in educational quizzes and represent themselves as if they are financially responsible. Social media can be gamed. On the flip side, a consumer can’t manipulate their payment history. There is no question that data is essential for all aspects of the financial services industry, but when it comes to making credit decisions on a consumer, FCRA data trumps everything. In the consumer’s best interest, it is essential that credit data be both displayable and disputable. The right data must be used. For lenders, their primary goal is to assess a consumer’s stability, ability and willingness to pay. Today, social media can’t address those needs. It’s not to say that social media data can’t be used in the future, but financial institutions are still grappling with how it can be predictive of credit behavior over time. In the meantime, other sources of data are being evaluated. Everything from including on-time utility and rental payments, insights on smaller dollar loans and various credit attributes can help to provide a more holistic view of today’s credit consumer. There is no question social media data will continue to grow exponentially. But in the world of credit decisioning, the “like” button cannot be given quite yet.

  Our national survey found that consumers struggle to find a credit card that meets their needs. They say there are too many options and it’s too time-consuming to research. What do consumers want?     With 53% of survey respondents not satisfied with their current cards and 1 in 3 saying they’re likely to get a new card within 6 months, now’s the time to start personalizing offers and growing your portfolio. Start personalizing offers today>