Tag: customer experience

Recently, I shared articles about the problems surrounding third-party and first-party fraud. Now I’d like to explore a hybrid type – synthetic identity fraud – and how it can be the hardest type of fraud to detect. What is synthetic identity fraud? Synthetic identity fraud occurs when a criminal creates a new identity by mixing real and fictitious information. This may include blending real names, addresses, and Social Security numbers with fabricated information to create a single identity.   Once created, fraudsters will use their synthetic identities to apply for credit. They employ a well-researched process to accumulate access to credit. These criminals often know which lenders have more liberal identity verification policies that will forgive data discrepancies and extend credit to people who appear to be new or emerging consumers. With each account that they add, the synthetic identity builds more credibility.   Eventually, the synthetic identity will “bust out,” or max out all available credit before disappearing. Because there is no single person whose identity was stolen or misused there’s no one to track down when this happens, leaving businesses to deal with the fall out.   More confounding for the lenders involved is that each of them sees the same scam through a different lens. For some, these were longer-term reliable customers who went bad. For others, the same borrower was brand new and never made a payment. Synthetic identities don't appear consistently as a new account problem or a portfolio problem or correlate to thick- or thin-filed identities, further complicating the issue.   How does synthetic identity fraud impact me?   As mentioned, when synthetic identities bust out, businesses are stuck footing the bill.   Annual SIF (synthetic identity fraud) charge-offs in the United States alone could be as high as $11 billion. – Steven D’Alfonso, research director, IDC Financial Insights1   Unlike first- and third-party fraud, which deal with true identities and can be tracked back to a single person (or the criminal impersonating them), synthetic identities aren’t linked to an individual. This means that the tools used to identify those types of fraud won’t work on synthetics because there’s no victim to contact (as with third-party fraud), or real customer to contact in order to collect or pursue other remedies.   Solving the synthetic identity fraud problem   Preventing and detecting synthetic identities requires a multi-level solution that includes robust checkpoints throughout the customer lifecycle.   During the application process, lenders must look beyond the credit report. By looking past the individual identity and analyzing its connections and relationships to other individuals and characteristics, lenders can better detect anomalies to pinpoint false identities.   Consistent portfolio review is also necessary. This is best done using a risk management system that continuously monitors for all types of fraudulent activities across multiple use cases and channels. A layered approach can help prevent and detect fraud while still optimizing the customer experience.   With the right tools, data, and analytics, fraud prevention can teach you more about your customers, improving your relationships with them and creating opportunities for growth while minimizing fraud losses.   To wrap up this series, I’ll explore account takeover fraud and how the correct strategy can help you manage all four types of fraud while still optimizing the customer experience. To learn more about the impact of synthetic identities, download our “Preventing Synthetic Identity Fraud” white paper and call us to learn more about innovative solutions you can use to detect and prevent fraud.   Contact us Download whitepaper   1Synthetic Identity Fraud Update: Effects of COVID-19 and a Potential Cure from Experian, IDC Financial Insights, July 2020

COVID-19 is not only shifting the way we work, live and think, but it is also reframing the conversation behind which metrics successful companies focus on. Having worked in marketing for various lenders, origination and funding milestones were prevalent in their marketing. However, during this unique time in mortgage when most lenders are shattering previous origination records, focus is now drawn to new performance indicators. Providing a seamless digital process A recent McKinsey survey determined that consumer and business digital adoption vaulted five years forward in a matter of eight weeks at the beginning of the pandemic. And while this is generally true for business, many mortgage lenders may not have had the time or resources to update and modernize their processes due to massive origination volumes. When volume is good, companies wait to update their technology – either due to an “if it isn’t breaking why fix it” mentality, or, in the case of unmanageable volume, lenders can’t fathom disrupting their processes. Lenders that proactively streamlined technology and focused on digital adoption before the pandemic are leveraging and benefitting from the current mortgage environment. For lenders that did not digitize in time, the high-volume environment highlights their inefficiencies and unscalable processes. Providing meaningful customer experiences Forward-thinking, resilient mortgage lenders are also tracking how effectively they can provide meaningful customer experiences, for both their borrowers as well as their internal customers – their employees. For borrowers, it could come in the form of enjoying a seamless mortgage experience, being proactively kept abreast of their loan status, and the ability to interact and communicate with the lender in a manner that works best for their style. For employees of the company, this can come from feeling valued and listened to, with relevant and useful communications and resources to rely on during these uncertain times. It also comes in the form of providing the right resources for employees to perform at a high level during these times when it matters the most and working efficiently without sacrificing quality. Investing in technology and your greatest asset, your employees, is the answer to how mortgage lenders can achieve these metrics which will help them stand out among their competition. As the refi heyday starts to show signs of impermanence, these differentiators will become more important than ever – and all lenders should be taking a proactive look now at how they can bridge their digital gaps. Mortgage lenders are coming out of 2020 with strong earnings and should look to allocate a part of these earnings towards ‘future-proofing’ through scalable technology that will ultimately reduce costs and continue to bring in qualified volume. Join Experian Mortgage in accelerating the mortgage evolution and learn how we can help bridge your technology gaps. Learn More

The shift created by the COVID-19 pandemic is still being realized. One thing that we know for sure is that North American consumers’ expectations continue to rise, with a focus on online security and their digital experience.   In mid-September of this year, Experian surveyed 3,000 consumers and 900 businesses worldwide—with 300 consumers and 90 businesses in the U.S.—to explore the shifts in consumer behavior and business strategy pre- and post-COVID-19.   More than half of consumers surveyed continue to expect more security steps when online, including more visible security measures in place on websites and more knowledge about how their data is being protected and stored. However, those same consumers aren’t willing to wait more than 60 seconds to complete an online transaction making it more important than ever to align your security and experience strategies.   While U.S. consumers are optimistic about the economy’s recovery, they are still dealing with financial challenges and their behaviors have changed. Future business plans should take into account consumers’:   High expectations of their online experience Increases in online spending Difficulty paying bills Reduction in discretionary spending   Moving forward, businesses are focusing on use of AI, online security, and digital engagement. They are emphasizing revenue generation while looking into the future of online security. Nearly 70% of businesses also plan to increase their fraud management budgets in the next 6 months.   Download the full North America Insights Report to get all of the insights into North American business and consumer needs and priorities and keep visiting the Insights blog in the coming weeks for a look at how trends have changed from early in the pandemic. North America Insights Report Global Insights Report

This week, Experian released a new version of our CrossCore® digital identity and fraud risk platform, adding new tools and functionality to help businesses quickly respond to today’s emerging fraud threats. The ability to confidently recognize your customers and safeguard their digital transactions is becoming an increasing challenge for businesses. Fraud threats are already rising across the globe as fraudsters take advantage of the global health crisis and rapidly shifting economic conditions. CrossCore combines risk-based authentication, identity proofing and fraud detection into a single cloud platform, which means businesses can more quickly respond to an ever-changing environment. And with flexible decisioning orchestration and advanced analytics, businesses can make real-time risk decisions throughout the customer lifecycle. “Now more than ever, businesses need to lean on capabilities and technology that will allow them to rapidly respond in these challenging times, increase identity confidence in every transaction, and provide a safe and convenient experience for customers,” said E.K. Koh, Experian’s Senior Vice President of Global Identity & Fraud Solutions in a recent press release. “This new CrossCore release enables businesses to easily leverage best-in-class, pre-integrated identity and fraud services through simple self-service.” This new version of CrossCore features a cloud architecture, modern user interface, progressive risk assessments, faster response times, self-service workflow configuration, and a transactional volume reporting dashboard. These enhancements give you a simpler way to manage how backing applications are utilized, allow you to analyze key performance indicators in near real-time, and empower you to catch more fraud faster - without impacting the customer experience. “Recent Aite Group research shows that many banks have seen digital channel usage increase 250% in the wake of the pandemic, so ensuring a seamless and safe customer experience is more important than ever,” said Julie Conroy, Research Director at Aite Group. “Platforms such as CrossCore that can enable businesses to nimbly respond to changing patterns of customer behavior as well as rapidly evolving attack tactics are more important than ever, as financial services firms work to balance fraud mitigation with the customer experience.” CrossCore is the first identity and fraud platform that enables you to connect, access, and orchestrate decisions across multiple solutions. With the newest version, Experian enhances your ability to consolidate numerous fraud risk signals into a single, holistic assessment to improve operational processes, stay ahead of fraudsters, and protect your customers. Read Press Release Learn More About CrossCore

The response to the coronavirus (COVID-19) health crisis requires a brand-new mindset from businesses across the country. As part of our recently launched Q&A perspective series, Jim Bander, Market Lead of Analytics and Optimization and Kathleen Peters, Senior Vice President of Fraud and Identity, provided insight into how businesses can work to mitigate fraud and portfolio risk. Q: How can financial institutions mitigate fraud risk while monitoring portfolios? JB: The most important shift in portfolio monitoring is the view of the customer, because it’s very different during times of crisis than it is during expansionary periods. Financial institutions need to take a holistic view of their customers and use additional credit dimensions to understand consumers’ reactions to stress. While many businesses were preparing for a recession, the economic downturn caused by the coronavirus has already surpassed the stress-testing that most businesses performed. To help mitigate the increased risk, businesses need to understand how their stress testing was performed in the past and run new stress tests to understand how financially sound their institution is. KP: Most businesses—and particularly financial institutions—have suspended or relaxed many of their usual risk mitigation tools and strategies, in an effort to help support customers during this time of uncertainty. Many financial institutions are offering debt and late fee forgiveness, credit extensions, and more to help consumers bridge the financial gaps caused by the economic downturn. Unfortunately, the same actions that help consumers can hamstring fraud prevention efforts because they impact the usual risk indicators. To weather this storm, financial institutions need to pivot from standard risk mitigation strategies to more targeted fraud and identity strategies. Q: How can financial institutions’ exposure to risk be managed? JB: Financial institutions are trying to extend as much credit as is reasonably possible—per government guidelines—but when the first stage of this crisis passes, they need to be prepared to deal with the consequences. Specifically, which borrowers will actually repay their loans. Financial institutions should monitor consumer health and use proactive outreach to offer assistance while keeping a finger on the pulse of their customers’ financial health. For the foreseeable future, the focus will be on extending credit, not collecting on debt, but now is the time to start preparing for the economic aftermath. Consumer health monitoring is key, and it must include a strategy to differentiate credit abusers and other fraudsters from overall good consumers who are just financially stressed. KP: As financial institutions work to get all of their customers set up with online and mobile banking and account access, there’s an influx of new requests that all require consumer authentication, device identification, and sometimes even underwriting. All of this puts pressure on already strained resources which means increased fraud risk. To manage this risk, businesses need to balance customer experience—particularly minimizing friction—with vigilance against fraudsters and reputational risk. It will require a robust and flexible fraud strategy that utilizes automated tools as much as possible to free up personnel to follow up on the riskiest users and transactions.   Experian is closely monitoring the updates around the coronavirus outbreak and its widespread impact on both consumers and businesses. We will continue to share industry-leading insights to help financial institutions manage their portfolios and protect against losses. Learn more About Our Experts: [avatar user="jim.bander" /] Jim Bander, Market Lead, Analytics and Optimization, Experian Decision Analytics, North America Jim joined Experian in April 2018 and is responsible for solutions and value propositions applying analytics for financial institutions and other Experian business-to-business clients throughout North America. He has over 20 years of analytics, software, engineering and risk management experience across a variety of industries and disciplines. Jim has applied decision science to many industries, including banking, transportation and the public sector. [avatar user="kathleen.peters" /] Kathleen Peters, Vice President, Fraud and Identity, Experian Decision Analytics, North America Kathleen joined Experian in 2013 to lead business development and international sales for the recently acquired 41st Parameter business in San Jose, Calif. She went on to lead product management for Experian’s fraud and identity group within the global Decision Analytics organization, launching Experian’s CrossCore® platform in 2016, a groundbreaking and award-winning new offering for the fraud and identity market. The last two years, Kathleen has been named a “Top 100 Influencer in Identity” by One World Identity (OWI), an exclusive list that annually recognizes influencers and leaders from across the globe, showcasing a who’s who of people to know in the identity space.

It may be a new decade of disruption, but one thing remains constant – the consumer is king. As such, customer experience (and continually evolving digital transformations necessary to keep up), digital expansion and all things identity will also reign supreme as we enter this new set of Roaring 20s. Here are seven of the top trends to keep tabs of through 2020 and beyond. 1. Data that does more – 100 million borrowers and counting Traditional, alternative, public record, consumer-permissioned, small business, big business, big, bigger, best – data has a lot of adjectives preceding it. But no matter how we define, categorize and collate data, the truth is there’s a lot of it that’s untapped, which is keeping financial institutions from operating at their max efficiency levels. Looking for ways to be bigger and bolder? Start with data to engage your credit-worthy consumer universe and beyond. Across the entire lending lifecycle, data offers endless opportunities – from prospecting and acquisitions to fraud and risk management. It fuels any technology solution you have or may want to implement over the coming year. Additionally, Experian is doing their part to create a more holistic picture of consumer creditworthiness with the launch of Experian LiftTM in November. The new suite of credit score products combines exclusive traditional credit, alternative credit and trended data assets, intended to help credit invisible and thin-file consumers gain access to fair and affordable credit. "We're committed to improving financial access while helping lenders make more informed decisions. Experian Lift is our latest example of this commitment brought to life,” said Greg Wright, Executive Vice President and Chief Product Officer for Experian Consumer Information Services. “Through Experian Boost, we're empowering consumers to play an active role in building their credit histories. And, with Experian Lift, we're empowering lenders to identify consumers who may otherwise be excluded from the traditional credit ecosystem,” he said. 2. Identity boom for the next generation Increasingly digital lifestyles have put personalization and frictionless transactions on hyperdrive. They are the expectation, not a nice-to-have. Having customer intelligence will become a necessary survival strategy for those in the market wanting to compete. Identity is not just for marketing purposes; it must be leveraged across the lending lifecycle and every customer interaction. Fragmented customer identities are more than flawed for decisioning purposes, which could potentially lead to losses. And, of course, the conversation around identity would be incomplete without a nod to privacy and security considerations. With the roll-out of the California Consumer Privacy Act (CCPA) earlier this month, we will wait to see if the other states follow suit. Regardless, consumers will continue to demand security and trust. 3. All about artificial intelligence and machine learning We get it – we all want the fastest, smartest, most efficient processes on limited – and/or shrinking – budgets. But implementing advanced analytics for your financial institution doesn’t have to break the bank. And, when it comes to delivering services and messaging to customers the way they want it, how to do that means digital transformation – specifically, leveraging big data and actionable analytics to evaluate risk, uncover industry intel and improve decisioning. One thing’s for certain, financial institutions looking to compete, gain traction and pull away from the competition in this next decade will need to do so by leveraging a future-facing partner’s expertise, platforms and data. AI and machine learning model development will go into hyperdrive to add accuracy, efficiency, and all-out speed. Real-time transactional processing is where it’s at. 4. Customer experience drives decisioning and everything Faster, better, more frictionless. 2020 and the decade will be all about making better decisions faster, catering to the continually quickening pace of consumer attention and need. Platforms and computing language aside, how do you increase processing speed at the same time as increasing risk mitigation? Implementing decisioning environments that cater to consumer preferences, coupled with best-in-class data are the first two steps to making this happen. This can facilitate instant decisioning within financial institutions. Looking beyond digital transformation, the next frontier is digital expansion. Open platforms enable financial institutions to readily add solutions from numerous providers so that they can connect, access and orchestrate decisions across multiple systems. Flexible APIs, single integrations and better strategy and design build the foundation of the framework to be implemented to enhance and elevate customer experience as it’s known today. 5. Credit marketing that keeps up with the digital, instant-gratification age Know your customer may be a common acronym for the financial services industry, but it should also be a baseline for determining whether to send a specific message to clients and prospects. From the basics, like prescreen, to omni-channel marketing campaigns, financial institutions need to leverage the communication channels that consumers prefer. From point of sale to mobile – there are endless possibilities to fit into your consumers’ credit journey. Marketing is clearly not a one-and-done tactic, and therefore multi-channel prequalification offers and other strategies will light the path for acquisitions and cross-sell/up-sell opportunities to come. By developing insights from customer data, financial institutions have a clear line of sight into determining optimal strategies for customer acquisition and increasing customer lifetime value. And, at the pinnacle, the modern customer acquisition engine will continue to help financial institutions best build, test and optimize their customer channel targeting strategies faster than ever before. From segmentation to deployment, and the right data across it all, today and tomorrow’s technology can solve many of financial organizations’ age-old customer acquisition challenges. 6. Three Rs: Recession, regulatory and residents of the White House Last March, the yield curve inverted for the first time since 2007. Though the timing of the next economic correction is debated, messaging is consistent around making a plan of action now. Whether it’s arming your collections department, building new systems, updating existing systems, or adjusting rules and strategy, there are gaps every organization needs to fill. By leveraging the stability of the economy now, financial institutions can put strategies in place to maximize profitability, manage risk, reduce bad debt/charge-offs, and ensure regulatory compliance among their list of to-do’s, ultimately resulting in a more efficient, better-performing program. Also, as we near the election later this year, the regulatory landscape will likely change more than the usual amount. Additionally, we will witness the first accounts of what CECL looks like for SEC-filing financial institutions (and if that will suggest anything for how non-SEC-filing institutions may fare as their deadline inches closer), as well as see the initial implications of the CCPA roll out and whether it will pave a path for other states to follow. As system sophistication continues to evolve, so do the risks (like security breaches) and new regulatory standards (like GDPR and CCPA) which provide reasons for organizations to transform. 7. Focus on fraud (in all forms) With evolving technology, comes evolved fraudsters. Whether it’s loyalty and rewards programs, account openings, breaches, there are so many angles and entry points. Synthetic identity fraud is the fastest-growing type of financial crime in the United States. The cost to businesses is estimated to grow to $1.2 billion by 2020, according to the Aite Group. To ensure the best protection for your business and your customers, a layered, risk-based approach to fraud management provides the highest levels of confidence in the industry. Balance is key – while being compliant with regulatory requirements and conscious of user experience, ensuring consumers’ peace of mind is priority one. Not a new trend, but recognizing fraud and recognizing good consumers will save continue to save financial institutions money and reputational harm, driving significant improvement in key performance indicators. Using the right data (and aggregating multiple data sets) and digital device intelligence tools is the one-two punch to protect your bottom line. For all your needs in 2020 and throughout the next decade, Experian has you covered. Learn more

With the growing need for authentication and security, fintechs must manage risk with minimal impact to customer experience. When implementing tactical approaches for fraud risk strategy operations, keeping up with the pace of fraud is another critical consideration. How can fintechs be proactive about future-proofing fraud strategies to stay ahead of savvy fraudsters while maintaining customer expectations? I sat down with Chris Ryan, Senior Fraud Solutions Business Consultant with Experian Decision Analytics, to tap into some of his insights. Here’s what he had to say: How have changes in technology added to increased fraud risk for businesses operating in the online space? Technology introduces many risks in the online space. As it pertains to the fintech world, two stand out. First, the explosion in mobile technology. The same capabilities that make fintech products broadly accessible makes them vulnerable. Anyone with a mobile device can attempt to access a fintech and try their hand at committing fraud with very little risk of being caught or punished. Second, the evolution of an interconnected, digital ‘marketplace’ for stolen data. There’s an entire underground economy that’s focused on connecting the once-disparate pieces of information about a specific individual stolen from multiple, unrelated data breaches. Criminal misrepresentations are more complete and more convincing than ever before. What are the major market drivers and trends that have attributed to the increased risk of fraud? Ultimately, the major market drivers and trends that drive fraud risk for fintechs are customer convenience and growth. In terms of customer convenience, it’s a race to meet customer needs in real time, in a single online interaction, with a minimally invasive request for information. But, serving the demands of good customers opens opportunities for identity misuse. In terms of growth, the pressure to find new pockets of potential customers may lead fintechs into markets where consumer information is more limited, so naturally, there are some risks baked in. Are fintechs really more at risk for fraud? If so, how are fintechs responding to this dynamic threat? The challenge for many fintechs has been the prioritization of fraud as a risk that needs to be addressed. It’s understandable that fintech’s initial emphasis had to be the establishment of viable products that meet the needs of their customers. Obviously, without customers using a product, nothing else matters. Now that fintechs are hitting their stride in terms of attracting customers, they’re allocating more of their attention and innovative spirit to other areas, like fraud. With the right partner, it’s not hard for fintechs to protect themselves from fraud. They simply need to acquire reliable data that provides identity assurance without negatively impacting the customer experience. For example, fintechs can utilize data points that can be extracted from the communications channel, like device intelligence for example, or non-PII unique identifiers like phone and email account data. These are valuable risk indicators that can be collected and evaluated in real time without adding friction to the customer experience. What are the major fraud risks to fintechs and what are some of the strategies that Risk Managers can implement to protect their business? The trends we’ve talked about so far today have focused more on identity theft and other third-party fraud risks, but it’s equally important for fintechs to be mindful of first party fraud types where the owner of the identity is the culprit. There is no single solution, so the best strategy recommendation is to plan to be flexible. Fintechs demonstrate an incredible willingness to innovate, and they need to make sure the fraud platforms they pick are flexible enough to keep pace with their needs. From your perspective, what is the future of fraud and what should fintechs consider as they evolve their products? Fraud will continue to be a challenge whenever something of value is made available, particularly when the transaction is remote and the risk of any sort of prosecution is very low. Criminals will continue to revise their tactics to outwit the tools that fintechs are using, so the best long-term defense is flexibility. Being able to layer defenses, explore new data and analytics, and deploy flexible and dynamic strategies that allow highly tailored decisions is the best way for fintechs to protect themselves. Digital commerce and the online lending landscape will continue to grow at an increasing pace – hand-in-hand with the opportunities for fraud. To stay ahead of fraudsters, fintechs must be proactive about future-proofing their fraud strategies and toolkits. Experian can help. Our Fintech Digital Onboarding Bundle provides a solid baseline of cutting-edge fraud tools that protect fintechs against fraud in the digital space, via a seamless, low-friction customer experience. More importantly, the Fintech Digital Onboarding Bundle is delivered through Experian’s CrossCore platform—the premier platform in the industry recognized specifically for enabling the expansion of fraud tools across a wide range of Experian and third-party partner solutions. Click here to learn more or to speak with an Experian representative. Learn More About Chris Ryan:  Christopher Ryan is a Senior Fraud Solutions Business Consultant. He delivers expertise that helps clients make the most from data, technology and investigative resources to combat and mitigate fraud risks across the industries that Experian serves. Ryan provides clients with strategies that reduce losses attributable to fraudulent activity. He has an impressive track record of stopping fraud in retail banking, auto lending, deposits, consumer and student lending sectors, and government identity proofing. Ryan is a subject matter expert in consumer identity verification, fraud scoring and knowledge-based authentication. His expertise is his ability to understand fraud issues and how they impact customer acquisition, customer management and collections. He routinely helps clients review workflow processes, analyze redundancies and identify opportunities for process improvements. Ryan recognizes the importance of products and services that limit fraud losses, balancing expense and the customer impact that can result from trying to prevent fraud.

In today’s ever-changing and hypercompetitive environment, the customer experience has taken center-stage – highlighting new expectations in the ways businesses interact with their customers. But studies show financial institutions are falling short. In fact, a recent study revealed that 94% of banking firms can’t deliver on the “personalization promise.” It’s not difficult to see why. Consumer preferences have changed, with many now preferring digital interactions. This has made it difficult for financial institutions to engage with consumers on a personal level. Nevertheless, customers expect seamless, consistent, and personalized experiences – that’s where the power of advanced analytics comes into play. It’s no secret that using advanced analytics can enable businesses to turn rich data into insights that lead to confident business decisions and strategy development. But these business tools can actually help financial institutions deliver on that promise of personalization. According to an Experian study, 90% of organizations say that embracing advanced analytics is critical to their ability to provide an excellent customer experience. By using data and analytics to anticipate and respond to customer behavior, companies can develop new and creative ways to cater to their audiences – revolutionizing the customer experience as a whole. It All Starts With Data Data is the foundation for a successful digital transformation – the lack of clean and cohesive datasets can hinder the ability to implement advanced analytic capabilities. However,  89% of organizations face challenges on how to effectively manage and consolidate their data, according to Experian’s Global Data Management Research Benchmark Report of 2019. Because consumers prefer digital interactions, companies have been able to gather a vast amount of customer data. Technology that uses advanced analytic capabilities (like machine learning and artificial intelligence) are capable of uncovering patterns in this data that may not otherwise be apparent, therefore opening doors to new avenues for companies to generate revenue. To start, companies need a strategy to access all customer data from all channels in a cohesive ecosystem – including data from their own data warehouses and a variety of different data sources. Depending on their needs, the data elements can come from a third party data provider such as: a credit bureau, alternative data, marketing data, data gathered during each customer contact, survey data and more. Once compiled, companies can achieve a more holistic and single view of their customer. With this single view, companies will be able to deliver more relevant and tailored experiences that are in-line with rising customer expectations. From Personalized Experiences to Predicting the Future The most progressive financial institutions have found that using analytics and machine learning to conquer the wide variety of customer data has made it easier to master the customer experience. With advanced analytics, these companies gain deeper insights into their customers and deliver highly relevant and beneficial offers based on the holistic views of their customers. When data is provided, technology with advanced analytic capabilities can transform this information into intelligent outputs, allowing companies to optimize and automate business processes with the customer in mind. Data, analytics and automation are the keys to delivering better customer experiences. Analytics is the process of converting data into actionable information so firms can understand their customers and take decisive action. By leveraging this business intelligence, companies can quickly adapt to consumer demand. Predictive models and forecasts, increasingly powered by machine learning, help lenders and other businesses understand risks and predict future trends and consumer responses. Prescriptive analytics help offer the right products to the right customer at the right time and price. By mastering all of these, businesses can be wherever their customers are. The Experian Advantage With insights into over 270 million customers and a wealth of traditional credit and alternative data, we’re able to drive prescriptive solutions to solve your most complex market and portfolio problems across the customer lifecycle – while reinventing and maintaining an excellent customer experience. If your company is ready for an advanced analytical transformation, Experian can help get you there. Learn More

AI, machine learning, and Big Data – these are no longer just buzzwords. The advanced analytics techniques and analytics-based tools that are available to financial institutions today are powerful but underutilized. And the 30% of banks, credit unions and fintechs successfully deploying them are driving better data-driven decisions, more positive customer experiences and stronger profitability. As the opportunities surrounding advanced analytics continue to grow, more lenders are eager to adopt these capabilities to make the most of their datasets. And it’s understandable that financial institution are excited at the possibilities and insights that advanced analytics can bring to their business. However, there are some key considerations to keep in mind as you begin this important digital transformation. Here are three things you should do as your financial institution begins its advanced analytics journey. Ensure consistent and clean data quality Companies have a plethora of data and information on their customers. The main hurdles that many organizations face is being able to turn this information into a clean and cohesive dataset and formulating an effective and long-term data management strategy. Trying to implement advanced analytic capabilities while lacking an effective data governance strategy is like building a house on a poor foundation – likely to fail. Data quality issues, such as inconsistent data, data gaps, and incomplete and duplicated data, also haunt many organizations, making it difficult to complete their analytics objectives. Ensuring that issues in data quality are managed is the key to gaining the correct insights for your business.   Establish and maintain a single view of customers The power of advanced analytics can only be as strong as the data provided. Unfortunately, many companies don’t realize that advanced analytics is much more powerful when companies are able to establish a single view of their customers. Companies need to establish and maintain a single view of customers in order to begin implementing advanced analytic capabilities. According to Experian research, a single customer view is a consistent, accurate and holistic view of your organization’s customers, prospects, and their data. Having full visibility and a 360 view into your customers paves the way for companies to make personalized, relevant, timely and precise decisions. But as many companies have begun to realize, getting this single view of customers is easier said than done. Organizations need to make sure that data should always be up-to-date, unique and available in order to begin a complete digital transformation.   Ensure the right resources and commitment for your advanced analytics initiative It’s important to have the top-down commitment within your organization for advanced analytics. From the C-suite down, everyone should be on the same page as to the value analytics will bring and the investment the project might require. Organizations that want to move forward with implementing advanced analytic capabilities need to make sure to set aside the right financial and human resources that will be needed for the journey. This may seem daunting, but it doesn’t have to be. A common myth is that the costs of new hardware, new hires and the costs required to maintain, configure, and set up new technology will make advanced analytics implementation far too expensive and difficult to maintain. However, many organizations don’t realize that it’s not necessary to allocate large capital expenses to implement advanced analytics. All it takes is finding the right-sized solution with configurations to fit the team size and skill level in your organization. Moreover, finding the right partner and team (whether internal or external) can be an efficient way to fill temporary skills gaps on your team. No digital transformation initiative is without its challenges. However, beginning your advanced analytics journey on the right footing can deliver unparalleled growth, profitability and opportunities. Still not sure where to begin? At Experian, we offer a wide range of solutions to help you harness the full power and potential of data and analytics. Our consultants and development teams have been a game-changer for financial institutions, helping them get more value, insight and profitability out of their data and modeling than ever before. Learn More

It seems like artificial intelligence (AI) has been scaring the general public for years – think Terminator and SkyNet. It’s been a topic that’s all the more confounding and downright worrisome to financial institutions. But for the 30% of financial institutions that have successfully deployed AI into their operations, according to Deloitte, the results have been anything but intimidating. Not only are they seeing improved performance but also a more enhanced, positive customer experience and ultimately strong financial returns. For the 70% of financial institutions who haven’t started, are just beginning their journey or are in the middle of implementing AI into their operations, the task can be daunting. AI, machine learning, deep learning, neural networks—what do they all mean? How do they apply to you and how can they be useful to your business? It’s important to demystify the technology and explain how it can present opportunities to the financial industry as a whole. While AI seems to have only crept into mainstream culture and business vernacular in the last decade, it was first coined by John McCarthy in 1956. A researcher at Dartmouth, McCarthy thought that any aspect of learning or intelligence could be taught to a machine. Broadly, AI can be defined as a machine’s ability to perform cognitive functions we associate with humans, i.e. interacting with an environment, perceiving, learning and solving problems. Machine learning vs. AI Machine learning is not the same thing as AI. Machine learning is the application of systems or algorithms to AI to complete various tasks or solve problems. Machine learning algorithms can process data inputs and new experiences to detect patterns and learn how to make the best predictions and recommendations based on that learning, without explicit programming or directives. Moreover, the algorithms can take that learning and adapt and evolve responses and recommendations based on new inputs to improve performance over time. These algorithms provide organizations with a more efficient path to leveraging advanced analytics. Descriptive, predictive, and prescriptive analytics vary in complexity, sophistication, and their resulting capability. In simplistic terms, descriptive algorithms describe what happened, predictive algorithms anticipate what will happen, and prescriptive algorithms can provide recommendations on what to do based on set goals. The last two are the focus of machine learning initiatives used today. Machine learning components - supervised, unsupervised and reinforcement learning Machine learning can be broken down further into three main categories, in order of complexity: supervised, unsupervised and reinforcement learning. As the name might suggest, supervised learning involves human interaction, where data is loaded and defined and the relationship to inputs and outputs is defined. The algorithm is trained to find the relationship of the input data to the output variable. Once it delivers accurately, training is complete, and the algorithm is then applied to new data. In financial services, supervised learning algorithms have a litany of uses, from predicting likelihood of loan repayment to detecting customer churn. With unsupervised learning, there is no human engagement or defined output variable. The algorithm takes the input data and structures it by grouping it based on similar characteristics or behaviors, without a defined output variable. Unsupervised learning models (like K-means and hierarchical clustering) can be used to better segment or group customers by common characteristics, i.e. age, annual income or card loyalty program. Reinforcement learning allows the algorithm more autonomy in the environment. The algorithm learns to perform a task, i.e. optimizing a credit portfolio strategy, by trying to maximize available rewards. It makes decisions and receives a reward if those actions bring the machine closer to achieving the total available rewards, i.e. the highest acquisition rate in a customer category. Over time, the algorithm optimizes itself by correcting actions for the best outcomes. Even more sophisticated, deep learning is a category of machine learning that involves much more complex architecture where software-based calculators (called neurons) are layered together in a network, called a neural network. This framework allows for much broader, complex data ingestion where each layer of the neural network can learn progressively more complex elements of the data. Object classification is a classic example, where the machine ‘learns’ what a duck looks like and then is able to automatically identify and group images of ducks. As you might imagine, deep learning models have proved to be much more efficient and accurate at facial and voice recognition than traditional machine learning methods. Whether your financial institution is already seeing the returns for its AI transformation or is one of the 61% of companies investing in this data initiative in 2019, having a clear picture of what is available and how it can impact your business is imperative. How do you see AI and machine learning impacting your customer acquisition, underwriting and overall customer experience?

Over the years, businesses have gathered a plethora of datasets on their customers. However, there is no value in data alone. The true value comes from the insights gained and actions that can be derived from these datasets. Advanced analytics is the key to understanding the data and extracting the critical information needed to unlock these insights. AI and machine learning in particular, are two emerging technologies with advanced analytics capabilities that can help companies achieve their business goals. According to an IBM survey, 61% of company executives indicated that machine learning and AI are their company’s most significant data initiatives in 2019. These leaders recognize that advanced analytics is transforming the way companies traditionally operate. It is no longer just a want, but a must. With a proper strategy, advanced analytics can be a competitive differentiator for your financial institution. Here are some ways that advanced analytics can empower your organization: Provide Personalized Customer Experiences Business leaders know that their customers want personalized, frictionless and enhanced experiences. That’s why improving the customer experience is the number one priority for 80 percent of executives globally, according to an Experian study. The data is already there – companies have insights into what products their customers like, the channels they use to communicate, and other preferences. By utilizing the capabilities of advanced analytics, companies can extract more value from this data and gain better insights to help create more meaningful, personalized and profitable lending decisions. Reduce Costs Advanced analytics allows companies to deploy new models and strategies more efficiently – reducing expenses associated with managing models for multiple lending products and bureaus. For example, OneMain Financial, was able to successfully drive down risk modeling expenses after implementing a solution with advanced analytics capabilities. Improve Accuracy and Speed to Market To stay ahead of the competition, companies need to maintain fast-moving environments. The speed, accuracy and power of a company’s predictive models and forecasts are crucial for success. Being able to respond to changing market conditions with insights derived from advanced analytics is a key differentiator for future-forward companies. Advanced analytic capabilities empower companies to anticipate new trends and drive rapid development and deployment, creating an agile environment of continual improvement. Drive Growth and Expand Your Customer Base With the rise of AI, machine learning and big data, the opportunities to expand the credit universe is greater than ever. Advanced analytic capabilities allow companies to scale datasets and get a bird’s eye view into a consumer’s true financial position – regardless of whether they have a credit history. The insights derived from advanced analytics opens doors for thin file or credit invisible customers to be seen – effectively allowing lenders to expand their customer base. Meet Compliance Requirements Staying on top of model risk and governance should always remain top of mind for any institution. Analytical processing aggregates and pulls new information from a wide range of data sources, allowing your institution to make more accurate and faster decisions. This enables lenders to lend more fairly, manage models that stand up to regulatory scrutiny, and keep up with changes in reporting practices and regulations. Better, faster and smarter decisions. It all starts with advanced analytics. Businesses must take advantage of the opportunities that come with implementing advanced analytics, or risk losing their customers to more future-forward organizations. At Experian, we believe that using big data can help power opportunities for your company. Learn how we can help you leverage your data faster and more effectively. Learn More

A few months ago, I got a letter from the DMV reminding me that it was finally time to replace my driver’s license. I’ve had it since I was 21 and I’ve been dreading having to get a new one. I was especially apprehensive because this time around I’m not just getting a regular old driver’s license, I’m getting a REAL ID. For those of you who haven’t had this wonderful experience yet, a REAL ID is the new form of driver’s license (or state ID) that you’ll need to board a domestic flight starting October 1, 2020. Some states already offered compliant IDs, but others—like California, where I’m from—didn’t. This means that if I want to fly within the U.S. using my driver’s license next year, I can’t renew by mail. It’s Easier Than It Looks Imagine my surprise when I started the process to schedule my appointment, and the California DMV website made things really easy! There’s an online application you can fill out before you get to the DMV and they walk you through the documents to bring to the appointment (which I was able to schedule online). Despite common thought that the DMV and agencies like it are slow to adopt technology, the ease of this process may indicate a shift toward a digital-first mindset. As financial institutions embrace a similar shift, they’ll be better positioned to meet the needs of customers. Case in point, the electronic checklist the DMV provided to prepare me for my appointment. I sailed through the first two parts of the checklist, confirming that I’ll bring my proof of identity and social security number, but I paused when I got to the “Two Proofs of Residency” screen. Like many people my age—read: 85% of the millennial population, according to a recent Experian study—I don’t have a mortgage or any other documents relating to property ownership. I also don’t have my name on my utilities (thanks, roomie) or my cell phone bill (thanks Mom). I do however have a signed lease with my name on it, plus my renter’s insurance, both of which are acceptable as proof of residency. And just like that, I’m all set to get my REAL ID, even though I don’t have some of the basic adulting documents you might expect, because the DMV took into account the fact that not all REAL ID applicants are alike. Imagine if lenders could adopt that same flexibility and create opportunities for the more than 45 million U.S. consumers1 who lack a credit report or have too little information to generate a credit score. The Bigger Picture By removing some of the usual barriers to entry, the DMV made the process of getting my REAL ID much easier than it might have been and corrected my assumptions about how difficult the process would be. Experian has the same line of thought when it comes to helping you determine whether a borrower is credit-worthy. Just because someone doesn’t have a credit card, auto loan or other traditional credit score contributor doesn’t mean they should be written off. That’s why we created Experian BoostTM, a product that lets consumers give read-only access to their bank accounts and add in positive utility and telecommunications bill payments to their credit file to change their scores in real time and demonstrate their stability, ability and willingness to repay. It’s a win-win for lenders and consumers. 2 out of 3 users of Experian Boost see an increase in their FICO Score and of those who saw an increase, 13% moved up a credit tier. This gives lenders a wider pool to market to, and thanks to their improved credit scores, those borrowers are eligible for more attractive rates. Increasing your flexibility and removing barriers to entry can greatly expand your potential pool of borrowers without increasing your exposure to risk. Learn more about how Experian can help you leverage alternative credit data and expand your customer base in our 2019 State of Alternative Data Whitepaper. Read Full Report 1Kenneth P. Brevoort, Philipp Grimm, Michelle Kambara. “Data Point: Credit Invisibles.” The Consumer Financial Protection Bureau Office of Research. May 2015.

The future is, factually speaking, uncertain. We don't know if we'll find a cure for cancer, the economic outlook, if we'll be living in an algorithmic world or if our work cubical mate will soon be replaced by a robot. While futurists can dish out some exciting and downright scary visions for the future of technology and science, there are no future facts. However, the uncertainty presents opportunity. Technology in today's world From the moment you wake up, to the moment you go back to sleep, technology is everywhere. The highly digital life we live and the development of our technological world have become the new normal. According to The International Telecommunication Union (ITU), almost 50% of the world's population uses the internet, leading to over 3.5 billion daily searches on Google and more than 570 new websites being launched each minute. And even more mind-boggling? Over 90% of the world's data has been created in just the last couple of years. With data growing faster than ever before, the future of technology is even more interesting than what is happening now. We're just at the beginning of a revolution that will touch every business and every life on this planet. By 2020, at least a third of all data will pass through the cloud, and within five years, there will be over 50 billion smart connected devices in the world. Keeping pace with digital transformation At the rate at which data and our ability to analyze it are growing, businesses of all sizes will be forced to modify how they operate. Businesses that digitally transform, will be able to offer customers a seamless and frictionless experience, and as a result, claim a greater share of profit in their sectors. Take, for example, the financial services industry - specifically banking. Whereas most banking used to be done at a local branch, recent reports show that 40% of Americans have not stepped through the door of a bank or credit union within the last six months, largely due to the rise of online and mobile banking. According to Citi's 2018 Mobile Banking Study, mobile banking is one of the top three most-used apps by Americans. Similarly, the Federal Reserve reported that more than half of U.S. adults with bank accounts have used a mobile app to access their accounts in the last year, presenting forward-looking banks with an incredible opportunity to increase the number of relationship touchpoints they have with their customers by introducing a wider array of banking products via mobile. Be part of the movement Rather than viewing digital disruption as worrisome and challenging, embrace the uncertainty and potential that advances in new technologies, data analytics and artificial intelligence will bring. The pressure to innovate amid technological progress poses an opportunity for us all to rethink the work we do and the way we do it. Are you ready? Learn more about powering your digital transformation in our latest eBook. Download eBook Are you an innovation junkie? Join us at Vision 2020 for future-facing sessions like:  -  Cloud and beyond - transforming technologies - ML and AI - real-world expandability and compliance

Today is National Fintech Day – a day that recognizes the ever-important role that fintech companies play in revolutionizing the customer experience and altering the financial services landscape. Fintech. The word itself has become synonymous with constant innovation, agile technology structures and being on the cusp of the future of finance. Fintech challengers are disrupting existing financial models by leveraging data, advanced analytics and technology – both inspiring traditional financial institutions in their digital transformation strategies and giving consumers access to a variety of innovative financial products and services. But to us at Experian, National Fintech Day means more than just financial disruption. National Fintech Day represents the partnerships we have carefully fostered with our fintech clients to drive financial inclusion for millions of people around the globe and provide consumers with greater control and more opportunities to access the quality credit they deserve. “We are actively seeking out unresolved problems and creating products and technologies that will help transform the way businesses operate and consumers thrive in our society. But we know we can’t do it alone,” said Experian North American CEO, Craig Boundy in a recent blog article on Experian’s fintech partnerships. “That’s why over the last year, we have built out an entire team of account executives and other support staff that are fully dedicated to developing and supporting partnerships with leading fintech companies. We’ve made significant strides that will help us pave the way for the next generation of lending while improving the financial health of people around the world.” At Experian, we understand the challenges fintechs face – and our real-world solutions help fintech clients stay ahead of constantly changing market conditions and demands. “Experian’s pace of innovation is very impressive – we are helping both lenders and consumers by delivering technological solutions that make the lending ecosystem more efficient,” said Experian Senior Account Executive Warren Linde. “Financial technology is arguably the most important type of tech out there, it is an honor to be a part of Experian’s fintech team and help to create a better tomorrow.” If you’d like to learn more about Experian’s fintech solutions, visit us at Experian.com/Fintech.

The fact that the last recession started right as smartphones were introduced to the world gives some perspective into how technology has changed over the past decade. Organizations need to leverage the same technological advancements, such as artificial intelligence and machine learning, to improve their collections strategies. These advanced analytics platforms and technologies can be used to gauge customer preferences, as well as automate the collections process. When faced with higher volumes of delinquent loans, some organizations rapidly hire inexperienced staff. With new analytical advancements, organizations can reduce overhead and maintain compliance through the collections process. Additionally, advanced analytics and technology can help manage customers throughout the customer life cycle. Let’s explore further: Why use advanced analytics in collections? Collections strategies demand diverse approaches, which is where analytics-based strategies and collections models come into play. As each customer and situation differs, machine learning techniques and constraint-based optimization can open doors for your organization. By rethinking collections outreach beyond static classifications (such as the stage of account delinquency) and instead prioritizing accounts most likely to respond to each collections treatment, you can create an improved collections experience. How does collections analytics empower your customers? Customer engagement, carefully considered, perhaps comprises the most critical aspect of a collections program—especially given historical perceptions of the collections process. Experian recently analyzed the impact of traditional collections methods and found that three percent of card portfolios closed their accounts after paying their balances in full. And 75 percent of those closures occurred shortly after the account became current. Under traditional methods, a bank may collect outstanding debt but will probably miss out on long-term customer loyalty and future revenue opportunities. Only effective technology, modeling and analytics can move us from a linear collections approach towards a more customer-focused treatment while controlling costs and meeting other business objectives. Advanced analytics and machine learning represent the most important advances in collections. Furthermore, powerful digital innovations such as better criteria for customer segmentation and more effective contact strategies can transform collections operations, while improving performance and raising customer service standards at a lower cost. Empowering consumers in a digital, safe and consumer-centric environment affects the complete collections agenda—beginning with prevention and management of bad debt and extending through internal and external account resolution. When should I get started? It’s never too early to assess and modernize technology within collections—as well as customer engagement strategies—to produce an efficient, innovative game plan. Smarter decisions lead to higher recovery rates, automation and self-service tools reduce costs and a more comprehensive customer view enhances relationships. An investment today can minimize the negative impacts of the delinquency challenges posed by a potential recession. Collections transformation has already begun, with organizations assembling data and developing algorithms to improve their existing collections processes. In advance of the next recession, two options present themselves: to scramble in a reactive manner or approach collections proactively. Which do you choose? Get started