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This is the second of a three part series of blog posts highlighting key focus areas for your response to the COVID-19 health crisis: Risk, Operations, Consumer Behavior, and Reporting and Compliance. For more information and the latest resources, please visit Look Ahead 2020, Experian’s COVID-19 resource center with the latest news and tools for our business partners as well as links to consumer resources and a risk simulator. To read the introductory post, click here.  Strategic Focus on Risk The last recession spurred an industry-wide systemic focus on stressed scenario forecasting. Now’s the time to evaluate the medium- to long-term impacts of the downturn response on portfolio risk measurement. The impact will be wide ranging, requiring recalibration of scorecards and underwriting processes and challenging assumptions related to fees, net interest income, losses, expenses and liquidity. There are critical inputs to understand portfolio monitoring and benchmarking by account types and segments.   Higher unemployment across the country is likely. You need a thorough response to successfully navigate the emerging risks. Expanding credit line management efforts for existing accounts is critical. Proactively responding to the needs of your customers will demand a wide range of data and analytics and more frequent and active processes to take action. Current approaches and tools with increased automation may need to be reevaluated. When sudden economic shocks occur, statistical models may still rank-order effectively, while the odds-to-score relationships deteriorate. This is the time to take full advantage of explainable machine learning techniques to quickly calibrate or rebuild scorecards with refreshed data (traditional and alternative) and continue the learning cycle.   As your risk management tools are evaluated and refreshed, there are many opportunities to target your servicing strategies where they can produce results. This may take the form of identifying segments exhibiting financial stress that can benefit from deferred payments, loan consolidation or refinancing. It might also involve more typical risk mitigation strategies, such as credit line reduction. There are several scenarios that may emerge over the next nine to 12 months that can offer opportunities to deepen relationships with your customers while managing long-term risk exposure. Optimizing Business Operations One of the most significant impacts to your business is the increase in transaction volumes as a result of the economic shock. We expect material increases in collections, refinancing and hardship programs. These increases are arriving at a time when many businesses have streamlined their teams in concert with periods of low delinquency and credit losses. Additional strain from call center shutdowns and limited staffing can easily overwhelm operations and cause business continuity plans to breakdown.   More than ever, the use of digital channels and self-servicing technology are no longer nice-to-haves. Customers expect online access, and efficiency demands automation, including virtual assistants. As more volume migrates to these channels, it’s critical to have the right customer experience and fraud risk controls deployed through flexible, cloud-based systems.   Learn More

This is the introduction to a series of blog posts highlighting key focus areas for your response to the COVID-19 health crisis: Risk, Operations, Consumer Behavior, and Reporting and Compliance. For more information and the latest resources, please visit Look Ahead 2020, Experian's COVID-19 resource center with the latest news and tools for our business partners as well as links to consumer resources and a risk simulator. Responding to COVID-19 The response to COVID-19 is rolling out across the global financial system and here in North America. Together, we’re adapting to working remotely and adjusting to our “new normal.” It seems the long forecasted economic recession is finally and abruptly on our doorstep. Recession planning has been a focus for many organizations, and it’s now time to act on these contingency plans and respond to the downturn. The immediate effects and those that quickly follow the pandemic will widely impact the economy, affecting businesses of all sizes, employment and consumer confidence. We learned from the housing crisis and Great Recession how to identify and adapt to emerging risks. We can apply those skills while rebuilding the economy and focusing on the consumer. How should you respond? What strategies should you deploy? How can you balance emerging risks, changing consumer expectations and regulatory impacts? First, let's draw upon the best knowledge we gained from the last recession and apply those learnings. Second, we need to understand the current environment including the impact of major changes in technology and consumer behavior over the last few years. This approach will allow us to identify key themes to help build-out strategies to focus resources, respond successfully and deliver for stakeholders.   Anticipate the pervasive and highly impactful market dynamics and trends The impact of this downturn on the consumer, on businesses and on financial institutions will be very different to that of the Great Recession. There will be a complete loss of income for many workers and small businesses. In a survey conducted by the Center for Financial Services Innovation (CFSI), more than 112 million Americans said that they don’t have enough savings to cover three months of living expenses*. These volatile market conditions and consumer insecurity will cause changes to your business models. You must prepare to manage increased fraud attacks, continue to push toward digital banking and understand regulatory changes.   Learn More   *U.S. Financial Health Pulse, 2018 Baseline Survey Results. https://s3.amazonaws.com/cfsi-innovation-files-2018/ wp-content/uploads/2018/11/20213012/Pulse-2018- Baseline-Survey-Results-11-16.18.pdf

While many companies are interested in implementing technology with advanced analytic capabilities, the concepts behind the technology can often be hard to understand. Demystifying the terminology around artificial intelligence and machine learning is one of the first steps for successful implementation. Discover what they mean for your financial institution in our new infographic: Learn more

Security. Convenience. Personalization. Finding the balance between these three priorities is key to creating a safe and low-friction customer experience. We surveyed more than 6,500 consumers and 650 businesses worldwide about these priorities for our 2020 Global Identity and Fraud Report: Most business are focusing on personalization, specifically in relation to upselling and cross-selling. This is frustrating customers who are looking for increases in both security and convenience. It’s possible to have all three. Read Full Report

Update: After closely monitoring updates from the WHO, CDC, and other relevant sources related to COVID-19, we have decided to cancel our 2020 Vision Conference. If you had the chance to experience tomorrow, today, would you take it? What if it meant you could get a glimpse into the future technology and trends that would take your organization to the next level? If you’re looking for a competitive edge – this is it. For more than 38 years, Experian’s premier conference has connected business leaders to data-driven ideas and solutions, fueling them to target new markets, grow existing customer bases, improve response rates, reduce fraud and increase profits. What’s in it for you? Everything to gain and nothing to lose. Are you a marketer? These sessions were made to drive your conversion rates to new heights: Know your customers via omnichannel marketing: Your customers are everywhere, but can you reach them? Learn how to drive business-expansion strategy, brand affinity and customer engagement across multiple channels. Plus, gain insight into connecting with customers via one-to-one messaging. By invitation only, the future of ITA marketing: An evolving landscape means marketers face new challenges in effectively targeting consumers while staying compliant. In this session, we’ll explore how you can leverage fair lending-friendly marketing data for targeting, analysis and measurement. Want the latest in technology trends? Dive into discussions to transform your customer experience: Credit in the age of technology transformation: Machine learning and artificial intelligence are the current darlings of big data, but the platform that drives the success of any big data endeavor is crucial. This session will dive into what happens behind the curtain. Put away your plastic – next-generation identity: An industry panel of experts discusses the newest digital identity and authentication capabilities – those in use today and also exciting solutions on the horizon. How about for the self-proclaimed data geeks? Analyze these: Alternative data: Listen in on an in-depth conversation about creative and impactful examples of using emerging data assets, such as alternative and consumer-permissioned data, for improved consumer inclusion, risk assessment and verification services. The next wave in open data: Experian will share their views on the potential of advanced data and models and how they benefit the global value chain – from consumer scores to business opportunities – regardless of local regulations. And the risk masters? Join us as we kick fraud to the curb: Understanding and tackling synthetic ID fraud: Synthetic IDs present a serious challenge for our entire industry. This expert panel will explore the current landscape – what’s working and what’s not, the expected impact of the next generation SSA eCBSV service, and best practice prevention methods. You are your ID – the new reality of biometrics: Consumers are becoming increasingly comfortable with biometrics. Just as CLEAR has transformed how we use our biometric identity to move through airports, sports venues and more, financial transactions can also be made friction-free. The point is, there’s something for everyone at Vision 2020. It’s not just another conference. Trade in stuffy tradeshow halls and another tri-fold brochure for the insights and connections you need to take your career and organization to the next level. Like technology itself, Vision 2020 promises to connect us, unify us and enable us all to create a better tomorrow. Join us for unique networking opportunities, one-on-one conversations with subject-matter experts and more than 50 breakout sessions with the industry’s most sought-after thought leaders.    

Machine learning, once a mysterious and unknown field, has come a long way throughout the years. Now, it's being implemented across a variety of industries - and expertise in all things related to machine learning is in high demand. Take a journey through the history of machine learning in our new infographic: Read the e-book

If you’ve been on the dating scene in the last few years, you’re probably familiar with ghosting. For those of you who aren’t, I’ll save you the trip to Urban Dictionary. “Ghosting” is when the person you’re dating disappears. No calls. No texts. No DMs. They just vanish, never to be heard from again. As troublesome as this can be, there’s a much more nefarious type of ghosting to be wary of – credit ghosting. Wait, what’s credit ghosting? Credit ghosting refers to the theft of a deceased person’s identity. According to the IRS, 2.5 million deceased identities are stolen each year. The theft often occurs shortly after someone dies, before the death is widely reported to the necessary agencies and businesses. This is because it can take months after a person dies before the Social Security Administration (SSA) and IRS receive, share, or register death records. Additionally, credit ghosting thefts can go unnoticed for months or even years if the family of the deceased does not check their credit report for activity after death. Opportunistic fraudsters check obituaries and other publicly available death records for information on the deceased. Obituaries often include a person’s birthday, address or hometown, parents’ names, occupation, and other information regularly used in identity verification. With this information fraudsters can use the deceased person’s identity and take advantage of their credit rating rather than taking the time to build it up as they would have to with other types of fraud. Criminals will apply for credit cards, loans, lines of credit, or even sign up for a cell phone plan and rack up charges before disappearing. Where did this type of identity theft come from? Credit ghosting is the result of a few issues. One traces back to a discrepancy noted by the Social Security’s inspector general. In an audit, they found that 6.5 million Social Security numbers for people born before June 16, 1901, did not have a date of death on record in the administration’s Numident (numerical identification) system – an electronic database containing Social Security number records assigned to each citizen since 1936. Without a date of death properly noted in the database, government agencies and other entities inquiring won’t necessarily know an individual is deceased, making it possible for criminals to implement credit ghosting schemes. Additionally, unreported deaths leave further holes in the system, leading to opportunity for fraudsters. When financial institutions run checks on the identity information supplied by a fraudster, it can seem legitimate. If the deceased’s credit is in good standing, the fraudster now appears to be a good customer—much like a synthetic identity—but now with the added twist that all of the information is from the same person instead of stitched together from multiple sources. It can take months before the financial institution discovers that the account has been compromised, giving fraudsters ample time to bust out and make off with the funds they’ve stolen. How can you defend against credit ghosting? Luckily, unlike your dating pipeline, there are ways to guard against ghosting in your business’ pipeline. Frontline Defense: Start by educating your customers. It’s never pleasant to consider your own passing or that of a loved one, but it’s imperative to have a plan in place for both the short and long term. Remind your customers that they should contact lenders and other financial institutions in the event of a death and continue monitoring those accounts into the future. Relatives of the deceased don’t tend to check credit reports after an estate has been settled. If the proper steps aren’t taken by the family to notify the appropriate creditors of the death, the deceased flag may not be added to their credit report before the estate is closed, leaving the deceased’s information vulnerable to fraud. By offering your customers assistance and steps to take, you can help ensure that they’re not dealing with the fallout of credit ghosting—like dealing with calls from creditors following up after the fraudster’s bust-out—on top of grieving. Backend Defense: Ensure you have the correct tools in place to spot credit ghosts when they try to enter your pipeline. Experian’s Fraud Shield includes high risk indicators and provides a deceased indicator flag so you can easily weed them out. Additionally, you can track other risk indicators like previous uses of a particular Social Security number and identify potential credit-boosting schemes. Speak to an Experian associate today about how you can increase your defenses against credit ghosting. Let's talk

Sometimes, the best offense is a good defense. That’s certainly true when it comes to detecting synthetic identities, which by their very nature become harder to find the longer they’ve been around. To launch an offense against synthetic identity fraud, you need to defend yourself from it at the top of your new customer funnel. Once fraudsters embed their fake identity into your portfolio, they become nearly impossible to detect. The Challenge Synthetic identity fraud is the fastest-growing type of financial crime in the United States. The cost to businesses is hard to determine because it’s not always caught or reported, but the amounts are staggering. According to the Aite Group, it was estimated to total at least $820 million in 2017 and grow to $1.2 billion by 2020. This type of theft begins when individual thieves and large-scale crime rings use a combination of compromised personal information—like unused social security numbers—and fabricated data to stitch together increasingly sophisticated personas. These well-crafted synthetic identities are hard to differentiate from the real deal. They often pass Know Your Customer, Customer Identification Program and other onboarding checks both in person and online. This puts the burden on you to develop new defense strategies or pay the price. Additionally, increasing pressure to grow deposits and expand loan portfolios may coincide with the relaxation of new customer criteria, allowing even more fraudsters to slip through the cracks. Because fraudsters nurture their fake identities by making payments on time and don’t exhibit other risk factors as their credit limits increase, detecting synthetic identities becomes nearly impossible, as does defending against them. How This Impacts Your Bottom Line Synthetic identity theft is sometimes viewed as a victimless crime, since no single individual has their entire identity compromised. But it’s not victimless. When undetected fraudsters finally max out their credit lines before vanishing, the financial institution is usually stuck footing the bill. These same fraudsters know that many financial institutions will automatically settle fraud claims below a specific threshold. They capitalize on this by disputing transactions just below it, keeping the goods or services they purchased without paying. Fraudsters can double-dip on a single identity bust-out by claiming identity theft to have charges removed or by using fake checks to pay off balances before maxing out the credit again and defaulting. The cost of not detecting synthetic identities doesn’t stop at the initial loss. It flows outward like ripples, including: Damage to your reputation as a trusted organization Fines for noncompliance with Know Your Customer Account opening and maintenance costs that are not recouped as they would be with a legitimate customer Mistakenly classifying fraudsters as bad debt write offs Monetary loss from fraudsters’ unpaid balances Rising collections costs as you try to track down people who don’t exist Less advantageous rates for customers in the future as your margins grow thinner These losses add up, continuing to impact your bottom line over and over again. Defensive Strategies So what can you do? Tools like eCBSV that will assist with detecting synthetic identities are coming but they’re not here yet. And once they’re in place, they won’t be an instant fix. Implementing an overly cautious fraud detection strategy on your own will cause a high number of false positives, meaning you miss out on revenue from genuine customers. Your best defense requires finding a partner to help you implement a multi-layered fraud detection strategy throughout the customer lifecycle. Detecting synthetic identities entails looking at more than a single factor (like length of credit history). You need to aggregate multiple data sets and connect multiple customer characteristics to effectively defend against synthetic identity fraud. Experian’s synthetic identity prevention tools include Synthetic Identity High Risk Score to incorporate the history and past relationships between individuals to detect anomalies. Additionally, our digital device intelligence tools perform link analyses to connect identities that seem otherwise separate. We help our partners pinpoint false identities not associated with an actual person and decrease charge offs, protecting your bottom line and helping you let good customers in while keeping false personas out. Find out how to get your synthetic identity defense in place today.

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.

As the holiday shopping season kicks off, it’s prime time for fraudsters to prey on consumers who are racking up rewards points as they spend. Find out how fraud trends in loyalty and rewards programs can impact your business: Are you ready to prevent fraud this holiday season? Get started today

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’s Halloween time – time for trick or treating, costume parties and monsters lurking in the background. But this year, the monsters aren’t just in the background. They’re in your portfolio.  This year, “Frankenstein” has another meaning. Much more ominous than the neighbor kid in the costume.   “Frankenstein IDs” refer to synthetic identities — a type of fraud carried out by criminals that have created fictitious identities. Just as Dr. Frankenstein’s monster was stitched together from parts, synthetic IDs are stitched together pieces of mismatched identities — some fake, some real, some even deceased.   It typically takes fraudsters 12 to 18 months to create and nurture a synthetic identity before it’s ready to "bust out" – the act of building a credit history with the intent of maxing out all available credit and eventually disappearing. That means fraudsters are investing money and time to build numerous tradelines, ensure these "fake" identities are in good credit standing, and ultimately steal the largest amount of money possible.   “Wait Master, it might be dangerous . . . you go, first.” — Igor   Synthetic identities are a notable challenge for many financial institutions and retail organizations. According to the recently released Federal Reserve Board White Paper, synthetic identity fraud accounts for roughly 20% of all credit losses, and cost U.S. businesses roughly $6 billion in 2016 with an estimated 41% growth over 2 years. 85-95% of applicants identified as potential synthetic are not even flagged by traditional fraud models.   The Social Security Administration recently announced plans for the electronic Consent Based Social Security Number Verification service – pilot program scheduled for June 2020. This service is designed to bring efficiency to the process for verifying Social Security numbers directly with the government agency. Once available, this verification could be an important tool in the fight against the elusive “Frankenstein” identity monster.   But with the Social Security Administration's pilot program not scheduled for launch until the middle of next year, how can financial institutions and other organizations bridge the gap and adequately prepare for a potential uptick in synthetic identity fraud attacks? It comes down to a multilayered approach that relies on advanced data, analytics, and technology — and focuses on identity.   Any significant progress in making synthetic identities easier to detect could cost fraudsters significant time and money.   Far too many financial institutions and other organizations depend solely on basic demographic information and snapshots in time to confirm the legitimacy of an identity. These organizations need to think beyond those capabilities. The real value of data in many cases lies between the data points. We have seen this with synthetic identity — where a seemingly legitimate identity only shows risk when we can analyze its connections and relationships to other individuals and characteristics.   In addition to our High Risk Fraud Score, we now have a Synthetic Fraud Risk Level Indicator available on credit profiles. These advanced detection capabilities are delivered via the simplicity of a straightforward indicator returned on the credit profile which lenders can use to trigger additional identity verification processes.   While there are programs and initiatives in the works to help financial institutions and other organizations combat synthetic identity fraud, it's important to keep in mind there's no silver bullet, or stake to the heart, to completely keep these Frankenstein IDs out.   Oh, and don’t forget… “It’s pronounced ‘Fronkensteen.’ ” — Dr. Frankenstein

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

Experian is excited to have been chosen as one of the first data and analytics companies that will enable access to Social Security Administration (SSA) data for the purposes of verifying identity against the Federal Agency’s records. The agency’s involvement in the wake of Congressional interest and successful legislation will create a seismic shift in the landscape of identity verification. Ultimately, the ability to leverage SSA data will reduce the impact of identity fraud and synthetic identity and put real dollars back into the pockets of people and businesses that absorb the costs of fraud today. As this era of government and private sector collaboration begins, many of our clients and partners are breathing a sigh of relief. We see this in a common question our customers ask every day, “Do I still need an analytical solution for synthetic ID now that eCBSV is on the horizon?” The common assumption is that help is on the way and this long tempest of rising losses and identity uncertainty is about to leave us. Or is it? We don’t believe it’s the end of the synthetic ID storm. This is the eye. Rather than basking in the calm light of this moment, we should be thinking ahead and assessing our vulnerabilities because the second half of this storm will be worse than the first. Consider this: The people who develop and exploit synthetic IDs are playing a long game. It takes time, research, planning and careful execution to create an identity that facilitates fraud. The bigger the investment, the bigger the spoils will be. Synthetic ID are being used to purchase luxury automobiles. They’re passing lender marketing criteria and being offered credit. The criminals have made their investment, and it’s unlikely they will walk away from it. So, what does SSA’s pending involvement mean to them? How will they prepare? These aren’t hard questions. They’ll do what you would do in the eye of a storm — maximize the value of the preparations that are in place. Gather what you can quickly and brace yourself for the uncertainty that’s coming. In short, there’s a rush to monetize synthetic IDs on the horizon, and this is no time to declare ourselves safe. It’s doubtful that the eCBSV process will be the silver bullet that ends synthetic ID fraud — and certainly not on day one. It’s more likely that the physical demands of the data exchange, volume constraints, response times and the actionability of the results will take time to optimize. In the meantime, the criminals aren’t going to sit by and watch as their schemes unravel and lose value. We should take some comfort that we’ve made it through the first half of the storm, but recognize and prepare for what still needs to be faced.