Ecommerce / Retail

To combat the growing threat of synthetic identity fraud, Experian recently announced the launch of Sure ProfileTM, a revolutionary change to the credit profile that gives lenders peace of mind with Experian’s commitment to share in losses that result from an identity we’ve assured.   “Experian has always been a leader in combatting fraud, and with Sure Profile, we’re proud to deliver an industry-first fraud offering integrated into the credit profile that mitigates lender losses while protecting millions of consumers’ identities,” said Robert Boxberger, President of Decision Analytics, Experian North America.   Synthetic identity fraud is expected to drive $48 billion in annual online payment fraud losses by 2023. Between opportunistic fraudsters and a lack of a unified definition for synthetic identity theft it can be nearly impossible to detect—and therefore prevent—this type of fraud.   This breakthrough solution provides a composite history of a consumer’s identification, public record, and credit information and determines the risk of synthetic fraud associated with that consumer. It’s not just a fraud tool, it’s a comprehensive credit profile that utilizes premium data so lenders can make positive credit decisions.   Sure Profile leverages the capabilities of the Experian Ascend Identity PlatformTM and uses Experian’s industry-leading data assets and data quality to drive advanced analytics that set a higher level of protection for lenders. It’s powered by newly-developed machine learning and AI models. And it offers a streamlined approach to define and detect synthetic identities early in the originations process.   Most importantly, Sure Profile differentiates between real people and potentially risky applicants so lenders can increase application approvals with greater assurance and less risk.   “Experian can confidently define and help detect synthetic fraud. That's why we can help stop it,” said Craig Boundy, CEO of Experian North America. “Experian stands behind our data with assurance given to our clients. It’s better for lenders and it’s better for consumers.”   Sure Profile is a complement to our robust set of identity protection and fraud management capabilities, which are designed to address fraud and identity challenges including account openings, account takeovers, e-commerce fraud and more. This first-of-its kind profile is the future of underwriting and portfolio protection and it’s here now. Read press release Learn More About Sure Profile

The economic impact of the COVID-19 health crisis is ever-evolving and requires great flexibility and planning from lenders. Shannon Lois, Experian’s Senior Vice President, Analytics, Consulting and Operations, discusses what lenders can expect and next steps to take. Q: Though COVID-19 is catalyzing a sharp economic slowdown, many experts expect it to be temporary and liken it more to a global natural disaster than the prior financial crisis. What are your reactions? SL: There is still debate as to whether we will have a U-shaped or a V-shaped recession and its probable severity and longevity. Regardless, we are in a recession caused by a health pandemic with uncertainty of what it will mean for our global economy and without a clear view as to when it will end. The sooner we can contain the virus the more it will help to curtail the size of the recession. The unemployment rates and the consumer lack of confidence in the future will continue to contract spending which in turn will continue to propagate the recession. Our ability to limit COVID-19 over the coming months will have a direct impact in the economy, although the effects will probably linger on for six or more months. Q: From an economic perspective, what are the current trends we’re seeing? SL: Unemployment has skyrocketed and every business sector has been impacted although with   different degrees of severity. In particular, tourism/hospitality, airlines, automotive, consumer products and retail have suffered. Consumers’ financial status varies and will continue to fluctuate, and credit conditions tighten while welfare payments increase. The government programs that have started will help, but they’re not enough to counter a prolonged recession. As some states seek to reopen and others extend their shelter in place orders, we will continue to see economic changes, with different sectors bouncing back or dipping further depending on their geographic location. Q: How does the economic slowdown compare to what we may have expected previously? SL: This recession is different than anything we have encountered previously not only because of the health concerns and implication of our population but because of the uncertainty of it all. As an example, social distancing has significantly and immediately impacted consumer demand but overall it is their low confidence in the future that will cause a continuous drop in discretionary and non-discretionary spending. Not only do we have challenges on the demand side, we also are seeing the same on the supply side with no automotive manufacturing occurring in the USA, and international oil flooding the market causing negative impact on domestic oil and the broad energy market. Q: How do the unemployment and liquidity challenges come into play? SL: The unemployment rate has already jumped to a record high. Most consumers are facing liquidity and affordability challenges and businesses do not have enough cash reserves to sustain them. Consumer activity has shifted drastically across all channels while lenders are exercising more caution. If this is a V-shaped recession (and hopefully it will be), then most activity is bound to spring back quickly in Q3. With companies safeguarding some jobs and the help of governments’ supplemental programs, businesses will restore supply and consumer demand will get a kick start. Q: What is the smartest next play for financial institutions? SL: The path forward requires several steps. First, understand your customers, existing and new. Refine your policies with the right information around your customers’ financial situations and extend programs (forbearance and loan payment forgiveness) as needed under the right guidelines. It’s also important to use refreshed data to lend to consumers and businesses who need it now more than ever, with the proper policies and fraud checks in place. Finally, increase your agility to operate effectively and dynamically with automation, interactive communication and self-serving digital tools. Experian is committed to helping lenders throughout these uncertain times. For more resources, visit our Look Ahead 2020 Resource Hub. Learn more   About Our Expert Shannon Lois, Senior Vice President, Analytics, Consulting and Operations, Decision Analytics Shannon and her team of analysts, scientists, credit, fraud and marketing risk management experts provide results-driven consulting services and state-of-the-art advanced analytics, science and data products to clients in a wide range of businesses, including banking, auto, credit, utility, marketing and finance. Prior to her current role, she founded the Advisory Services practice at Experian, driving to actionable and proven solutions for our clients’ most pressing business problems.    

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

One of the most difficult parts of combating fraud is the ability to distinguish between the variety of fraud types. To properly manage your fraud efforts, you need to be able to differentiate between first party fraud and third party fraud so you can determine the best treatment. After all, if you’re treating first party fraud as though it’s third party fraud, the customer you’re contacting for verification will give whatever information they need to in order to continue their criminal actions. So how do you verify each type of fraud without adding additional overhead or increasing the friction experienced by your customers? Combating Fraud During an Economic Downturn Particularly in times of economic uncertainty, the ability to detect and identify individual fraud types allows you to work to prevent them in the future. Through proper identification, you can also apply the correct treatments to maximize the effectiveness of your fraud response teams, since the treatment for first and third party fraud is different. During the economic upswing, first party fraud was a secondary concern. Businesses were easing friction to help continue growth. Now, the same customers that businesses thought would drive growth are hurting and unable to help offset the losses caused by bad actors. Now is the time to revisit existing fraud prevention and mitigation strategies to ensure that fraud is properly identified, and the correct treatments are applied. Introducing Precise ID® Model Suite Experian’s Precise ID Model Suite combines identity analytics with advanced fraud risk models to: Protect the entire customer journey again fraud – across account opening, login, maintenance and transactions Distinguish first-party, third-party, and synthetic identity fraud to determine the best next action Enable agility during changing market conditions Maintain regulatory compliance (including: KYC, CIP, GLBA, FCRA, FFIEC, PATRIOT Act, FACTA, and more) Improve overall fraud management strategies and reduce losses Precise ID Model Suite allows you to detect and distinguish types of fraud with a single call – enabling your business to maximize efficiency and eliminate redundancy across your fraud prevention teams. By accurately recognizing risk, and in particular, recognizing that first party fraud is in fact a type of fraud distinct from credit risk, you’re able to protect your portfolio and your customers. Learn more

This is the next article in our series about how to handle the economic downturn – this time focusing on how to prevent fraud in the new economic environment. We tapped two new experts—Chris Ryan, Market Lead, Fraud and Identity and Tischa Agnessi, Go-to-Market Lead, Decisioning Software—to share their thoughts on how to keep fraud out of your portfolio while continuing to lend. Q: What new fraud trends do you expect during the economic downturn? CR: Perhaps unsurprisingly, we tend to see high volumes of fraud during economic downturn periods. First, we anticipate an uptick in third-party fraud, specifically account takeover or ATO. It’ll be driven by the need for first-time users to be forced online. In particular, the less tech-savvy crowd is vulnerable to phishing attacks, social engineering schemes, using out-of-date software, or landing on a spoofed page. Resources to investigate these types of fraud are already strained as more and more requests come through the top of the funnel to approve new accounts. In fact, according to Javelin Strategy & Research’s 2020 Identity Fraud Study, account takeover fraud and scams will increase at a time when consumers are feeling financial stress from the global health and economic crisis. It is too early to predict how much higher the fraud rates will go; however, criminals become more active during times of economic hardships. We also expect that first party fraud (including synthetic identity fraud) will trend upwards as a result of the deliberate abuse of credit extensions and additional financing options offered by financial services companies. Forced to rely on credit for everyday expenses, some legitimate borrowers may take out loans without any intention of repaying them – which will impact businesses’ bottom lines. Additionally, some individuals may opportunistically look to escape personal credit issues that arise during an economic downturn. The line between behaviors of stressed consumers and fraudsters will blur, making it more difficult to tell who is a criminal and who is an otherwise good consumer that is dealing with financial pressure. Businesses should anticipate an increase in synthetic identity fraud from opportunistic fraudsters looking to take advantage initial financing offers and the cushions offered to consumers as part of the stimulus package. These criminals will use the economic upset as a way to disguise the fact that they’re building up funds before busting out. Q: With payment stress on the rise for consumers, how can lenders manage credit risk and prevent fraud? TA: Businesses wrestle daily with problems created by the coronavirus pandemic and are proactively reaching out to consumers and other businesses with fresh ideas on initial credit relief, and federal credit aid. These efforts are just a start – now is the time to put your recession readiness plan and digital transformation strategies into place and find solutions that will help your organization and your customers beyond immediate needs. The faceless consumer is no longer a fraction of the volume of how organizations interact with their customers, it is now part of the new normal. Businesses need to seek out top-of-line fraud and identity solutions help protect themselves as they are forced to manage higher digital traffic volumes and address the tough questions around: How to identify and authenticate faceless consumers and their devices How to best prevent an overwhelming number of fraud tactics, including first party fraud, account takeover, synthetic identity, bust out, and more. As time passes and the economic crisis evolves, we will all adapt to yet another new normal. Organizations should be data-driven in their approach to this rapidly changing credit crisis and leverage modern technology to identify financially stressed consumers with early-warning indicators, predict future customer behavior, and respond quickly to change as they deliver the best treatment at the right time based on customer-specific activities. Whether it’s preparing portfolio risk assessment, reviewing debt management, collections, and recovery processes, or ramping up your fraud and identity verification services, Experian can help your organization prepare for another new normal. Experian is continuing to monitor 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 differentiate legitimate consumers from fraudsters and protect their business and customers. Learn more About Our Experts [avatar user="ChrisRyan" /] Chris Ryan, Market Lead, Fraud and Identity Chris has over 20 years of experience in fraud prevention and uses this knowledge to identify the most critical fraud issues facing individuals and businesses in North America, and he guides Experian’s application of technology to mitigate fraud risk. [avatar user="tischa.agnessi" /] Tischa Agnessi, Go-to-Market Lead, Decisioning Software Tischa joined Experian in June of 2018 and is responsible for the go to market strategy for North America’s decisioning software solutions. Her responsibilities include delivering compelling propositions that are unique and aligned to markets, market problems, and buyer and user personas. She is also responsible for use cases that span the PowerCurve® software suite as well as application platforms, such as Decisioning as a ServiceSM and Experian®One.

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.

In the face of severe financial stress, such as that brought about by an economic downturn, lenders seeking to reduce their credit risk exposure often resort to tactics executed at the portfolio level, such as raising credit score cut-offs for new loans or reducing credit limits on existing accounts. What if lenders could tune their portfolio throughout economic cycles so they don’t have to rely on abrupt measures when faced with current or future economic disruptions? Now they can. The impact of economic downturns on financial institutions Historically, economic hardships have directly impacted loan performance due to differences in demand, supply or a combination of both. For example, let’s explore the Great Recession of 2008, which challenged financial institutions with credit losses, declines in the value of investments and reductions in new business revenues. Over the short term, the financial crisis of 2008 affected the lending market by causing financial institutions to lose money on mortgage defaults and credit to consumers and businesses to dry up. For the much longer term, loan growth at commercial banks decreased substantially and remained negative for almost four years after the financial crisis. Additionally, lending from banks to small businesses decreased by 18 percent between 2008-2011. And – it was no walk in the park for consumers. Already faced with a rise in unemployment and a decline in stock values, they suddenly found it harder to qualify for an extension of credit, as lenders tightened their standards for both businesses and consumers. Are you prepared to navigate and successfully respond to the current environment? Those who prove adaptable to harsh economic conditions will be the ones most poised to lead when the economy picks up again. Introducing the FICO® Resilience Index The FICO® Resilience Index provides an additional way to evaluate the quality of portfolios at any point in an economic cycle. This allows financial institutions to discover and manage potential latent risk within groups of consumers bearing similar FICO® Scores, without cutting off access to credit for resilient consumers. By incorporating the FICO® Resilience Index into your lending strategies, you can gain deeper insight into consumer sensitivity for more precise credit decisioning. What are the benefits? The FICO® Resilience Index is designed to assess consumers with respect to their resilience or sensitivity to an economic downturn and provides insight into which consumers are more likely to default during periods of economic stress. It can be used by lenders as another input in credit decisions and account strategies across the credit lifecycle and can be delivered with a credit file, along with the FICO® Score. No matter what factors lead to an economic correction, downturns can result in unexpected stressors, affecting consumers’ ability or willingness to repay. The FICO® Resilience Index can easily be added to your current FICO® Score processes to become a key part of your resilience-building strategies. Learn more

For the last several years, as the global economy flourished, the opportunities created by removing friction and driving growth guided business strategies governing identity and fraud. The amount of profitable business available in a low-friction environment simply outweighed the fraud that could be mitigated with more stringent verification methods. Now that we’re facing a global crisis, it’s time to reconsider the approach that drove the economic boom that defined that last decade. Recognizing how economic changes impact fraud At the highest level, we separate fraud into two types; third party fraud and first party fraud. In simple terms, third party fraud involves the misuse of a real customer’s identity or unauthorized access to a real customer’s accounts or assets. First party fraud involves the use of an identity that the fraudster controls—whether it’s their own identity, a manipulated version of their own identity, or a synthetic identity that they have created. The important difference in this case is that the methods of finding and stopping third party fraud remain constant even in the event of an economic downturn – establish contact with the owner of the identity and verify whether the events are legitimate. Fraud tactics will evolve, and volumes increase as perpetrators also face pressure to generate income, but at the end of the day, a real person is being impersonated, and a victim exists that will confirm when fraud is taking place. Changes in first party fraud during an economic downturn are dramatically different and much more problematic. The baseline level of first party fraud using synthetic, manipulated and the perpetrator’s own identity continue, but they are augmented by real people facing desperate circumstances and existing “good” customers who over-extend while awaiting a turn-around. The problem is that there is no “victim” to confirm fraud is occurring, and the line between fraud (which implies intent) and credit default (which does not) becomes very difficult to navigate. With limited resources and pressures of their own, at some point lenders must try to distinguish deliberate theft from good customers facing bad circumstances and manage cases accordingly. The new strategy When times are good, it’s easier to build up a solid book of business with good customers. Employment rates are high, incomes are stable, and the risks are manageable. Now, we’re experiencing rapidly changing conditions, entire industries are disrupted, unemployment claims have skyrocketed and customers will need assistance and support from their lenders to help them weather the storm. This is a reciprocal relationship – it behooves those same lenders to help their customers get through to the other side. Lenders will look to limit losses and strengthen relationships. At the same time, they’ll need to reassess their existing fraud and identity strategies (among others) as every interaction with a customer takes on new meaning. Unexpected losses We’ve all been bracing for a recession for a while. But no one expected it to show up quite like it did. Consumers who have been model customers are suddenly faced with a complete shift in their daily life. A job that seemed secure may be less so, investments are less lucrative in the short term, and small business owners are feeling the pressure of a change in day-to-day commerce. All of this can lead to unexpected losses from formerly low-risk customers. As this occurs, it becomes more critical than ever to identify and help good customers facing grim circumstances and find different ways to handle those that have malicious intent. Shifting priorities When the economy was strong, many businesses were able to accept higher losses because those losses were offset by immense growth. Unfortunately, the current crisis means that some of those policies could have unforeseen consequences. For instance – the loss of the ability to differentiate between a good customer who has fallen on hard times and someone who’s been a bad actor from the start. Additionally, businesses need to revise their risk management strategies to align with shifting customer needs. The demand for emergency loans and will likely rise, while loans for new purchases like cars and homes will fall as consumers look to keep their finances secure. As the need to assist customers in distress rises and internal resources are stressed, it’s critical that companies have the right tools in place to triage and help customers who are truly in need. The good news The tools businesses like yours need to screen first party fraud already exist. In fact, you may already have the necessary framework in place thanks to an existing partnership, and a relatively simple process could prepare your business to properly screen both new and existing customers at every touchpoint. This global crisis is nowhere near over, but with the right tools, your business can protect itself and your customers from increased fraud risks and losses of all sorts – first party, stolen identities, or synthetic identities, and come out on the other side even stronger. Contact Experian for a review of your current fraud strategy to help ensure you’re prepared to face upcoming challenges. Contact us

Originally posted by Experian Global News blog At Experian, we have an unwavering commitment to helping consumers and clients manage through this unprecedented period. We are actively working with consumers, lenders, lawmakers and regulators to help mitigate the potential impact on credit scores during times of financial hardship. In response to the urgent and rapid changes associated with COVID-19, we are accelerating and enhancing our financial education programming to help consumers maintain good credit and gain access to the financial services they need. This is in addition to processes and tools the industry has in place to help lenders accommodate situations where consumers are affected by circumstances beyond their control. These processes will be extended to those experiencing financial hardship as a result of COVID-19. As the Consumer’s Credit Bureau, our commitment at Experian is to inform, guide and protect our consumers and customers during uncertain times. With expected delays in bill payments, unprecedented layoffs, hiring freezes and related hardships, we are here to help consumers in understanding how the credit reporting system and personal finance overall will move forward in this landscape. One way we’re doing this is inviting everyone to join our special eight-week series of #CreditChat conversations surrounding COVID-19 on Wednesdays at 3 p.m. ET on Twitter. Our weekly #CreditChat program started in 2012 to help the community learn about credit and important personal finance topics (e.g. saving money, paying down debt, improving credit scores). The next several #CreditChats will be dedicated to discussing ways to manage finances and credit during the pandemic. Topics of these #CreditChats will include methods and strategies for bill repayment, paying down debt, emergency financial assistance and preparing for retirement during COVID-19. “As the consumer’s credit bureau, we are committed to working with consumers, lenders and the financial community during and following the impacts of COVID-19,” says Craig Boundy, Chief Executive Officer of Experian North America. “As part of our nation’s new reality, we are planning for options to help mitigate the potential impact on credit scores due to financial hardships seen nationwide. Our #CreditChat series and supporting resources serve as one of several informational touchpoints with consumers moving forward.” Being fully committed to helping consumers and lenders during this unprecedented period, we’ve created a dedicated blog page, “COVID-19 and Your Credit Report,” with ongoing and updated information on how COVID-19 may impact consumers’ creditworthiness and – ultimately – what people should do to preserve it. The blog will be updated with relevant news as we announce new solutions and tactics. Additionally, our “Ask Experian” blog invites consumers to explore immediate and evolving resources on our COVID-19 Updates page. In addition to this guidance, and with consumer confidence in the economy expected to decline, we will be listening closely to the expert voices in our Consumer Council, a group of leaders from organizations committed to helping consumers on their financial journey. We established a Consumer Council in 2009 to strengthen our relationships and to initiate a dialogue among Experian and consumer advocacy groups, industry experts, academics and other key stakeholders. This is in addition to ongoing collaboration with our regulators. Additionally, our Experian Education Ambassador program enables hundreds of employee volunteers to serve as ambassadors sharing helpful information with consumers, community groups and others. The goal is to help the communities we serve across North America, providing the knowledge consumers need to better manage their credit, protect themselves from fraud and identity theft and lead more successful, financially healthy lives. COVID-19 has impacted all industries and individuals from all walks of life. We want our community to know we are right there with you. Learn more about our weekly #CreditChat and upcoming schedule here. 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

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

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

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.

What do movie actors Adam Sandler and Hugh Grant, jazz singer Michael Bublé, Russian literary giant Leo Tolstoy, and Colonel Sanders, the founder of KFC, have in common? Hint, it’s not a Nobel Prize for Literature, a Golden Globe, a Grammy Award, a trademark goatee, or a “finger-lickin’ good” bucket of chicken. Instead, they were all born on September 9, the most common birth date in the U.S. Baby Boom According to real birth data compiled from 20 years of American births, September is the most popular month to give birth to a child in America – and December, the most popular time to make one. With nine of the top 10 days to give birth falling between September 9 and September 20, one may wonder why the birth month is so common. Here are some theories: Those who get to choose their child’s birthday due to induced and elective births tend to stay away from the hospital during understaffed holiday periods and may plan their birth date around the start of the school year. Several of the most common birth dates in September correspond with average conception periods around the holidays, where couples likely have more time to spend together. Some studies within the scientific community suggest that our bodies may actually be biologically disposed to winter conceptions. While you may not be feeling that special if you were born in September, the actual differences in birth numbers between common and less common birthdays are often within just a few thousand babies. For example, September 10, the fifth most common birthday of the year, has an average birth rate of 12,143 babies. Meanwhile, April 20, the 328th most common birthday, has an average birth rate of 10,714 newborns. Surprisingly, the least common birthdays fall on Christmas Eve, Christmas Day and New Year’s Day, with Thanksgiving and Independence Day also ranking low on the list. Time to Celebrate – but Watch out! Statistically, there’s a pretty good chance that someone reading this article will soon be celebrating their birthday. And while you should be getting ready to party, you should also be on the lookout for fraudsters attempting to ruin your big day. It’s a well-known fact that cybercriminals can use your birth date as a piece of the puzzle to capture your identity and commit identity theft – which becomes a lot easier when it’s being advertised all over social media. It’s also important for employers to safeguard their organization from fraudsters who may use this information to break into corporate accounts. While sharing your birthday with a lot of people could be a good or bad thing depending on how much undivided attention you enjoy – you’re in great company! Not only can you plan a joint party with Michelle Williams, Afrojack, Cam from Modern Family, four people I went to high school with on Facebook and a handful of YouTube stars that I’m too old to know anything about, but there will be more people ringing in your birthday than any other day of the year! And that’s pretty cool.

If you’re a credit risk manager or a data scientist responsible for modeling consumer credit risk at a lender, a fintech, a telecommunications company or even a utility company you’re certainly exploring how machine learning (ML) will make you even more successful with predictive analytics. You know your competition is looking beyond the algorithms that have long been used to predict consumer payment behavior: algorithms with names like regression, decision trees and cluster analysis. Perhaps you’re experimenting with or even building a few models with artificial intelligence (AI) algorithms that may be less familiar to your business: neural networks, support vector machines, gradient boosting machines or random forests. One recent survey found that 25 percent of financial services companies are ahead of the industry; they’re already implementing or scaling up adoption of advanced analytics and ML. My alma mater, the Virginia Cavaliers, recently won the 2019 NCAA national championship in nail-biting overtime. With the utmost respect to Coach Tony Bennett, this victory got me thinking more about John Wooden, perhaps the greatest college coach ever. In his book Coach Wooden and Me, Kareem Abdul-Jabbar recalled starting at UCLA in 1965 with what was probably the greatest freshman team in the history of basketball. What was their new coach’s secret as he transformed UCLA into the best college basketball program in the country? I can only imagine their surprise at the first practice when the coach told them, “Today we are going to learn how to put on our sneakers and socks correctly. … Wrinkles cause blisters. Blisters force players to sit on the sideline. And players sitting on the sideline lose games.” What’s that got to do with machine learning? Simply put, the financial services companies ready to move beyond the exploration stage with AI are those that have mastered the tasks that come before and after modeling with the new algorithms. Any ML library — whether it’s TensorFlow, PyTorch, extreme gradient boosting or your company’s in-house library — simply enables a computer to spot patterns in training data that can be generalized for new customers. To win in the ML game, the team and the process are more important than the algorithm. If you’ve assembled the wrong stakeholders, if your project is poorly defined or if you’ve got the wrong training data, you may as well be sitting on the sideline. Consider these important best practices before modeling: Careful project planning is a prerequisite — Assemble all the key project stakeholders, and insist they reach a consensus on specific and measurable project objectives. When during the project life cycle will the model be used? A wealth of new data sources are available. Which data sources and attributes are appropriate candidates for use in the modeling project? Does the final model need to be explainable, or is a black box good enough? If the model will be used to make real-time decisions, what data will be available at runtime? Good ML consultants (like those at Experian) use their experience to help their clients carefully define the model development parameters. Data collection and data preparation are incredibly important — Explore the data to determine not only how important and appropriate each candidate attribute is for your project, but also how you’ll handle missing or corrupt data during training and implementation. Carefully select the training and validation data samples and the performance definition. Any biases in the training data will be reflected in the patterns the algorithm learns and therefore in your future business decisions. When ML is used to build a credit scoring model for loan originations, a common source of bias is the difference between the application population and the population of booked accounts. ML experts from outside the credit risk industry may need to work with specialists to appreciate the variety of reject inference techniques available. Segmentation analysis — In most cases, more than one ML model needs to be built, because different segments of your population perform differently. The segmentation needs to be done in a way that makes sense — both statistically and from a business perspective. Intriguingly, some credit modeling experts have had success using an AI library to inform segmentation and then a more tried-and-true method, such as regression, to develop the actual models. During modeling: With a good plan and well-designed data sets, the modeling project has a very good chance of succeeding. But no automated tool can make the tough decisions that can make or break whether the model is suitable for use in your business — such as trade-offs between the ML model’s accuracy and its simplicity and transparency. Engaged leadership is important. After modeling: Model validation — Your project team should be sure the analysts and consultants appreciate and mitigate the risk of over fitting the model parameters to the training data set. Validate that any ML model is stable. Test it with samples from a different group of customers — preferably a different time period from which the training sample was taken. Documentation — AI models can have important impacts on people’s lives. In our industry, they determine whether someone gets a loan, a credit line increase or an unpleasant loss mitigation experience. Good model governance practice insists that a lender won’t make decisions based on an unexplained black box. In a globally transparent model, good documentation thoroughly explains the data sources and attributes and how the model considers those inputs. With a locally transparent model, you can further explain how a decision is reached for any specific individual — for example, by providing FCRA-compliant adverse action reasons. Model implementation — Plan ahead. How will your ML model be put into production? Will it be recoded into a new computer language, or can it be imported into one of your systems using a format such as the Predictive Model Markup Language (PMML)? How will you test that it works as designed? Post-implementation — Just as with an old-fashioned regression model, it’s important to monitor both the usage and the performance of the ML model. Your governance team should check periodically that the model is being used as it was intended. Audit the model periodically to know whether changing internal and external factors — which might range from a change in data definition to a new customer population to a shift in the economic environment — might impact the model’s strength and predictive power. Coach Wooden used to say, “It isn’t what you do. It’s how you do it.” Just like his players, the most successful ML practitioners understand that a process based on best practices is as important as the “game” itself.