Financial Services

Credit cards are the most widely available credit products offered to millions of consumers today. For many consumers, owning a credit card is a relatively simple step toward establishing credit history and obtaining access to other lending products later in life. For credit unions, offering a credit card to members expands and enriches the credit relationship. In today’s environment, some credit unions don’t view credit cards as an integral part of their member service. I propose that the benefits of credit cards in a credit union portfolio are impactful, meaningful and fully align to member outreach and community service. A high-level review of risk-adjusted yields across three of the most common retail products offered by credit unions show that credit cards can be very profitable. The average APR of credit cards as of Q3 2020 is just slightly below personal loans. While charge-offs as a percentage of balances are more than double of personal loans, the estimated risk-adjusted yield is still elevated and is 1.8 times higher than auto loan and leases. See Table 1. Table 1. Estimated average risk-adjusted yield for auto loan and lease, personal loan, and credit card for credit unions Auto loan and lease Personal loan Credit card Average APR 5.21% 12.05% 11.26% Charge-offs as % of balances (annualized) 0.28% 0.89% 1.98% Risk-adjusted yield 4.93% 11.16% 9.28% Notes: Average APR of auto loans and leases, personal loans, and charge-off information as of Q3 2020 was extracted from Experian-Oliver Wyman IntelliViewSM Market Intelligence Reports. IntelliView Market Intelligence Reports, Dec. 22, 2020, experian.com/decision-analytics/market-intelligence/intelliview. Average APR of credit card as of Q3 2020 was extracted from National Credit Union Administration website. Credit Union and Bank Rates 2020 Q3, Dec. 22, 2020, https://www.ncua.gov/analysis/cuso-economic-data/credit-union-bank-rates/credit-union-and-bank-rates-2020-q3. Estimated risk-adjusted yield is calculated as the difference between average APR and charge-offs. A profitable retail product allows a credit union to share those profits back with members consistent with its mission of promoting and supporting the financial health and well-being of its members. Credit cards provide diversification of income streams. Income diversification provides a level of stability across cyclical economic conditions when some types of credit exposures may perform poorly, while others may be more stable. When combined with sound and effective risk governance, credit diversification allows lenders to mitigate levels of concentration risks in their aggregate portfolio. Offering credit cards to members is one avenue to grow loan volume and achieve scale that’s sufficiently manageable for credit unions. Scale is particularly important today as it’s needed to fund technology investments. The pandemic accelerated the massive movement toward digital engagement, and scale makes technology investments more cost-effective.  When lenders become more productive and efficient, they further lower the cost of credit products to members. (Stovall, Nathan. Dec. 14, 2020. Desire to compete with megabanks driving more U.S. regional bank M&A — KBW CE blog. https://platform.mi.spglobal.com/web/client?auth=inherit#news/.) The barriers to offering credit cards have moderately declined. Technology partners, payment processors and specialized industry companies are available in the marketplace. The biggest challenge for credit unions and lenders is credit risk management. To be profitable and to stay relevant, credit cards require a relatively sophisticated risk management framework of underwriting criteria, pricing, credit line management, operations and marketing. Industry and specialized support for launching and managing credit cards is widely available and accessible. Analytics play an essential role in managing credit cards. With an average active life of approximately five years, credit card portfolios need regular and periodic performance reviews to manage inherent risk and to identify opportunities for growth and profitability. Account management for credit cards is equally as important as underwriting. Credit line management, authorization, activation and retention have significant impact to the performance of existing accounts. Continuous engagement with members is critical and has taken on a new meaning lately. Credit cards provide an opportunity to engage members, to grow lending relationships and to support financial well-being. Marketing and meaningful card offers drive card usage and relevance. They’re critical components in customer communication and service. The benefits of credit cards contribute positively to a credit union portfolio. With sound and effective risk management practices, credit cards are profitable, help diversify income streams, grow loan volume and support member credit needs.

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

Despite the constant narrative around “unprecedented times” and the “new normal,” if the current market volatility tells us anything, it’s to go back to basics. As financial institutions navigate COVID-19’s economic impact, and challenges that are likely to be different or more extreme than in the past, the best credit portfolio management practices are fundamental. The global pandemic impacts today’s data as existing data and analytics may not accurately reflect what is happening now, resulting in inaccurate portfolio assessment. In order to successfully navigate loss forecasting, predicting borrower behavior and controlling loss ratios, lenders must engage new data, analytics and economic scenarios suited for today’s changing times. In Experian’s latest white paper, “Credit Portfolio Management After the COVID-19 Recession,” we’ll explore best practices to combat the following challenges: Forecasting credit losses despite increased economic volatility Businesses have long used a variety of data, analytics and models to anticipate and project the future direction of their organization based on a number of data points; however, with the onset of the global pandemic, long-standing scenarios became suddenly irrelevant.   Predicting borrower behavior given increased financial disparities The post-pandemic and pre-pandemic worlds are very different places for some borrowers. Pandemic-related job losses and other economic effects will not be spread evenly and this variability may be reflected in lenders’ portfolios.   Controlling loss ratios In the post-COVID world, it will be mission critical for lenders to use high-quality and up-to-date data to balance priorities and identify which areas of their portfolio need attention now.   Whether your portfolio is doing better than expected, as expected, or worse than expected, now is the time to refresh portfolio management strategy. Lenders should be watching for early indicators in loan portfolios to better navigate a fluctuating economy and that requires new resources and better tools. Take control of your business’ trajectory. Download now

Previously, we discussed the risks of account takeover and how a Defense in Depth strategy can protect your business. Before implementation it’s important to understand the financial benefits of the strategy. There are a few key steps to assessing and quantifying the value of Defense in Depth. Transaction risk assessment: This requires taking inventory of all possible transactions. Session-level risk analysis: With the transactions categorized by risk level, the next step is to review session history based on the highest risk activity within the session. Quantify the cost of a challenge: There are multiple costs associated with challenging a user using step-up authentication. Consider both direct and indirect costs – failure rate, contact center operational cost, and attrition rate following failed challenges (consider lifetime value of account) Quantify the expected challenge rate: This can be done by comparing the Defense in Depth approach to a traditional approach. Below is a calculator that will help determine the cost of the reduced challenges associated with a Defense in Depth strategy versus a traditional strategy. initIframe('5f039d2e4c508b1b0aafa4bd'); In addition to the quantitative benefits, it is important to consider some of the qualitative benefits of this approach: Challenging at moments that matter: Customers appreciate and expect protection in online banking, especially when moving money externally or updating contact information. This is a great way to achieve both convenience and security. Improved fraud management: By staging the risk decision at the transaction level, the business can balance the type of challenge with the transaction risk. There are incremental cost considerations to include in the business case as well. For instance, there is an increase in transaction calls for a risk assessment at the medium/high risk transactions – about 10% in the example above. Generally, the increased transaction cost is more than offset by the reduction in cost of challenges alone. A Defense in Depth strategy can help businesses manage fraud risk and prevent account takeover in online banking without sacrificing user experience. If you are interested in assistance with building your business case and understanding the strategies to implement a successful Defense in Depth strategy, contact us today. Contact us 1Identity Fraud in the Digital Age, Javelin Strategy & Research, September 2020

Preventing account takeover (ATO) fraud is paramount in today’s increasingly digital world. In this two-part series, we’ll explore the benefits and considerations of a Defense in Depth strategy for stopping ATO. The challenges with preventing account takeover Historically, managing fraud and identity risk in online banking has been a trade-off between customer experience and the effectiveness of fraud controls. The basic control structure relies on a lock on the front door of online banking front door—login—as the primary authentication control to defend against ATO. Within this structure, there are two choices. The first is tightening the lock, which equals a higher rate of step-up authentication challenges and lower fraud losses. The second is loosening the lock, which results in a lower challenge rate and higher fraud loses. Businesses can layer in more controls to reduce the false positives, but that only allows marginal efficiency increases and usually represents a significant expense in both time and budget to add in new controls. Now is the perfect time for businesses reassess their online banking authentication strategy for a multitude of reasons: ATO is on the rise: According to Javelin Strategy & Research, ATO increased 72% in 2019.1 Users’ identities and credentials are at more risk than ever before: Spear phishing and data breaches are now a fact of life leading to reduced effectiveness of traditional authentication controls. Online banking enrollments are on the rise: According to BioCatch, in the months following initial shelter-in-place orders across the country, banks have seen a massive spike in first time online banking access. Users expect security in online banking: Half of consumers continue to cite security as the most important factor in their online experience. Businesses who reassess the control structure for their online banking will increase the effectiveness of their tools and reduce the number of customers challenged at the same time – giving them Defense in Depth. What is Defense in Depth? Defense in Depth refers to a strategy in which a series of defense mechanisms are layered in order to protect data and information. The basic assumptions underlying the value of a Defense in Depth strategy are: Different types of transactions within online banking have different levels of inherent risk (e.g., external money movement is considerably higher risk compared to viewing recent credit card transactions) At login, the overall transaction risk associated with the session risk is unknown The risk associated with online banking is concentrated in relatively small populations – the vast majority of digital transactions are low risk This is the Pareto principle at play – i.e., about 80% of online banking risk is concentrated within about 20% of sessions. Experian research shows that risk is even more concentrated – closer to >90% of the risk is concentrated in <10% of transactions. This is relatively intuitive, as the most common activities within online banking consist of users checking their balance or reviewing recent transactions. It is much less common for customers to engage in higher risk transaction. The challenge is that businesses cannot know the session risk at the time of challenge, thus their efficiency is destined to be sub-optimal. The benefits of Defense in Depth A Defense in Depth strategy can really change the economics of an online banking security program. Adopting a strategy that continuously assesses the overall session risk as a user navigates through their session allows more efficient risk decisions at moments that matter most to the user. With that increased efficiency, businesses are better set up to prevent fraud without frustrating legitimate users. Defense in Depth allows businesses to intelligently layer security protocols to protect against vulnerability – helping to prevent theft and reputational losses and minimize end-user frustration. In addition to these benefits, a continuous risk-based approach can have lower overall operational costs than a traditional security approach. The second part of this series will explore the cost considerations associated with the Defense in Depth strategy explored above. In the meantime, feel free to reach out to discuss options. Contact us 1Identity Fraud in the Digital Age, Javelin Strategy & Research, September 2020

No two customers are the same. That’s why it’s important to go beyond the traditional credit score for a closer look at each consumer’s individual circumstance and create personalized response plans. Learn more about some of the many different customers you’ll encounter and download our guide to get recommendations for every stage of the lifecycle. Get the Guide

It’s clear that the digital transformation we experienced this year is here to stay. While there are many positives associated with this transformation – innovation, new ways to work, and greater online connectedness – it’s important that we review the risks associated with these trends as well.   In late 2019 and throughout 2020, Experian surveyed consumers and businesses. We asked about online habits, expectations for information security and plans for future spending. Unsurprisingly, about half of consumers think they’ll continue to spend more online in the coming year. Those same consumers now have a higher expectation for their online experience than before the onset of COVID-19.   Hand-in-hand with the online activity trends come increased risks associated with identity theft and fraud as criminals find new chances to steal information. In response to both of these trends, businesses and consumers want a balance between security and convenience.   Our latest trends report dives into the new opportunities 2020 has created for fraud, and the opportunities to prevent identity theft or manipulation and the associated losses while building stronger relationships.   Download the full North America Trends Report for a look into North American trends over the last year and to learn how fraud prevention and positive customer relationships are actually two sides of the same coin. North America Trends Report

Financial services companies have long struggled to make inclusive decisions for small businesses and for low- and moderate-income consumers. One key reason: to make accurate predictions of the financial risks associated with those customers’ accounts requires lenders to rely on a wider variety of data than a credit score alone. To accurately assess risk, expanded Fair Credit Reporting Act regulated data is helpful – including rental data, trended data, enhanced public records, alternative financial services data and more. This expanded FCRA data is one key to financial inclusion. Without that data, lenders risk rejecting potentially profitable customers, including so-called credit invisibles and thin file consumers. In fact, The Federal Reserve, along with four important financial services regulators, highlighted the consumer benefits of alternative data in their December 2019 interagency statement. That statement also highlighted the increased importance of managing compliance when firms use alternative data in credit underwriting. With hundreds of data sources available to help with important tasks such as verifying identity, checking credit, and assessing the value of automotive and real-estate collateral, why have some lenders been slow to use the most appropriate data attributes when making credit decisions? One reason is a matter of IT Architecture; another is priorities. Changing a business process to take advantage of new data requirements can be prohibitively lengthy and costly – ­in terms of both analytical and IT resources. This is especially true for older systems—which were seldom adapted to use Application Programming Interfaces (APIs) supporting modern data structures such as JSON. Furthermore, data access to older systems can require specific types of system connectivity such as VPNs or leased lines. Latency is important in this type of application: some of these tasks have to be done instantly in a digital-first or digital-only lending environment. So is time to market: lenders deploying analytics processes cannot wait for overtaxed IT teams to complete lengthy projects. Lenders’ analytics and IT teams have long known they need to be more agile and efficient, faster to market, and increasingly secure. Their answer, largely, has been a slow but steady migration of their systems to the cloud. A 2019 McKinsey survey revealed that CIOs were modernizing their infrastructures primarily to achieve four goals: agility and time to market, quality and reliability, cost, and security. There are other benefits as well. But if the business case for a cloud strategy was somewhat clear to IT and analytics leaders, it became crystal clear to the rest of the business in 2020. As companies shifted to at-home work using cloud-based collaboration tools, especially videoconferencing services, most companies conquered what was perhaps the final barrier to entry—the fear that the issues of data privacy and security were somehow more insurmountable with virtual machines, containers, and microservices than with on-premise infrastructure. Last quarter, the leading cloud providers ­Amazon Web Services, Google Cloud Platform, and Microsoft Azure ­reported incredible annual revenue growth: 29%, 45%, and 48% respectively. COVID-19 has proven to be the catalyst that greatly sped up the transition to cloud technologies. The jump to the cloud means that lenders are suddenly more capable than ever at making analytically sound – and therefore more financially inclusive ­decisions. The key to analytical decision-making is to use the right data and to make the most appropriate calculations (called attributes) as part of a business strategy or a mathematical model. With Experian programs such as Attribute Toolbox now available in the cloud, calculating those all-important attributes is as simple for the IT department as coding an API call. Lenders will soon be able just as easily to retrieve and process raw data from over 100 data sources, to recognize their native formats and to extract the desired information quickly enough for real-time and batch decisioning. The pandemic has brought economic distress to millions of Americans—it is unlike anything in our lifetimes. The growth of cloud computing promises to enable these consumers to obtain additional products as well as more favorable pricing and terms. It’s ironic that COVID has accelerated the adoption of the very technologies that will expand access to credit for many people who cannot currently access it from mainstream financial firms. To learn more about our Attribute Toolbox, click here. Learn More

The global pandemic has created major shifts in the ways companies operate and innovate. For many organizations, a heavy reliance on cloud applications and cloud services has become the new normal, with cloud applications being praised as “an unsung hero” for accommodating a world in crisis, as stated in an article from the Channel Company. However, cloud computing isn’t just for consumers and employees working from home. In the last few years, cloud computing has changed the way organizations and businesses operate. Cloud-based solutions offer the flexibility, reduced operational costs and fast deployment that can transform the ways traditional companies operate. In fact, migrating services and software to the cloud has become one of the next steps to a successful digital transformation. What is cloud computing? Simply put – it’s the ability to run applications or software from remote servers, hosted by external providers, also known as infrastructure-as-a-service (IaaS). Data collected from cloud computing is stored online and is accessed via the Internet. According to a study by CommVault, more than 93% of business leaders say that they are moving at least some of their processes to the cloud, and a majority are already cloud-only or plan to completely migrate. In a recent Forrester blog titled ‘Troubled Times Test Traditional Tech Titans,’ Glenn O’Donnell, Vice President, Research Director at Forrester highlights that “as we saw in prior economic crises, the developments that carried business through the crisis remained in place. As many companies shift their infrastructure to cloud services through this pandemic, those migrated systems will almost certainly remain in the cloud.” In short, cloud computing is the new wave – now more than ever during a crisis. But what are the benefits of moving to the cloud? Flexibility Cloud computing offers the flexibility that companies need to adjust to fluctuating business environments. During periods of unexpected growth or slow growth, companies can expand to add or remove storage space, applications, or features and scale as needed. Businesses will only have to pay for the resources that they need. In a pandemic, having this flexibility and easy access is the key to adjusting to volatile market conditions. Reduced operational costs Companies (big or small) that want to reduce costs from running a data center will find that moving to the cloud is extremely cost-effective. Cloud computing eliminates the high cost of hardware, IT resources and maintaining internal and on-premise data systems. Cloud-based solutions can also help organizations modernize their IT infrastructures and automate their processes. By migrating to the cloud, companies will be able to save substantial capital costs and see a higher return on investment – while maintaining efficiency. Faster deployment With the cloud, companies get the ability to deploy and launch programs and applications quickly and seamlessly. Programs can be deployed in days as opposed to weeks – so that businesses can operate faster and more efficiently than ever. During a pandemic, faster deployment speeds can help organizations accommodate, make updates to software and pivot quickly to changing market conditions. Flexible, scalable, and cost-effective solutions will be the keys to thriving during and after a pandemic. That’s why we’ve enhanced a variety of our solutions to be cloud-based – to help your organization adapt to today’s changing customer needs. Solutions like our Attribute Toolbox are now officially on the cloud, to help your organizations make better, faster, and more effective decisions. Learn More

Intuitively we all know that people with higher credit risk scores tend to get more favorable loan terms. Since a higher credit risk score corresponds to lower chance of delinquency, a lender can grant: a higher credit line, a more favorable APR or a mix of those and other loan terms. Some people might wonder if there is a way to quantify the relationship between a credit risk score and the loan terms in a more mathematically rigorous way. For example, what is an appropriate credit limit for a given score band? Early in my career I worked a lot with mathematical optimization. This optimization used a software product called Marketswitch (later purchased by Experian). One caveat of optimization is in order to choose an optimal decision you must first simulate all possible decisions. Basically, one decision cannot be deemed better than another if the consequences of those decisions are unknown. So how does this relate to credit risk scores? Credit scores are designed to give lenders an overall view of a borrower’s credit worthiness. For example, a generic risk score might be calibrated to perform across: personal loans, credit cards, auto loans, real estate, etc. Per lending category, the developer of the credit risk score will provide an “odds chart;” that is, how many good outcomes can you expect per bad outcome. Here is an odds chart for VantageScore® 3 (overall - demi-decile). Score Range How Many Goods for 1 Bad 823-850 932.3 815-823 609.0 808-815 487.6 799-808 386.1 789-799 272.5 777-789 228.1 763-777 156.1 750-763 115.6 737-750 85.5 723-737 60.3 709-723 45.1 693-709 33.0 678-693 24.3 662-678 18.3 648-662 14.1 631-648 10.8 608-631 7.9 581-608 5.5 542-581 3.5 300-542 1.5 Per the above chart, there will be 932.3 good accounts for every one “bad” (delinquent) account in the score range of 823-850. Now, it’s a simple calculation to turn that into a bad rate (i.e. what percentage of accounts in this band will go bad). So, if there are 932.3 good accounts for every one bad account, we have (1 expected bad)/(1 expected bad + 932.3 expected good accounts) = 1/(1+932.3) = 0.1071%. So, in the credit risk band of 823-850 an account has a 0.1071% chance of going bad. It’s very simple to apply the same formula to the other risk bands as seen in the table below. Score Range How Many Goods for 1 Bad Bad Rate 823-850 932.3 0.1071% 815-823 609.0 0.1639% 808-815 487.6 0.2047% 799-808 386.1 0.2583% 789-799 272.5 0.3656% 777-789 228.1 0.4365% 763-777 156.1 0.6365% 750-763 115.6 0.8576% 737-750 85.5 1.1561% 723-737 60.3 1.6313% 709-723 45.1 2.1692% 693-709 33.0 2.9412% 678-693 24.3 3.9526% 662-678 18.3 5.1813% 648-662 14.1 6.6225% 631-648 10.8 8.4746% 608-631 7.9 11.2360% 581-608 5.5 15.3846% 542-581 3.5 22.2222% 300-542 1.5 40.0000%   Now that we have a bad percentage per risk score band, we can define dollars at risk per risk score band as: bad rate * loan amount = dollars at risk. For example, if the loan amount in the 823-850 band is set as $10,000 you would have 0.1071% * $10,000 = $10.71 at risk from a probability standpoint. So, to have constant dollars at risk, set credit limits per band so that in all cases there is $10.71 at risk per band as indicated below. Score Range How Many Goods for 1 Bad Bad Rate Loan Amount $ at Risk 823-850 932.3 0.1071%  $   10,000.00  $   10.71 815-823 609.0 0.1639%  $     6,535.95  $   10.71 808-815 487.6 0.2047%  $     5,235.19  $   10.71 799-808 386.1 0.2583%  $     4,147.65  $   10.71 789-799 272.5 0.3656%  $     2,930.46  $   10.71 777-789 228.1 0.4365%  $     2,454.73  $   10.71 763-777 156.1 0.6365%  $     1,683.27  $   10.71 750-763 115.6 0.8576%  $     1,249.33  $   10.71 737-750 85.5 1.1561%  $        926.82  $   10.71 723-737 60.3 1.6313%  $        656.81  $   10.71 709-723 45.1 2.1692%  $        493.95  $   10.71 693-709 33.0 2.9412%  $        364.30  $   10.71 678-693 24.3 3.9526%  $        271.08  $   10.71 662-678 18.3 5.1813%  $        206.79  $   10.71 648-662 14.1 6.6225%  $        161.79  $   10.71 631-648 10.8 8.4746%  $        126.43  $   10.71 608-631 7.9 11.2360%  $          95.36  $   10.71 581-608 5.5 15.3846%  $          69.65  $   10.71 542-581 3.5 22.2222%  $          48.22  $   10.71 300-542 1.5 40.0000%  $          26.79  $   10.71   In this manner, the output is now set credit limits per band so that we have achieved constant dollars at risk across bands. Now in practice it’s unlikely that a lender will grant $1,683.27 for the 763 to 777 credit score band but this exercise illustrates how the numbers are generated. More likely, a lender will use steps of $100 or something similar to make the credit limits seem more logical to borrowers. What I like about this constant dollars at risk approach is that we aren’t really favoring any particular credit score band. Credit limits are simply set in a manner that sets dollars at risk consistently across bands. One final thought on this: Actual observations of delinquencies (not just predicted by the scores odds table) could be gathered and used to generate a new odds tables per score band. From there, the new delinquency rate could be generated based on actuals. Though, if this is done, the duration of the sample must be long enough and comprehensive enough to include both good and bad observations so that the delinquency calculation is robust as small changes in observations can affect the final results. Since the real world does not always meet our expectations, it might also be necessary to “smooth” the odds-chart so that its looks appropriate.

Enterprise Security Magazine recently named Experian a Top 10 Fraud and Breach Protection Solutions Provider for 2020.   Accelerating trends in the digital economy--stemming from stay-at-home orders and rapid increases in e-commerce and government funding--have created an attractive environment for fraudsters. At the same time, there’s been an uptick in the amount of personally identifiable information (PII) available on the dark web. This combination makes innovative fraud and breach solutions more crucial than ever.   Enterprise Security Magazine met with Kathleen Peters, Experian’s Chief Innovation Officer, and Michael Bruemmer, Vice President of Global Data Breach and Consumer Protection, to discuss COVID-19 digital trends, the need for robust fraud protection, and how Experian’s end-to-end breach protection services help businesses protect consumers from fraud.   According to the magazine, “With Experian’s best in class analytics, clients can rapidly respond to ever-changing environments by utilizing offerings such as CrossCore® and Sure ProfileTM to identify and prevent fraud.”   In addition to our commitment to develop new products to combat the rising threat of fraud, Experian is focused on helping businesses minimize the consequences of a data breach. The magazine noted that, “To serve as a one-stop-shop for data breach protection, Experian offers a wide range of auxiliary services such as incident management, data breach notification, identity protection, and call center support.”   We are continuously working to create and integrate innovative and robust solutions to prevent and manage different types of data breaches and fraud. Read the full article Contact us

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

The financial services industry is not always synonymous with innovation and forward-thinking. While there are some exceptions with top-10 banks and some savvy regionals, as a whole, the sector tends to fall on the latter half of the diffusion of innovation curve, usually slotting in the late majority or laggard phase. Conversely, the opposite is true for fintechs who have been an enormously disruptive force of change in financial services over the past 10 years.   For many businesses, the pandemic has created uncertainty and an inability to conduct or generate business. However, the silver lining with COVID-19 might just be that it’s driving digital innovation across industries. Andreesen Horowitz, a venture capital firm, estimates businesses of all kinds are experiencing at least two years’ worth of digitization compressed into the last six months. And while they have been significantly impacted, for fintechs who were already pushing the envelope and challenging existing business models, COVID-19 suddenly accelerated financial services innovation into overdrive. Here are three challenges fintechs are answering in the wake of the COVID-19 health crisis. Digital Banking   The first lockdowns flipped the digital switch in financial services. Seemingly overnight, banking moved digital. In April, new mobile banking registrations increased 200%, while mobile banking traffic rose 85%. Likewise, Deloitte reported online banking activity has increased 35% since the pandemic started. Being mobile-first or digital-only has allowed many fintechs to win in offering presentment, activation, underwriting, and a contextual digital interface, all capabilities that will only become more relevant as the pandemic stretches on. At Square, direct deposit volumes grew by three times from March to April, up to $1.3 billion; Chime saw record signups. Continued social distancing will only serve to accelerate customers’ use of mobile and online platforms to manage their finances.  Contactless Payments  Similar to digital banking as a whole, the health crisis has accelerated the necessity for contactless payments. Whereas convenience and a seamless customer experience may have been drivers for payments innovation in the past, now, many customers may view it as a life or death health concern. Phones, wearables and even connected vehicles are empowering customers to participate in commerce while avoiding handling cash or coming in contact with an infected surface. Through their adoption of IOT-powered contactless payments, fintechs are accelerating this area of financial services to keep customers safe.  Financial Inclusion and Speeding Economic Relief  Any disaster disproportionally affects the underbanked and those living at the poverty line, and COVID-19 is no different. While it will undoubtedly contribute to an increase in unbanked households, the pandemic may also provide an opportunity to innovate through this problem. Financial inclusion was already a focus for many fintechs, who’ve made it their mission to bring equity by offering basic financial services in a transparent way. Unencumbered by legacy systems and business models, fintechs are well positioned to work across the financial ecosystem, from financial services, retail and government to efficiently and more quickly distribute benefits to at-risk groups and impacted businesses.   From their ability to quickly ingest new and novel data sources, to a focus on using a digital-first approach to delight customers, fintechs will continue to harness their strengths to disrupt financial services, even during the pandemic. How is your fintech driving innovation and customer experience during the health crisis?   Learn more

Synthetic identity fraud, otherwise known as SID fraud, is reportedly the fastest-growing type of financial crime. One reason for its rapid growth is the fact that it’s so hard to detect, and thus prevent. This allows the SIDs to embed within business portfolios, building up lines of credit to run up charges or take large loans before “busting out” or disappearing with the funds. In Experian’s recent perspective paper, Preventing synthetic identity fraud, we explore how SID differs from other types of fraud, and the unique steps required to prevent it. The paper also examines the financial risks of SID, including: $15,000 is the average charge-off balance per SID attack Up to 15% of credit card losses are due to SID 18% - the increase in global card losses every year since 2013 SID is unlike any other type of fraud and standard fraud protection isn’t sufficient. Download the paper to learn more about Experian’s new toolset in the fight against SID. Download the paper

The CU Times recently reported on a nationwide synthetic identity fraud ring impacting several major credit unions and banks. Investigators for the Federal and New York governments charged 13 people and three businesses in connection to the nationwide scheme. The members of the crime ring were able to fraudulently obtain more than $1 million in loans and credit cards from 10 credit unions and nine banks. Synthetic Identity Fraud Can’t Be Ignored Fraud was on an upward trend before the pandemic and does not show signs of slowing. Opportunistic criminals have taken advantage of the shift to digital interactions, loosening of some controls in online transactions, and the desire of financial institutions to maintain their portfolios – seeking new ways to perpetrate fraud. At the onset of the COVID-19 pandemic, many financial institutions shifted their attention from existing plans for the year. In some cases they deprioritized plans to review and revise their fraud prevention strategy. Over the last several months, the focus swung to moving processes online, maintaining portfolios, easing customer friction, and dealing with IT resource constraints. While these shifts made sense due to rapidly changing conditions, they may have created a more enticing environment for fraudsters. This recent synthetic identity fraud ring was in place long before COVID-19. That said, it still highlights the need to have a prevention and detection plan in place. Financial institutions want to maintain their portfolios and their customer or member experience. However, they can’t afford to table fraud plans in the meantime. “72% of FI executives surveyed believe synthetic identity fraud to be more challenging than identity theft. This is due to the fact that it is harder to detect—either crime rings nurture accounts for months or years before busting out with six-figure losses, or they are misconstrued as credit losses, and valuable agent time is spent trying to collect from someone who doesn’t exist,” says Julie Conroy, Research Director at Aite Group. Prevention and Detection Putting the fraud strategy discussion on hold—even in the short term—could open up a financial institution to potential risk at time when cost control and portfolio maintenance are watch words. Canny fraudsters are on the lookout for financial institutions with fewer protections. Waiting to implement or update a fraud strategy could open a business up to increased fraud losses. Now is the time to review your synthetic identity fraud prevention and detection strategies, and Experian can help. Our innovative new tool in the fight against synthetic identity fraud helps financial institutions stop fraudsters at the door. Learn more