Financial Services

 Technology has dramatically transformed the financial services landscape, fostering innovation and enhancing operational efficiency. In an interview at this year’s Money20/20 conference, Scott Brown, Group President of Financial and Marketing Services for Experian, sat down with Fintech Futures’ North America Correspondent Heather Sugg to share how Experian is leveraging data, analytics, and artificial intelligence (AI) to modernize the financial services industry. During the discussion, Scott highlighted the recent launch of Experian Assistant — our newest generative AI tool designed to accelerate the modeling lifecycle, resulting in greater productivity, improved data visibility, and reduced delays and expenses. While Experian Assistant is a business-to-business solution built alongside our clients, Scott also noted its broader impact — helping increase credit access for underserved consumers. “At Experian, we’re really focused on addressing the underserved community who doesn’t have access to credit,” said Scott. “And we think that this tool helps lenders reach those customers in an easier way.”  Learn more about Experian Assistant and watch our tech showcase to see the solution in action. Learn more Watch tech showcase

Do you know where your customers stand? Not literally, of course, but do you know how recent macroeconomic changes and their personal circumstances are currently affecting your portfolio? While refreshing your customers’ credit data quarterly works for some aspects of portfolio management, you need more frequent access to fresh data to quickly respond to risky customer behavior and new credit needs before your portfolio takes a hit. Use triggers to improve portfolio management Event-based credit triggers provide daily or real-time alerts about important changes in your customers’ financial situations. You can use these to manage risk by promptly responding to signs of changing creditworthiness or to prevent attrition by proactively reaching out to customers who are shopping for credit. Risk Triggers℠ and Retention Triggers℠ offer a real-time solution that can be customized to fit your needs for daily portfolio management. What are Risk Triggers? Experian’s Risk Triggers alert you of notable information, such as unfavorable utilization rate changes, delinquencies with other lenders and recent activity with high-interest, short-term loan products. This solution allows you to monitor how your customers manage accounts with other lenders to get ahead of potential risk on your book. You can use Risk Triggers to get daily insights into your customers’ activity — allowing you to quickly identify potentially risky behavior and take appropriate action to limit your exposure and losses. Types of Risk Triggers Choose from a defined Risk Triggers package that could help you identify high-risk customers, including: New trades Increasing credit utilization or balances over limit New collection accounts An account is charged-off A credit grantor closes an account New delinquency statuses (30 to 180 days past due) Consumers seeking access to short-term, high-risk financing options Bankruptcy and deceased events How to use Risk Triggers You can use the daily alerts from Risk Triggers to help inform your account management strategy. Depending on the circumstances, you might: Decrease credit limits Close or freeze accounts Accelerate payment requests Continue monitoring accounts for other signs of risk Spotlight on Experian’s Clarity Services events Included in Risk Triggers are events from Experian’s Clarity Services, which draw on expanded FCRA-regulated data* from a leading source of alternative financial credit data.  For example, you could get an alert when someone has a new inquiry from non-traditional loans. These triggers provide a broader view of the customer – offering added protection against risky behavior. What are Retention Triggers? Experian’s Retention Triggers can alert you when a customer improves their creditworthiness, is shopping for new credit, opens a new tradeline or lists property. Proactively responding to these daily alerts can help you retain and strengthen relationships with your customers — which is often less expensive than acquiring new customers. Types of Retention Triggers Choose from over 100 Retention Triggers to bundle, including: New trades New inquiries Credit line increases Property listing statuses Improving delinquency status Past-due accounts are brought current or paid off How to use Retention Triggers You can use Retention Triggers to increase lifetime customer value by proactively responding to your customers’ needs and wants. You might: Increase credit limits Offer promotional financing, such as balance transfers Introduce perks or rewards to strengthen the relationship Append attributes for improved decisioning  By appending credit attributes to Risk and Retention Trigger outputs, you can gain greater insight into your accounts.  Premier AttributesSM is Experian's core set of 2,100-plus attributes. These can quickly summarize data from consumers' credit reports, allowing you to more easily segment accounts to make more strategic decisions across your portfolio.  Trended 3DTM attributes can help you spot and understand patterns in a customer's behavior over time. Integrating trended attributes into a triggers program can help you identify risk and determine the next best action. Trended 3D includes more than 2,000 attributes and provides insights into industries such as bankcard, mortgage, student loans, personal loans, collections and much more.  By working with both triggers and attributes, you'll proactively review an account, so you can then take the next best action to improve your portfolio's profits. Customize your trigger strategy When you partner with Experian, you can bundle and choose from hundreds of Risk and Retention Triggers to focus on risk, customer retention or both. Additionally, you can work with Experian’s experts to customize your trigger strategy to minimize costs and filter out repetitive or unneeded triggers: Use cool-off periods Set triggering thresholds Choose which triggers to monitor Establish hierarchies for which triggers to prioritize Create different strategies for segments of your portfolio Learn more about Risk and Retention Triggers. Learn more *Disclaimer: “Alternative Financial Credit Data” refers to the use of alternative data and its appropriate use in consumer credit lending decisions, as regulated by the Fair Credit Reporting Act. Hence, the term “Expanded FCRA-Regulated Data” may also apply in this instance, and both can be used interchangeably.

The open banking revolution is transforming the financial services landscape, offering banks and financial institutions unprecedented access to consumer-permissioned data. However, during our recent webinar, “Navigating Open Banking: Strategies for Banks and Financial Institutions,” over 78% of attendees stated that they do not currently have an open banking strategy in place. This highlights a significant gap in the industry. By tapping into consumer-permissioned data, you can develop more personalized products, streamline credit decisioning, and improve overall customer engagement. With the right strategies, open banking offers a pathway to growth, innovation, and enhanced customer experiences. Here’s a snippet from the webinar’s Q&A session with Ashley Knight, Senior Vice President of Product Management, who shared her perspective on open banking trends and opportunities. Q: What specific analytic skill is the most important when working on open banking data?A: The ability to parse and transform raw data, a deep understanding of data mining, experience in credit risk, and general modeling skills to improve underwriting. Q: What lessons did the U.S. learn from the experience of other countries that implemented open banking? A: The use cases are common globally; typical uses of open banking data include second-chance underwriting to help score more consumers and customer management, which involves assessing cashflow data to leverage on an existing portfolio (first-party data). This can be used in various ways, such as cross-sell, up-sell, credit line increase, and growing/retaining deposits. Q: Does Experian have access to all a consumer’s bank accounts in cases where the consumer has multiple accounts?A: Data access is always driven by consumer permission unless the organization owns this data (i.e., first-party data). Where first-party data is unavailable, we collect it through clients or lenders who send it to us directly, having gained the proper consent. Yes, we can intake data from multiple accounts and provide a categorization and attribute calculation. Q: Where does the cashflow data come from? Is it only credit card spending?A: It includes all spending data from bank accounts, checking accounts, credit cards, savings, debit cards, etc. All of this can be categorized, and we can calculate attributes and/or scores based on that data. Q: What is the coverage of Experian’s cashflow data, and how is it distributed across risk bands?A: Cashflow data moves through Experian directly from consumer permissioning for B2B use cases or from institutions with first-party data. We perform analytics and calculate attributes on that portfolio. Don’t miss the chance to learn from our industry leaders on how to navigate the complexities of open banking. Whether you are a seasoned professional or just starting to explore its potential, this webinar will equip you with the knowledge you need to stay ahead. Watch on-demand recording Learn more Meet our expert Ashley Knight, Senior VP of Product Management, Experian Ashley leads our product management team focusing on alternative data, scores, and open banking. She fosters innovation and drives financial inclusion by using new data, such as cash flow, analytics, and Experian’s deep expertise in credit.

This series will explore our monthly State of the Economy report, which provides a snapshot of the top monthly economic and credit data for financial service professionals to proactively shape their business strategies. After the Federal Reserve announced its first cut since 2020 in September, several pieces of economic data have surpassed expectations. Job creation was almost double economists’ estimates, unemployment ticked down, and personal incomes were revised up. Alongside these areas of strength, inflation continued to prove stubborn. The October State of the Economy report fills in the rest of the developing macroeconomic story. This month’s highlights include:  Unemployment decreased for the second month in a row, down to 4.1%. Core inflation increased from 3.2% to 3.3%, driven by shelter and service costs. Negative rental payment activity has declined 1.9% over the past year. Check out our report for a detailed analysis of the rest of this month’s data, including the latest trends in originations, retail sales, and consumer sentiment. Download October's report As our economy continues to fluctuate, it's critical to stay updated on the latest developments. Subscribe to our new series, The Macro Moment, for economic commentary from Experian NA’s Chief Economist, Joseph Mayans, with additional economic resources, including our new Lending Conditions Chartbook and our new Labor Market Monitor. For more economic trends and market insights, visit Experian Edge.

In today’s digital age, call center fraud is a growing threat that businesses can no longer afford to ignore. As fraudsters become increasingly sophisticated, it’s crucial for companies to implement robust security measures to protect both their operations and their consumers. Various forms of call center fraud can have a significant impact on businesses. To prevent this, companies can use effective strategies including multifactor authentication solutions and account takeover prevention techniques. But first, what is call center fraud? Understanding call center fraud Call center fraud occurs when fraudsters exploit vulnerabilities in customer service operations to gain unauthorized access to sensitive information and commit identity theft. This type of fraud can take many forms, including social engineering, which occurs when a fraudster manipulates a call center agent into providing information or access, and phishing, which occurs when fraudsters use deceptive tactics to obtain confidential details from unsuspecting individuals. One of the most concerning tactics used by fraudsters is impersonation, or pretending to be legitimate consumers to gain access to accounts. Once they have access, they can make unauthorized transactions, change account details, or even take over the account entirely—a scenario known as an account takeover. The impact of these fraudulent activities can be devastating, leading to significant financial losses, damage to brand reputation, and a loss of consumer trust. Key strategies for preventing call center fraud According to recent research, account takeover fraud has increased by 330% in the past two years, projecting to cost $6.24 billion globally.[1] In addition, the number of U.S. consumers who have experienced account takeover has increased from 22% in 2021 to 29% in 2023.[2] To effectively combat call center fraud, businesses must adopt a multi-layered approach that includes advanced technological solutions, comprehensive employee training, and real-time monitoring. Here are some of the most effective strategies: 1. Implementing multifactor authentication (MFA) solutions One of the most effective ways to secure consumer interactions is by implementing multifactor authentication (MFA) solutions. MFA requires users to provide two or more verification factors to gain access to an account or complete a transaction. This adds an extra layer of security, making it significantly more difficult for fraudsters to succeed even if they have obtained some of the consumer’s information. MFA can be integrated into call center operations in several ways. For example, businesses can use voice recognition as a biometric factor, requiring consumers to verify their identity through a unique voiceprint. Other methods include sending a one-time code via text message, which the consumer must provide during the call, or using mobile app verification, where consumers approve transactions directly through their smartphones. 2. Account takeover prevention Account takeover is one of the most serious threats to call centers, as they involve fraudsters gaining control of a consumer’s account, often with disastrous consequences. To prevent account takeover, businesses can employ a combination of technological solutions and best practices. First, understanding what account takeover entails is crucial. It typically begins when a fraudster obtains some of the consumer’s personal information—often through phishing, social engineering, or a data breach. They then use this information to impersonate the consumer and convince call center agents to provide them with access to the account. To combat this, businesses can employ several account takeover prevention techniques. Anomaly detection systems can flag unusual activities, such as login attempts from unfamiliar locations or devices, prompting additional verification steps. Behavioral biometrics is another powerful tool, analyzing patterns in how users interact with their devices to detect inconsistencies that may indicate fraud. Continuous authentication, where the system continuously verifies the user’s identity throughout the session, is also effective in catching fraudsters in the act. 3. Training and awareness Technology alone may not be enough to entirely prevent call center fraud—human factors are equally important. Regular training for call center staff is essential to ensure team members can recognize and respond to potential fraud attempts. Employees should be trained to identify common tactics used by fraudsters, such as social engineering, and to follow strict verification procedures before providing any sensitive information. Awareness campaigns can also play a significant role in preventing fraud. Internally, companies should run regular campaigns to remind employees of the importance of adhering to security protocols. Externally, educating consumers about the risks of fraud and encouraging them to use security features like MFA can help reduce the likelihood of successful attacks. 4. Real-time monitoring and analytics Real-time monitoring is a critical component of an effective fraud prevention strategy. By continuously monitoring calls and transactions, businesses can quickly identify and respond to suspicious activities before they escalate. Advanced analytics tools, including voice analytics and behavior analysis, can provide valuable insights into potential fraud, allowing companies to take proactive measures. Voice analytics, for instance, can detect stress or hesitation in a caller’s voice, which may indicate that they are not who they claim to be. Behavior analysis can track how consumers typically interact with their accounts, flagging deviations from the norm as potential fraud. Continuous improvement is key here—regularly reviewing and updating monitoring protocols ensures that businesses stay ahead of evolving threats. Preventing call center fraud in your business By using a multi-layered fraud approach through a variety of authentication solutions, your business can quickly detect call center fraud without disrupting your consumers’ experience. Identify the risk Identity-based risk detection can pinpoint when a specific identity may be in the hands of fraudsters. Device intelligence solutions can recognize the risk associated with a specific device used to attempt online access. Address the risk Knowledge-based authentication (KBA) can quickly authenticate users by asking questions only they can answer, which can deter fraudsters. MFA services can generate and deliver a one-time password to a consumer’s mobile device to verify their identity in real time. Document verification allows your business to collect and verify images of identity documents uploaded from a consumer’s mobile device. Protect your business and your consumers from call center fraud Call center fraud is a significant threat that requires a proactive and comprehensive approach to prevention. By implementing strategies such as multifactor authentication solutions, account takeover prevention techniques, and robust employee training, businesses can significantly reduce their risk of falling victim to fraud. In today’s fast-paced digital world, staying vigilant and proactive is the key to safeguarding your call center against fraud. Act now to protect your business and maintain the trust of your consumers. Enable your call center to detect risk quickly and effectively with our robust fraud prevention solutions. Get started Download our identity and fraud report This article includes content created by an AI language model and is intended to provide general information. [1] Worldmetrics.org, Account Takeover Statistics: Losses to Reach $6.24 Billion Globally, 2024. [2] Security.org, Account Takeover Incidents are Rising: How to Protect Yourself in 2024.

This series will explore our monthly State of the Economy report, which provides a snapshot of the top monthly economic and credit data for financial service professionals to proactively shape their business strategies. During their September meeting, the Federal Reserve made a highly-anticipated announcement to cut rates for the first time since 2020. Fed officials cut rates by 50bps, while also penciling in an additional 50bps of cuts for 2024 and 100bps of cuts in 2025 in their Summary of Economic Projections. While rates are coming down and inflation continues to cool, there were downward revisions to job creation made in August and declining job openings in July. Data highlights from this month’s report include: The Federal Reserve announced a 50bps rate cut during the September meeting. Annual headline inflation cooled from 2.9% to 2.5%, getting closer to the Fed’s 2% goal. Mortgage originations increased 7.0% in August. Check out our report for a deep dive into the rest of this month’s data, including the latest trends in job creation, retail sales, and consumer sentiment. Download September's report As our economy continues to fluctuate, it's critical to stay updated on the latest developments. Subscribe to our new series, The Macro Moment, for economic commentary from Experian North America's Chief Economist, Joseph Mayans, and download our new Lending Conditions Chartbook for additional insights. For more economic trends and market insights, visit Experian Edge.

Effective collection strategies are critical for the financial health of credit unions. Unlike traditional banks, credit unions often emphasize member relationships and community values, making the collection process more tactful. Crafting a strategy that balances the need for financial stability with member-centric values is essential.  Here’s a step-by-step guide on how to create an effective credit union collection strategy. 1. Understand your members The foundation of an effective credit union collection strategy is understanding your members. Credit unions often serve specific communities or groups, and members may face unique financial challenges. By analyzing member demographics, financial behavior, and common reasons for delinquency, you can tailor your approach to be more vigilant and effective. Segment members: Group members based on factors like loan type, payment history, and financial behavior. This allows for targeted communications and outreach strategies. Member communication preferences: Determine how your members prefer to be contacted—whether by phone, email, or in person. This can increase engagement and responsiveness. 2. Prioritize compliance Compliance with regulations is non-negotiable in the collections process. Ensure that your strategy adheres to all relevant laws and guidelines. Fair Debt Collection Practices Act (FDCPA): Ensure that your team is fully trained on the FDCPA and that your practices comply with its requirements. State and local regulations: Be aware of any state or local regulations that may impact your collections process. This could include restrictions on contact methods or times. Internal audits: Regularly conduct internal audits to ensure compliance and identify any areas of risk. 3. Leverage technology for efficiency Technology can streamline the collection process, making it more efficient and a better member experience. Automated reminders: Use automated systems to send reminders before and after payment due dates. This reduces the likelihood of missed payments due to forgetfulness. Data analytics: Use data analytics to identify trends in member behavior, establish a collections prioritization strategy, and predict potential delinquencies. This allows your team to be proactive rather than reactive. Digital communication channels: Implement digital communication options, such as text messages or chatbots to make it easier for members to interact with the credit union. 4. Establish clear communication protocols Early and frequent communication is key to preventing delinquency and managing it when it occurs. Create clear protocols for member communication that prioritize empathy and treatment plans over demands. Early intervention: Reach out to members as soon as they miss a payment. Early intervention can prevent minor issues from escalating. Consistent communication: Ensure that your communication is consistent across all channels. Whether a member receives a call, an email, or a letter, the message should be clear and aligned with the credit union’s values. Human understanding: Train your collections team to use a compassionate tone. Members are more likely to respond positively when they feel understood and respected. 5. Offer flexible payment solutions Flexibility is crucial when working with members who are struggling financially. Offering a range of payment solutions can help members stay on track and reduce the likelihood of default. Customized treatment plans: Offer customizable payment plans that fit the member’s financial situation. This could include lower payments over a longer term or temporary payment deferrals. Loan modifications: In some cases, modifying the terms of the loan—such as extending the repayment period or lowering the interest rate—may be necessary to help the member succeed. Debt consolidation options: If a member has multiple loans, consider offering debt consolidation to simplify their payments and reduce their overall financial burden. 6. Train your collection team Your collection team is the frontline of your strategy. Providing them with the right training and tools is essential for success. Ongoing training: Regularly update your team on the latest regulations, best practices, and communication techniques. This keeps them informed and prepared to handle various situations. Better decision making: Empower your team to make decisions that align with the credit union’s values. This could include offering payment extensions or waiving late fees in certain situations. Regular support: Working in collections can be complex. Provide resources and support to help your team manage stress and maintain a positive attitude. 7. Monitor and adjust your strategy A successful credit union collection strategy is dynamic. Regularly monitor its performance and adjust as needed. Key performance indicators (KPIs): Track KPIs such as delinquency rates, recovery rates, roll-rates and member satisfaction to gauge the effectiveness of your strategy. Member feedback: Survey members who have gone through the collections process. Their insights can help you identify areas for improvement. Continuous improvement: Use data and feedback to continuously refine your strategy. What worked last year may not be as effective today, so staying adaptable is key. Creating an effective credit union collections strategy requires a balance of empathy, effective communication, and compliance. By understanding your members, communicating clearly, offering flexible solutions, leveraging technology, and continuously improving your approach, you can develop a strategy that not only reduces delinquency but also strengthens member relationships. In today’s fiercely competitive landscape, where efficiency and efficacy stand paramount, working with the right partner equipped with innovative credit union solutions can dramatically transform your outcomes. Choosing us for your debt collection needs signifies an investment in premier analytics, advanced debt recovery tools, and unmatched support.  Learn more Watch credit union collection chat This article includes content created by an AI language model and is intended to provide general information.

In this article...What is reject inference? How can reject inference enhance underwriting? Techniques in reject inference Enhancing reject inference design for better classification How Experian can assist with reject inference  In the lending world, making precise underwriting decisions is key to minimizing risks and optimizing returns. One valuable yet often overlooked technique that can significantly enhance your credit underwriting process is reject inferencing. This blog post offers insights into what reject inference is, how it can improve underwriting, and various reject inference methods.  What is reject inference?  Reject inference is a statistical method used to predict the potential performance of applicants who were rejected for a loan or credit — or approved but did not book. In essence, it helps lenders and financial institutions gauge how rejected or non-booked applicants might have performed had they been accepted or booked. By incorporating reject inference, you gain a more comprehensive view of the applicant pool, which leads to more informed underwriting decisions.  Utilizing reject inference helps reduce biases in your models, as decisions are based on a complete set of data, including those who were initially rejected. This technique is crucial for refining credit risk models, leading to more accurate predictions and improved financial outcomes.  How can reject inference enhance underwriting?  Incorporating reject inference into your underwriting process offers several advantages:  Identifying high-potential customers: By understanding the potential behavior of rejected applicants, you can uncover high-potential customers who might have been overlooked before.  Improved risk assessment: Considering the full spectrum of applicants provides a clearer picture of the overall risk landscape, allowing for more informed lending decisions. This can help reduce default rates and enhance portfolio performance.  Optimizing credit decisioning models: Including inferred data from rejected and non-booked applicants makes your credit scoring models more representative of the entire applicant population. This results in more robust and reliable predictions.  Techniques in reject inference  Several techniques are employed in reject inference, each with unique strengths and applications. Understanding these techniques is crucial for effectively implementing reject inference in your underwriting process. Let's discuss three commonly used techniques:  Parceling: This technique involves segmenting rejected applicants based on their characteristics and behaviors, creating a more detailed view of the applicant pool for more precise predictions.  Augmentation: This method adds inferred data to the dataset of approved applicants, producing a more comprehensive model that includes both approved and inferred rejected applicants, leading to better predictions.  Reweighting: This technique adjusts the weights of approved applicants to reflect the characteristics of rejected applicants, minimizing bias towards the approved applicants and improving prediction accuracy.  Pre-diction method  The pre-diction method is a common approach in reject inference that uses data collected at the time of application to predict the performance of rejected applicants. The advantage of this method is its reliance on real-time data, making it highly relevant and current.  For example, pre-diction data can include credit bureau attributes from the time of application. This method helps develop a model that predicts the outcomes of rejected applicants based on performance data from approved applicants. However, it may not capture long-term trends and could be less effective for applicants with unique characteristics.  Post-diction method  The post-diction method uses data collected after the performance window to predict the performance of rejected applicants. Leveraging historical data, this method is ideal for capturing long-term trends and behaviors.  Post-diction data may include credit bureau attributes from the end of the performance window. This method helps develop a model based on historical performance data, which is beneficial for applicants with unique characteristics and can lead to higher performance metrics. However, it may be less timely and require more complex data processing compared to pre-diction.  Enhancing reject inference design for better classification  To optimize your reject inference design, focus on creating a model that accurately classifies the performance of rejected and non-booked applicants. Utilize a combination of pre-diction and post-diction data to capture both real-time and historical trends.  Start by developing a parceling model using pre-diction data, such as credit bureau attributes from the time of application, to predict rejected applicants' outcomes. Regularly update your model with the latest data to maintain its relevance.  Next, incorporate post-diction data, including attributes from the end of the performance window, to capture long-term trends. Combining both data types will result in a more comprehensive model.  Consider leveraging advanced analytics techniques like machine learning and artificial intelligence to refine your model further, identifying hidden patterns and relationships for more accurate predictions. How Experian can assist with reject inference  Reject inference is a powerful tool for enhancing your underwriting process. By predicting the potential performance of rejected and non-booked applicants, you can make more inclusive and accurate decisions, leading to improved risk assessment and optimized credit scoring models.  Experian offers various services and solutions to help financial institutions and lenders effectively implement reject inference into their decisioning strategy. Our solutions include comprehensive and high-quality datasets, which empower you to build models that are more representative of the entire applicant population. Additionally, our advanced analytics tools simplify data analysis and model development, enabling you to implement reject inference efficiently without extensive technical expertise.  Ready to elevate your underwriting process? Contact us today to learn more about our suite of advanced analytics solutions or hear what our experts have to say in this webinar.  Watch Webinar Learn More This article includes content created by an AI language model and is intended to provide general information. 

Replay attacks may threaten your customers’ online security Today, consumer online security is more important than ever. This year, the FTC has already received nearly six million reports of fraud, and 1.4 million of those cases were specifically identity theft.[1] In addition, a recent study reported that losses due to identity fraud amounted to almost $23 billion in 2023.[2] And consumers aren’t the only ones at risk. According to CyberArk’s global research report, 93% of organizations had two or more identity-related breaches in the past year.[3] This means it’s not only up to consumers to protect themselves against identity theft. It’s also up to businesses to protect themselves and their customers from the threat of fraud. As security technology advances, so do the tactics of hackers attempting to steal information such as usernames, account numbers, and passwords from innocent online users. One method that hackers use to obtain this information is called a replay attack, which can pose a serious threat to your customers’ online security. What is a replay attack? A replay attack is a network-based security hack in which a hacker intercepts legitimate data transmission and then fraudulently repeats it to gain access to a network or system. These attacks are designed to fool the victim into believing the hacker is a genuine user, and they happen in three steps: Eavesdropping: The hacker listens in on secure network communications, such as information sent through a Virtual Private Network (VPN), to learn about the activity happening on that network. Interception: The hacker intercepts legitimate user information – usernames, user activity, computer specs, passwords, etc. Replay: The hacker illegally resends (or “replays”) the valid information they gathered to trick the receiver into thinking that they are a genuine user. Here’s an example: John transfers funds from one online banking account to another. A hacker illegally captures that transaction message (which is often accompanied by a digital signature or token) and “replays” that same transaction message multiple times to trigger additional fund transfers, all without the genuine user’s knowledge or permission. The bank doesn’t recognize a problem because the “replayed” transaction messages includes the legitimate digital signature/token, so the bank approves the additional transfers. Replay attacks aren’t just used for banking transactions. They can be used for various activities, such as: Internet of Things (IoT) device attacks: IoT devices include a multitude of “smart home” devices such as smart plugs, cameras, locks, appliances, speakers, lights, and more. Vulnerabilities in these devices can allow hackers to replicate commands to these devices that seem legitimate, such as turning on cameras, unlocking doors, and disabling security systems.[4] Remote keyless entry systems for vehicles: Most vehicles use a remote key fob to lock and unlock the doors. This key fob usually uses radio waves to send the lock/unlock signal to the car. Hackers can use a device to receive and transmit radio waves near a person’s vehicle that mimic that same lock/unlock signal, and then “replay” that signal to unlock the person’s car themselves.[5] Text-dependent speaker verification: Some people use voice recognition to verify their identity when accessing an account or system. Hackers can record a person’s voice when the person speaks to verify their identity, and then “replay” that voice recording to fraudulently access the account.[6] How to prevent replay attacks Replay attacks are dangerous because they are often unnoticed or overlooked until the damage has already been done. Fortunately, there are ways to stop hackers from using replay attacks to access your customers’ personal information. Device intelligence: By leveraging unique intelligence about the device being used, replay attacks can be thwarted even when fraudsters are using authentic, but stolen, information. Time stamping: By forcing a timestamp on all sent and received messages, you can prevent hackers from sending repeated messages with legitimate information obtained illegally. Geolocation review: By identifying suspicious language and/or time zones, you can compare access routes to confirm customers are authentic and secure. Why it matters for your business Consumers in the U.S. value network security more than ever, with 70% rating security a top priority, even over personalization and convenience.[7] People want to feel safe online, and if they experience a threat of identity theft or fraud, they’ll need to find a reliable resource to keep their personal information secure. Successful replay attacks allow fraudsters to impersonate real users and potentially gain partial or full access to their personal online accounts. If your customers fall victim to these kinds of attacks, the resulting stress may have a negative impact on your relationship with them. With our fraud management solutions, your business can strengthen your customers’ trust and security by leveraging highly trained fraud analysts to help uncover suspicious activity that might not be noticed otherwise. Lower fraud losses and achieve fraud capture rates that exceed industry averages. Protect your customers by using a covert, frictionless solution the reduces false positives. Improve operational efficiency by prioritizing resources across the board. Protect your consumers with powerful fraud management solutions 63% of consumers say it’s important for businesses to be able to recognize them online, and 81% say they are more trusting of businesses that can accomplish easy and accurate identification.[8] While replay attacks can cause consumers stress and anxiety, taking action to prevent them can fortify a strong, trusting relationship between your business and your customers. Protect your customers and prevent replay attacks with our powerful fraud management solutions. Get started [1] IdentityTheft.org, 2024 Identity Theft Facts and Statistics. [2] Javelin, 2024 Identity Fraud Study: Resolving the Shattered Identity Crisis. [3] CyberArk, Report: 93% of Organizations Had Two or More Identity-Related Breaches in the Past Year, May 2024. [4] Hackster.io, IoT Devices May Be Susceptible to Replay Attacks with a Raspberry Pi and RTL-SDR Dongle, 2017. [5] Automotive World, How to mitigate vulnerabilities in keyless entry systems, 2023. [6] Antispoofing, Audio Replay Attacks and Countermeasures Against Them, 2022. [7] 2018 Experian® Global Fraud Report [8] Experian® 2024 Identity and Fraud Report Highlights Evolving Fraud Landscape This article includes content created by an AI language model and is intended to provide general information.

This series will dive into our monthly State of the Economy report, providing a snapshot of the top monthly economic and credit data for those in financial services to proactively shape their business strategies. The labor market has been a source of strength for the U.S. economy coming out of the pandemic, providing workers with stable employment and solid wages. However, the labor market has slowed in recent months, with lower-than-expected job creation and rising unemployment, causing weakening sentiment in the broader market. This has resulted in increased pressure on the Federal Reserve to begin cutting rates and places more importance on the incoming data between now and the September FOMC meeting. Data highlights from this month’s report include: Job creation declined in July, falling short of economists’ expectations. Unemployment increased from 4.1% to 4.3%. Inflation cooled again in July, with annual headline inflation easing from 3.0% to 2.9%. GDP picked up in Q2 to 2.8%, primarily driven by strong consumer spending. Check out our report for a deep dive into the rest of this month’s data, including the latest trends in originations, retail sales, and the new housing market. Download August's report To have a holistic view of our current environment, it’s important to view the economy from different angles and through different lenses. Download our latest macroeconomic forecasting report for our views on what's to come in the U.S. economy and listen to our latest Econ to Action podcast. For more economic trends and market insights, visit Experian Edge.

Alternative lending is continuing to revolutionize the financial services landscape. From full-file public records to cash flow transactions, alternative credit data empowers financial institutions to make more informed lending decisions.  This article focuses on cashflow insights and how they help financial institutions drive profitable and inclusive growth.  Challenges with traditional credit underwriting  Traditional underwriting often limits access to credit for marginalized communities, including young adults, immigrants, and those from low-income backgrounds. Because the process relies heavily on credit history and credit scores to determine an applicant’s ability to pay, those with less-than-ideal credit profiles could be overlooked. This then creates a cycle — those who are already disadvantaged face further barriers to accessing credit, limiting their abilities to invest in opportunities that can improve their financial situations, such as education or homeownership.  Additionally, traditional underwriting models can be rigid. Consumers with stable incomes or significant assets may be denied credit if their financial profiles don’t fit the narrow criteria established by traditional models. As the financial landscape evolves, it’s important for lenders to adopt more inclusive and adaptive approaches to credit underwriting.  What is cashflow underwriting?  Cashflow underwriting is a modern approach to evaluating a borrower’s creditworthiness. It uses fresh, consumer-permissioned bank account transaction (balance, income and expense) data, giving lenders greater visibility into loan applicants’ financial situation. This process is made possible through open banking, an established, secure framework that enables consumers to quickly and easily share their bank account information with third-party financial service providers.  READ: Learn more about the open banking landscape.  Let’s look at a few quick examples:   A prospective tenant is filling out a rental application. Instead of manually submitting paystubs to verify their income, open banking facilitates the digital sharing of full cashflow data in seconds, enabling property managers to quickly access the applicant’s full cash flow information.  A consumer was previously denied credit due to insufficient credit history. With cashflow underwriting, the consumer is offered a second chance to qualify for the loan by including cashflow data in the lender’s decisioning model. The additional information gathered on the consumer’s ability to pay can transform the initial decline decision into an approval.   Cashflow underwriting can also be used for credit line management. By assessing a borrower’s income and expense transactions, lenders can recommend optimal credit limits that cater to their spending potential while minimizing risk.  Benefits of cashflow underwriting  There are many benefits to integrating cashflow data into the credit underwriting process, including:  Enhanced risk assessment. Going off credit scores and repayment behaviors alone won’t provide lenders with a complete or current picture of applicants. Through open banking, lenders can gain access to cashflow data in real-time, allowing them to more accurately assess consumers, increase approvals, and reduce credit risk.  Inclusive lending. Over 100 million adult Americans are considered unscoreable, invisible, or subprime.1 However, 71% of consumers are willing to share their banking information if it could improve their chances of getting approved for credit.2 With deeper insights into consumers’ income and expenses, lenders can increase credit access in underserved communities.  Improved customer experiences. Gaining a more comprehensive view of a consumer’s financial situation enables lenders to determine what loan products they’re eligible for and craft personalized options.  READ: Learn more about the benefits of leveraging alternative data for credit underwriting.  Get started  Cashflow underwriting represents a significant step forward in the world of lending. It offers a more comprehensive approach to assessing creditworthiness, helping financial institutions drive growth and profitability.   Experian’s Cashflow Attributes are an open banking enabled solution that provides lenders with consumer-permissioned insights into borrowers’ financial behaviors. With 940+ attributes derived from transaction data across 133 categories, financial institutions can make smarter, more inclusive lending decisions. Learn more about Cashflow Attributes Learn more about open banking 1 2023 State of Alternative Credit Data Report, Experian, 2023.  2 Atomik Research survey of 2,005 U.S. adults online, matching national demographics, 2024.  This article includes content created by an AI language model and is intended to provide general information. 

Gen Z, or "Zoomers," born from 1997 to 2012, are molded by modern transformations. They have witnessed events from post-9/11 impacts to the rise of the internet and the COVID-19 crisis. As early adopters of technology, their lives are intertwined with smartphones, online shopping, social platforms, cloud services, emerging fintech, and artificial intelligence. They are called “digital natives” as they are the first generation to grow up with internet as part of their daily life. Research generally indicates that this post-millennial generation values practicality, favoring financial stability over entrepreneurial pursuits. They appreciate communication tailored to them and often employ social media to cultivate their personal brands. As a generation growing up immersed in technology, they tend to choose digital interactions, seeking to forge robust, secure, genuine, and unconstrained digital experiences. The challenge of identity verification Identity verification presents a considerable challenge for Generation Z. According to a Fortune survey, close to 50% of this demographic regrets not opening financial accounts earlier, citing a lack of readiness to join the financial ecosystem by the age of 18. Consequently, this has given rise to "digital ghosts"—people with minimal or nonexistent financial histories who face challenges when trying to utilize financial services. The 2009 Credit Card Accountability Responsibility and Disclosure Act mandates that individuals under 21 need a cosigner or show income proof to get a credit card, hindering their early financial involvement. Moreover, conventional identity checks are becoming less reliable due to the surge in identity theft. Innovative solutions for verifying Gen Z Verifying identities and preventing fraud among Gen Z presents unique challenges due to their digital-native status and limited credit histories. Here are some effective strategies and approaches that financial institutions can adopt to address these challenges: Leveraging alternative data sources Academic records leverage information from higher learning institutions such as universities, colleges, and vocational schools. This data can be vital for authenticating the identities of younger individuals who may lack a substantial credit history. Employment verification retrieve data confirming the identity and employment status, especially focusing on Gen Z who are new to the job market. Utility and telecom records leverage payment histories for utilities, phone bills, and other recurring services, which can provide additional layers of identity verification. Alternative financial data includes online small dollar lenders, online installment lenders, single payment, line of credit, storefront small dollar lenders, auto title and rent-to-own. Phone-Centric ID Phone-Centric Identity refers to technology that leverages and analyzes mobile, telecom, and other signals for the purposes of identity verification, identity authentication, and fraud prevention. Phone-Centric Identity relies on billions of signals from authoritative sources pulled in real time, making it a powerful proxy for digital identity and trust. Advance authentication technologies Behavioral biometrics analyze user behaviors such as typing patterns, navigation habits, and device usage. These subtle behaviors can help create a unique profile for each user, making it difficult for fraudsters to impersonate them. Adaptive risk-based authentication that adjusts the level of security based on the user's behavior, location, device, and other factors. For example, a higher level of verification might be required for transactions that are deemed unusual or high-risk. Real-time fraud detection AI and machine learning: Deploy AI and machine learning algorithms to analyze transaction patterns and detect anomalies in real-time. These technologies can identify suspicious activities and flag potential fraud. Fraud analytics: Use predictive analytics to assess the likelihood of fraud based on historical data and current behavior. This approach helps in proactively identifying and mitigating fraudulent activities. Secure digital onboarding Digital identity verification: Implement digital onboarding processes that include online identity verification with real-time document verification. Users can upload government-issued IDs and take selfies to confirm their identity. Video KYC (Know Your Customer): Use video calls to conduct KYC processes, allowing bank representatives to verify identities and documents remotely via automated identity verification. This method is secure and convenient for tech-savvy Gen Z customers. Make identity verification easy To authenticate identities and combat fraud within the Gen Z population, financial organizations need to implement a comprehensive strategy utilizing innovative technologies, non-traditional data, and strong protective protocols. Such actions will enable the creation of a trustworthy and frictionless banking environment that appeals to a generation adept in digital interactions, thereby establishing trust and encouraging enduring connections. To learn more about Experian’s automated identity verification solutions, visit our website. Learn more 

With the noticeable uptick in delinquencies, credit unions face more significant hurdles in effectively managing overdue accounts. In this challenging financial landscape, it’s imperative that you refine your account management processes to remain competitive, preserve the well-being of your members, assure operational efficiency, and increase profitability.  Implementing efficient collection approaches not only improves loss rates but also helps with member retention, which is the backbone of your success. Grab a cup of coffee and join our experts on August 22 @ 1:00 p.m. ET/ 10:00 a.m. PT, for an engaging conversation on credit union collection trends and successful account management strategies. Highlights include: Current landscape: Gain valuable insight and understanding into the current debt collection environment for credit unions. Navigating challenges: Discover effective tips and strategies to tackle obstacles in your business, improve loss rates, and enhance member retention. Real-time Q&A: Participate in a live Q&A session where our experts will address your questions. Watch on-demand

Getting customers to respond to your credit offers can be difficult. With the advent of artificial intelligence (AI) and machine learning (ML), optimizing credit prescreen campaigns has never been easier or more efficient. In this post, we'll explore the basics of prescreen and how AI and ML can enhance your strategy.  What is prescreen?  Prescreen involves evaluating potential customers to determine their eligibility for credit offers. This process takes place without the consumer’s knowledge and without any negative impact on their credit score.  Why optimize your prescreen strategy?  In today's financial landscape, having an optimized prescreen strategy is crucial. Some reasons include:  Increased competition: Financial institutions face stiff competition in acquiring new customers. An optimized prescreen strategy helps you stand out by targeting the right individuals with tailored offers, increasing the chances of conversion.  Customer expectations: Modern customers expect personalized and relevant offers. An effective prescreen strategy ensures that your offers resonate with the specific needs and preferences of potential customers.  Strict budgets: Organizations today are faced with a limited marketing budget. By determining the right consumers for your offers, you can minimize prescreen costs and maximize the ROI of your campaigns.  Regulatory compliance: Compliance with regulations such as the Fair Credit Reporting Act (FCRA) is essential. An optimized prescreen strategy helps you stay compliant by ensuring that only eligible individuals are targeted for credit offers.  Financial inclusion: 49 million American adults don’t have conventional credit scores. An optimized prescreen strategy allows you to send offers to creditworthy consumers who you may have missed due to a lack of traditional credit history.  How AI and ML can enhance your strategy  AI and ML can revolutionize your prescreen strategy by offering advanced analytics and custom response modeling capabilities.  AI-driven data analytics  AI analytics allow financial institutions to analyze vast amounts of data quickly and accurately. This enables you to identify patterns and trends that may not be apparent through traditional analysis. By leveraging data-centric AI, you can gain deeper insights into customer behavior and preferences, allowing for more precise targeting and increased response rates.  LEARN MORE: Explore the benefits of AI for credit unions.  Custom response modeling  Custom response models enable you to better identify individuals who fall within your credit criteria and are more likely to respond to your credit offers. These models consider various factors such as credit history, spending habits, and demographic information to predict future behavior. By incorporating custom response models into your prescreen strategy, you can select the best consumers to engage, including those you may have previously overlooked.  LEARN MORE: AI can be leveraged for numerous business needs. Learn about generative AI fraud detection.   Get started today  Incorporating AI and ML into your prescreen campaigns can significantly enhance their effectiveness and efficiency. By leveraging Experian's Ascend Intelligence Services™ Target, you can better target potential customers and maximize your marketing spend.   Our optimized prescreen solution leverages:  Full-file credit bureau data on over 245 million consumers and over 2,100 industry-leading credit attributes.  Exclusive access to the industry's largest alternative datasets from nontraditional lenders, rental data inputs, full-file public records, and more.  24 months of trended data showing payment patterns over time and over 2,000 attributes that help determine your next best action.  When it comes to compliance, Experian leverages decades of regulatory experience to provide the documentation needed to explain lending practices to regulators. We use patent-pending ML explainability to understand what contributed most to a decision and generate adverse action codes directly from the model.  For more insights into Ascend Intelligence Services Target, view our infographic or contact us at 855 339 3990. View infographic This article includes content created by an AI language model and is intended to provide general information. 

This series will dive into our monthly State of the Economy report, providing a snapshot of the top monthly economic and credit data for those in financial services to proactively shape their business strategies. While much of the economic data released this month remained steady, including continued downward progress in inflation and resilience in inflation-adjusted spending, June was a pivotal month for the labor market. With downward revisions to job creation over the past few months to an up-tick in unemployment, the potential for a sooner-than-expected rate cut increased. Data highlights from this month’s report include: While above economists’ expectations in June, job creation was 111,000 jobs shy of what was recorded in April and May, signaling some slowdown in the labor market. Inflation-adjusted spending and incomes increased in May, by 0.3% and 0.5%, respectively. Inflation eased more than economists expected, with annual headline inflation cooling from 3.3% to 3.0%. Check out our report for a deep dive into the rest of this month’s data, including the latest trends in job openings, new business survival rates, and bankcard delinquency rates. Download July's report  To have a holistic view of our current environment, it’s important to view the economy from different angles and through different lenses. Watch our experts discuss the latest economic and credit trends in the next macroeconomic forecasting webinar and listen to our latest Econ to Action podcast. For more economic trends and market insights, visit Experian Edge.