Apply CIS Tag

In the latest episode of “The Chrisman Commentary” podcast, Experian experts Joy Mina, Director of Product Commercialization, and David Fay, Solution Consultant, talk about reducing mortgage pipeline fallout and improving loan pull-through rate. Listen to the full episode for all the details and check out the previous episode to explore how lenders can navigate a tight mortgage market, from rates to equity. Listen to podcast

With cybersecurity threats on the rise, organizations are turning to token-based authentication as a secure and efficient solution to safeguard sensitive data and systems. Data breaches impacted 1.1 billion individuals in 2024, a staggering 490% increase from the previous year.1 Token-based authentication is a method of verifying a user's identity through digital tokens rather than traditional means such as passwords. These tokens are temporary and serve as access keys, allowing users to securely interact with systems, applications, and networks. The goal of token authentication is to strengthen security while improving the user experience. Instead of relying solely on static credentials (like passwords), which can be intercepted or stolen, leveraging a type of multi-factor authentication like tokens adds an additional layer of security by functioning as dynamic access credentials. How token-based authentication works Token authentication unfolds through a series of steps to ensure robust security. Here's a simplified breakdown of how it works in practice: User request and authentication: When a user attempts to log in, they provide their credentials (e.g., username and password). These credentials are verified by the authentication server. Token generation: After verifying the user's credentials, the server generates a token — a cryptographically secured string often containing information like the user's ID and permissions. Token sent to the user: The generated token is sent back to the user or their device to confirm authentication. Token usage for access: Now authenticated, the user uses the token to access the system or application. The token is passed along with each request to ensure the user is authorized to proceed. Token validation: Each time a token is presented to the server, its integrity and expiration are verified. If the token is valid, access is granted; if not, the session is terminated. Token expiration and renewal: Tokens are typically temporary and expire after a set period. Users must either re-authenticate or renew the token for continued access. This limits the time window during which a stolen token can be misused. Types of token authentication methods Token authentication comes in different forms to meet various use case requirements. Common types include: JSON Web Tokens (JWT) Lightweight, self-contained, and easily transferred between clients and servers, JWT is one of the most widely used token formats. It includes claims, which are bits of information about a user encoded within the token, such as roles and permissions. Example: A financial application uses JWTs to ensure only registered users can access private account data. OAuth tokens OAuth is an industry-standard authorization protocol that uses tokens to grant limited access to applications without revealing the user's credentials. It’s often used for third-party service integration. Example: When you log into an e-commerce platform using your Google credentials, OAuth tokens authorize access. Session tokens These are temporary tokens stored on the server to track authenticated sessions, commonly used in web applications to ensure secure browsing. Example: Online banking platforms rely on session tokens for secure user sessions. Refresh tokens Refresh tokens are designed to renew access tokens without requiring the user to log in repeatedly. They extend session durations while maintaining a high-security standard. Example: A subscription service app uses refresh tokens to maintain a seamless user experience without frequent logouts. Benefits of token-based authentication Token-based authentication offers several advantages that make it a preferred security measure for organizations of all sizes. Enhanced security: Tokens reduce the risk of breaches as they are temporary and encrypted. They’re also specific to sessions, applications, or devices, meaning unauthorized users cannot reuse stolen tokens effectively. Elimination of password reliance: Tokens reduce dependence on static passwords, which are often reused and susceptible to brute-force attacks. This bolsters an organization’s overall cybersecurity posture. Improved user experience: Token authentication allows for more seamless interactions by minimizing the need for repeated logins. With features like single sign-on (SSO), users enjoy convenient access to multiple platforms with a single token. Scalability: Tokens are flexible and can adapt to varied business use cases, making them ideal for organizations of all scales. For instance, application programming interfaces (APIs) and microservices can communicate securely via token exchanges. Supports compliance: Token-based authentication helps organizations meet regulatory compliance requirements by offering robust access control and audit trails. This is critical for industries like finance, healthcare, and e-commerce. Cost efficiency: While implementing token-based authentication may require an initial investment, it reduces long-term risks and costs associated with data breaches, system downtime, and customer trust. How Experian can help strengthen your authentication process At Experian, we recognize that strong security measures should never compromise the user experience. That's why we offer cutting-edge identity solutions tailored to meet the needs of organizations. Our tools allow you to integrate token-based authentication seamlessly into your systems while ensuring compliance with security best practices and industry regulations. Are you ready to take your business's security and user experience to the next level? Visit us online today. Learn more 12024-2025 Data Breach Response Guide, Experian, 2024. This article includes content created by an AI language model and is intended to provide general information.

As Valentine’s Day approaches, hearts will melt, but some will inevitably be broken by romance scams. This season of love creates an opportune moment for scammers to prey on individuals feeling lonely or seeking connection. Financial institutions should take this time to warn customers about the heightened risks and encourage vigilance against fraud. In a tale as heart-wrenching as it is cautionary, a French woman named Anne was conned out of nearly $855,000 in a romance scam that lasted over a year. Believing she was communicating with Hollywood star Brad Pitt; Anne was manipulated by scammers who leveraged AI technology to impersonate the actor convincingly. Personalized messages, fabricated photos, and elaborate lies about financial needs made the scam seem credible. Anne’s story, though extreme, highlights the alarming prevalence and sophistication of romance scams in today’s digital age. According to the Federal Trade Commission (FTC), nearly 70,000 Americans reported romance scams in 2022, with losses totaling $1.3 billion—an average of $4,400 per victim. These scams, which play on victims’ emotions, are becoming increasingly common and devastating, targeting individuals of all ages and backgrounds. Financial institutions have a crucial role in protecting their customers from these schemes. The lifecycle of a romance scam Romance scams follow a consistent pattern: Feigned connection: Scammers create fake profiles on social media or dating platforms using attractive photos and minimal personal details. Building trust: Through lavish compliments, romantic conversations, and fabricated sob stories, scammers forge emotional bonds with their targets. Initial financial request: Once trust is established, the scammer asks for small financial favors, often citing emergencies. Escalation: Requests grow larger, with claims of dire situations such as medical emergencies or legal troubles. Disappearance: After draining the victim’s funds, the scammer vanishes, leaving emotional and financial devastation in their wake. Lloyds Banking Group reports that men made up 52% of romance scam victims in 2023, though women lost more on average (£9,083 vs. £5,145). Individuals aged 55-64 were the most susceptible, while those aged 65-74 faced the largest losses, averaging £13,123 per person. Techniques scammers use Romance scammers are experts in manipulation. Common tactics include: Fabricated sob stories: Claims of illness, injury, or imprisonment. Investment opportunities: Offers to “teach” victims about investing. Military or overseas scenarios: Excuses for avoiding in-person meetings. Gift and delivery scams: Requests for money to cover fake customs fees. How financial institutions can help Banks and financial institutions are on the frontlines of combating romance scams. By leveraging technology and adopting proactive measures, they can intercept fraud before it causes irreparable harm. 1. Customer education and awareness Conduct awareness campaigns to educate clients about common scam tactics. Provide tips on recognizing fake profiles and unsolicited requests. Share real-life stories, like Anne’s, to highlight the risks. 2. Advanced data capture solutions Implement systems that gather and analyze real-time customer data, such as IP addresses, browsing history, and device usage patterns. Use behavioral analytics to detect anomalies in customer actions, such as hesitation or rushed transactions, which may indicate stress or coercion. 3. AI and machine learning Utilize AI-driven tools to analyze vast datasets and identify suspicious patterns. Deploy daily adaptive models to keep up with emerging fraud trends. 4. Real-time fraud interception Establish rules and alerts to flag unusual transactions. Intervene with personalized messages before transfers occur, asking “Do you know and trust this person?” Block transactions if fraud is suspected, ensuring customers’ funds are secure. Collaborating for greater impact Financial institutions cannot combat romance scams alone. Partnerships with social media platforms, AI companies, and law enforcement are essential. Social media companies must shut down fake profiles proactively, while regulatory frameworks should enable banks to share information about at-risk customers. Conclusion Romance scams exploit the most vulnerable aspects of human nature: the desire for love and connection. Stories like Anne’s underscore the emotional and financial toll these scams take on victims. However, with robust technological solutions and proactive measures, financial institutions can play a pivotal role in protecting their customers. By staying ahead of fraud trends and educating clients, banks can ensure that the pursuit of love remains a source of joy, not heartbreak. Learn more

Debt collectors face a multitude of challenges when it comes to contacting the right people at the right time and improving their processes for collections. We interviewed Matt Baltzer, Senior Product Management Director at Experian, to learn more about how his team is helping debt collectors engage their customers and optimize their collection strategies.

In today's evolving financial landscape and with delinquincies rising, debt collection remains a critical function for financial institutions. However, traditional methods often fall short in efficiency and customer satisfaction. Enter artificial intelligence (AI), a game-changer poised to revolutionize the debt collection industry. This blog post explores the benefits and uses of AI in debt collection, shedding light on how financial institutions can leverage this technology to enhance their strategies. Understanding AI in debt collection Artificial intelligence – which encompasses machine learning, natural language processing, and other advanced technologies – is transforming various industries, including debt collection. AI in debt collection involves using these technologies to automate and optimize processes, making them more efficient and effective. Examples of AI technologies in debt collection include chatbots, predictive analytics, and automated communication systems. Uses Predictive analytics Predictive debt collection analytics is a powerful tool in AI collections. By analyzing patterns and trends in debtor behavior, AI can forecast the likelihood of repayment. This information allows financial institutions to tailor their collection strategies to individual debtors, improving the chances of successful recovery. Chatbots and virtual assistants AI-powered chatbots and virtual assistants handle routine customer interactions, providing instant responses to common queries. These tools can escalate complex issues to human agents when necessary, ensuring that customers receive the appropriate level of support. By automating routine tasks, chatbots free up human agents to focus on more complex cases. Automated communication AI can automate communication with debtors, sending payment reminders and notifications through various channels such as email, SMS, and phone calls. These messages can be customized based on debtor profiles, ensuring that communication is personalized and effective. Automated communication helps maintain consistent contact with debtors, increasing the likelihood of timely payments. Benefits Improved operational efficiency One of the most significant advantages of AI in debt collection is improved operational efficiency. AI can automate repetitive tasks such as sending payment reminders and processing payments, reducing the need for manual intervention. This automation speeds up the process, reduces costs, and minimizes human errors, ensuring more accurate and timely collections. Enhanced customer experience AI-driven chatbots and virtual assistants can provide personalized communication, enhancing the customer experience. These AI tools are available 24/7, allowing customers to get instant responses to their queries at any time. By offering a seamless and responsive service, financial institutions can improve customer satisfaction and engagement strategies. Better decision making AI collections leverage predictive analytics to assess debtor risk and provide data-driven insights. This information enables financial institutions to develop more effective collection strategies and prioritize high-risk accounts. By making informed decisions based on predictive models, institutions can optimize collections processes and increase their chances of successful debt recovery. Cost savings Automation through AI can lead to significant cost savings. Financial institutions can achieve higher profitability by reducing the need for human intervention and lowering operational costs. Additionally, increased recovery rates due to better cure strategies contribute to overall cost efficiency. Challenges and considerations While AI offers numerous benefits, there are challenges and considerations to keep in mind. Data privacy and security are paramount, as financial institutions must ensure compliance with regulations such as General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA). Balancing automation with the need for a human touch is also crucial, as some customers may prefer interacting with human agents. Additionally, addressing potential biases in AI algorithms is essential to ensure fair and equitable treatment of all debtors. Future Trends in AI and debt collection The future of AI in debt collection looks promising, with emerging technologies poised to make a significant impact. Integration of AI with other technologies such as blockchain and the Internet of Things (IoT) could further enhance the efficiency and security of debt collection processes. As AI continues to evolve, financial institutions must stay abreast of these trends to remain competitive and effective in their collection strategies. Our debt management and collection solutions With more than 25 years of experience and a comprehensive suite of collection products, our enhanced decisioning, improved processes, and account prioritization can enable your organization to move toward a customer-centric approach that helps reduce losses and control costs. AI in debt collection offers a myriad of benefits, from improved efficiency and enhanced customer experience to better decision-making and cost savings. By leveraging AI technologies such as predictive analytics, chatbots, and automated communication, financial institutions can optimize their debt collection strategies and achieve higher recovery rates. As the industry continues to evolve, embracing AI will be crucial for financial institutions looking to stay ahead of the curve. Click below to learn more about how we can help your organization optimize your debt collection strategies to lose less and recover more. Learn more Watch our webinar on-demand This article includes content created by an AI language model and is intended to provide general information.

Property managers and landlords nationwide aim to attract reliable, long-term tenants. Gaining insight into modern renters—their tenant data, financial situations, lifestyle choices, and key priorities—gives proactive property owners and managers a competitive edge in appealing to the ideal tenant. While certain elements of the rental landscape are not within the control of market professionals, knowledge is power, and understanding the preferences, spending habits, and profiles of today’s renters can inform their business approach and success. To understand today’s renter, Experian® took a deep dive into the tenant data of the rental market landscape in its 2024 report on the U.S. rental market. Among the principal findings, Generation Z and younger millennials' dominance in this sector is rising. Today’s Renter Profile Experian research reveals movements in the demographics of the average U.S. renter, now dominated by younger individuals and lower average-income consumers. These renters face challenges as they navigate the rising costs of securing housing. The 2024 rental report delves into these changes, highlighting age and income level shifts in tenant data. Critical to property managers and landlords, this information offers an understanding of their customer base and provides insight into the rental market landscape. Gen Z on the Rise: Gen Z alone accounts for 30.5% of all renters, and their numbers are increasing, up 3.5% over a year. Gen Z and younger millennials (adults under 35) represent over 50% of the rental population. Income Declines: From January 2023 to January 2024, the tenant data showed the average income of RentBureau® renters fell from $53,100 to $52,600[1]. Higher Rent Costs: In 2024, over 50% of renters paid $1,500+ per month, with the average U.S. renter's monthly payment of $1,713. Gen Z,the youngest renter population, spends an average of $1,600 monthly on rent. This context plays an important role in examining the state of the 2024 rental market. Propensity to Move In addition to age and economic well-being, landlords should take a keen interest in tenant data related to renters’ moving habits, as these provide valuable insights into behavior and market trends. Landlords generally prefer longer-term leaseholders, and renters who stay longer provide more stability to property management efforts. Not surprisingly, generational trends appear here as well. While over 90% of all renters retained one lease over a 2-year period, tenant data indicates that Gen Z and younger millennial renters tend to move more than other age groups. This tendency stems from various factors, including a willingness to relocate to more affordable regions or areas that better suit their lifestyle preferences. With today’s evolving work environment, remote work has opened new possibilities. Again, the overarching trend is that renters stay in one place for two years. In fact, this represents 92.5% of all renters. Signs of Overall Renter Financial Health Housing is a significant monthly cost of living expense, especially for many younger adults just starting out and lower-income individuals and families. The percentage of a renter’s monthly income allocated to rental costs clearly indicates housing affordability. This tenant data reflects that higher rent-to-income ratios (RTIs) signify that renters have less financial flexibility, as a larger portion of their monthly income is allocated to rent, leaving less available for essentials, savings, and discretionary spending. On average, renters spend over 44% of their monthly income on rent, and low-to-moderate-income renters dedicate over 50% to rent. General guidelines suggest that the percentage should be no more than 30%. Higher rental costs and declining annual incomes disproportionately impact those with fewer financial means. Credit and Other Signs Landlords and property managers value tenant data, such as renter applicants' stability. Indicators such as overall credit quality and negative payment history provide valuable insights into economic well-being. While negative payment history has improved slightly, the market shows a rise in delinquencies. Experian’s research highlights that while credit scores for the general U.S. population are on the rise, the trends for renters tell a slightly different story. Between May 2023 and May 2024, tenant data revealed a 2% increase in renters fell into the near-prime and subprime credit categories. Although the implications for the future remain uncertain, this data, combined with other analytics, may offer clues about market trends and opportunities. The Future The demand for rentals remains high, particularly among young adults and lower-income households. As the economy and market forces fluctuate, so do the financial pressures on renters and rental housing availability and costs. The role of young adults and lower-income households in the rental market will continue. Landlords and property managers must tune in to demographic realities in their efforts to develop risk management and success strategies. To learn more about the state of the U.S. rental market, download Experian’s 2024 rental report. [1] RentBureau income is based on modeled income, which is estimated using credit data and other predictive factors.

As we step into 2025, the convergence of credit and fraud risk has become more pronounced than ever. With fraudsters leveraging emerging technologies and adapting rapidly to new defenses, risk managers need to adopt forward-thinking strategies to protect their organizations and customers. Here are the top fraud trends and actionable resolutions to help you stay ahead of the curve this year. 1. Combat synthetic identity fraud with advanced AI models The trend: Synthetic identity fraud is surging, fueled by data breaches and advanced AI tooling. Fraudsters are combining genuine credentials with fabricated details, creating identities that evade traditional detection methods. Resolution: Invest in sophisticated identity validation tools that leverage advanced AI models. These tools can differentiate between legitimate and fraudulent identities, ensuring faster and more accurate creditworthiness assessments. Focus on integrating these solutions seamlessly into your customer onboarding process to enhance both security and user experience. 2. Strengthen authentication against deepfakes The trend: Deepfake technology is putting immense pressure on existing authentication systems, particularly in high-value transactions and account takeovers. Resolution: Adopt a multilayered authentication strategy that combines voice and facial biometrics with ongoing transaction monitoring. Dynamic authentication methods that evolve based on user behavior and fraud patterns can effectively counter these advanced threats. Invest in solutions that ensure digital interactions remain secure without compromising convenience. 3. Enhance detection of payment scams and APP fraud The trend: Authorized Push Payment (APP) fraud and scams are increasingly difficult to detect because they exploit legitimate customer behaviors. Resolution: Collaborate with industry peers and explore centralized consortia to share insights and develop robust detection strategies. Focus on monitoring both inbound and outbound transactions to identify anomalies, particularly payments to mule accounts. 4. Optimize Your Fraud Stack for Efficiency and Effectiveness The trend: Outdated device and network solutions are no match for GenAI-enhanced fraud tactics. Resolution: Deploy a layered fraud stack with persistent device ID technology, behavioral analytics, and GenAI-driven anomaly detection. Begin with frictionless first-tier tools to filter out low-hanging fraud vectors, reserving more advanced and costly tools for sophisticated threats. Regularly review and refine your stack to ensure it adapts to evolving fraud patterns. 5. Build collaborative relationships with fraud solution vendors The trend: Vendors offer unparalleled industry insights and long-tail data to help organizations prepare for emerging fraud trends. Resolution: Engage in reciprocal knowledge-sharing with your vendors. Leverage advisory boards and industry insights to stay informed about the latest attack vectors. Choose vendors who provide transparency and are invested in your fraud mitigation goals, turning product relationships into strategic partnerships. Turning resolutions into reality Fraudsters are becoming more ingenious, leveraging GenAI and other technologies to exploit vulnerabilities. To stay ahead of fraud in 2025, let us make fraud prevention not just a resolution but a commitment to safeguarding trust and security in a rapidly evolving landscape. Learn more

Whether consumers are shopping for new credit or experiencing financial stress, monitoring their behavior is crucial — even more so in an ever-changing economy. Our latest infographic explores economic trends impacting consumers’ financial behaviors and how Experian’s Risk and Retention TriggersSM enable lenders to detect early signs of risk or churn. Key highlights include: Credit card balances climbed to $1.17 trillion in Q3 2024. As prices of goods and services remain elevated, consumers may continue to experience financial stress, potentially leading to higher delinquency rates. Increasing customer retention rates by 5% can boost profits by 25% to 95%. View the infographic to learn how Risk and Retention Triggers can help you advance your portfolio management strategy. Access infographic

In 2024, the housing market defied recession fears, with mortgage and home equity growth driven by briefly lower interest rates, strong equity positions, generally positive economic indicators, and stock market appreciation. This performance is notable because, in 2023, economists’ favorite hobby was predicting a recession in 2024. Following a period of elevated inflation, driven largely by loose monetary policy, expansionary fiscal policy, and supply chain disruptions brought on by COVID, economists were certain that the US economy would shrink. However, the economy continued outperforming expectations, even as unemployment rose modestly (Figure 2) and inflation cooled (Figure 3). Source: FRED (Figure 1, Figure 2, Figure 3). So, a good economy is good for the mortgage and home equity markets, right? Generally speaking, this statement was true. As monitored by Experian’s credit database, mortgage originations increased by approximately thirty percent year over year as of November 2024 (Figure 4), and Q3 ’24 pre-tax profit for Independent Mortgage Banks (IMBs) averaged $701 per loan.1 So, business in home lending is good — certainly better than it was during the period when the Fed was raising rates, origination volumes shrank as opposed to grew, and IMB profit per loan turned negative. Source: Experian Ascend Insights Dashboard. What constituted this growth in mortgage lending? As we all know, the Fed has lowered interest rates by 100bps since they started reducing rates in September. The market had priced in the September cut weeks prior to the actual announcement (Figure 5), and the market enjoyed a spike in refinance volume as a result (Figure 6). However, in the lead-up to and following the US presidential election, interest rates spiked back up due to the market’s expectations around future economic activity, which will dampen pressure on refinance volumes even after the recent additional rate drop. The impact of further rate drops on mortgage rates is unclear, and refinance volume still constitutes only around three percent of overall origination volume. Source: Figure 5, Figure 6 (Experian Ascend Insights Dashboard). The shift to a purchase-driven housing market What does this all mean? Our view is that pockets of refinance volume (rate and term, VA, FHA, cashout) are available to those lenders with a sophisticated targeting strategy. However, the data also very clearly indicates that this market is still very much a purchase market in terms of opportunity for originations growth. This position should not surprise long-time mortgage lenders, given that purchase volume has always constituted a significant majority of origination volume. However, this market is a different purchase market than lenders may be used to. This purchase market is different because of unprecedented statistics about the housing market itself. The average age of a first-time homebuyer recently reached a record high of 38. The average age of overall homebuyers in November of this year similarly jumped to a new record high of 56, with homes being “wildly unaffordable for young people.” Twenty-six percent of home purchases are all-cash, another record high, and homeowners have an aggregate net equity position of $17.6 trillion, fueling those all-cash purchases. The market is expensive both from an interest rate perspective and a housing price-level perspective, and those trends are driving who is buying homes and how they are buying them.2 Opportunities for lenders in 2025 What do these housing market dynamics mean for lenders? To begin with, lenders should not spend money marketing mortgages to consumers in their 50s and 60s with large equity positions. These consumers are likely to be in the 26 percent all-cash buyer cohort, and that money will be wasted since mortgages are no longer so cheap that even cash-rich buyers would take them. Further, this equity-rich generation has children, and nearly 40% of those children borrow from the bank of mom and dad to purchase their first home. Since roughly a quarter (albeit a shrinking quarter) of homebuyers are first-time homebuyers, and since 40% of those rely on help from parents to facilitate that purchase, it may make sense for lenders to identify those consumers with 1) children and 2) significant equity positions and to offer products like cash-out refinances or home equity loans/lines to help facilitate those first-time purchases. Data is critical to executing these kinds of novel marketing strategies. It is one thing to develop these marketing and growth strategies in principle and another entirely to efficiently find the consumers that meet the criteria and give them a compelling offer. Consider home equity originations. As Figure 7 illustrates, HELOC originations are strong but have completely stalled from a growth rate perspective. As Figure 8 illustrates, this is despite the market's continued growth in direct mail marketing investment. Although HELOC origination volumes are a fraction of mortgage—around $27b per month for HELOC versus $182b per month for mortgage—there are significantly more home equity direct mail offers being sent per month (39 million) for home equity products as there are for mortgage (31 million) as of October ’24.3 This all means that although many lenders have wised up to the home equity opportunity to the point of saturating the market with offers, few have successfully leveraged targeting data and analytics to craft sufficiently compelling offers to those consumers to convert those marketing leads into booked loans. Source: Figure 7 (Experian Ascend Insights Dashboard), Figure 8 (Mintel). Adapting to a resilient housing market In summary, the housing market, comprised of mortgage and home equity products, has experienced persistent growth over the past year. Many who are reading this note will have benefitted from that growth. However, as we have identified, in many respects housing market growth has 1) been concentrated to some key borrower demographics and 2) many lenders are investing in marketing campaigns that are not efficiently reaching or convincing that key housing demographic to book loans, whether it be a home equity or mortgage product. As such, as we move into 2025, Experian advises our clients to focus on the following three themes to ensure they benefit from this trend of growth into the new year: Ensure you effectively differentiate your marketing targeting, collateral, and offers for the various demographics in the market. Ensure your origination experiences for mortgage and home equity products are modern and efficient. Lenders who force all borrowers through a painful, manual legacy process will waste marketing dollars and experience pipeline fallout. Although the market is growing, other lenders are coming for your current customers. They could be coming for purchase activity, refinance opportunities, or they may be using home equity products to encroach on your existing mortgage relationship. As such, capitalizing on growth in 2025 is not merely about gaining new customers; it is also about retaining your existing book of business using high-quality data and analytics. Learn more 1 Although December numbers are available for year-over-year comparison, we excluded them due to the holiday period's strong seasonality patterns. 2 The Case-Shiller index recently topped out at record levels. 3 Mintel/Comperemedia data.

Transformations in today’s U.S. rental market reflect changing economic and market forces. These dynamic times present challenges and opportunities for property managers and landlords seeking more stability and consistency in their property occupancies. The real estate industry responded positively to the Federal Reserve's recent announcement to cut interest rates by a quarter percentage point, marking a favorable shift from previous actions that kept rates steady. However, uncertainty lingers about the extent and pace of changes in the residential real estate market, including the rental and buying sectors. Experts remain optimistic, predicting improvements as the market heads into next year's busy season. Landlords and property managers looking to attract more stable renters need to understand macro- and micro-market trends, renter demographics and preferences, and other information impacting their specific locales. Experian Housing published its 2024 report on the U.S. rental market, which provides data-driven insights into the current rental landscape. Experts examined today’s renter population, current market trends, the state of housing development, and the market’s future. Who is today’s renter? Today’s renter is still navigating financial constraints and potential marketplace affordability challenges. While location-specific information does influence the affordability of renting versus buying a home, on average, affordability remains an important factor guiding consumer decision-making. Our latest rental report highlights a notable shift in the rental market, with a growing number of younger renters and a decline in the average annual income among renters. According to Experian’s RentBureau®1, over 30% of renters are Generation Z—the youngest adult demographic. Expanding this to include individuals under 34 years old, younger renters now represent over half of all renters in the United States. Experian’s research highlights a shift in rental spending trends, showing the average income for renters now at $52,600. RentBureau data underscores the evolving financial landscape, with rent-to-income (RTI) ratios reflecting a growing commitment to housing. On average, individuals allocate 44.1% of their income to rent, while low-to-moderate-income households dedicate 52.5%. These figures exceed the traditional guideline of keeping rent within 30% of gross monthly income, underscoring the significant economic pressures faced by renters, particularly those with low-to-moderate incomes, as they navigate rising housing costs and limited affordability in the current market. This reality highlights the urgent need for broader systemic solutions to address housing availability and affordability challenges. What is happening in the rental market? Rental market trends reflect several factors, including changes in renter demographics, interest rates, housing supply and demand, and the economy. Overall, vacancy rates have stayed relatively low, which has resulted in rising rent prices, although there are signs of flattening. With fewer housing options available, many renters stay put for longer, which also contributes to availability and affordability. More renters, over 50% of all renters (a 10% increase over May 2023), are paying $1,500 or more in monthly rent, and the nationwide average rent stands at $1,713. A regional look offers greater specific insights for landlords and property managers, which is critical for truly understanding the marketplace. In 2024, 43 of 50 states have RTI ratios above the suggested guideline of 30%. California has the highest median RTI at just over 46%, followed by Massachusetts, Florida, Washington, and New Jersey. Other states facing increasing RTI ratios include Georgia, North Carolina, Colorado, Texas, and Nevada. These high ratios negatively affect affordability. At the same time, Experian Housing research indicates that over 92% of renters hold a single lease over two years. Data also shows 6.7% of renters with two leases in 24 months and others moving three or more times in this timeframe. Older generations, surprisingly, are moving more now than in recent years. Where is development headed? High mortgage rates are constraining housing development, especially for affordable entry-level homes. Roughly 50% fewer starter homes are being built, and multifamily new construction also faces constraints. With that said, multi-family housing units already under construction are coming to market. These units are generally high-end, contributing to increased rental prices. The supply coming to the market is higher-priced due to greater construction costs across the board. Contributors to the rising costs include builds in pricier metropolitan areas as well as features and modern amenities sought after by younger renters. The U.S. Census Bureau reports a slight uptick in new home construction since July 2023. How is the future looking? The U.S. economy is expected to remain stable, which should benefit renters and landlords alike. The outlook for the rental market in 2024 and 2025 remains optimistic with inflation down and the Fed rate cut, but many other factors come into play, specifically, overall economic health and the state of the employment market. For renters, the best tact is to set goals to improve their overall credit profiles and opportunities in the housing market. Individuals benefit from rent reporting. Experian RentBureau helps renters build credit profiles and open the best opportunities for the rental market and moving to the first-time homebuyer market. With rental housing still in high demand, property managers and landlords should focus on tenant screening, rent reporting, and fraud prevention as part of their risk management strategies. Focusing on these areas will increase the chances of finding quality, longer-term tenants. To learn more about the state of the U.S. rental market, download Experian Housing’s 2024 rental report. Access report 1 RentBureau® is the largest rental payment database that contains more than 36 million renter profiles. While RentBureau doesn’t represent the total U.S. rental market population, internal studies reveal RentBureau data aligns closely to historical U.S. Census data studies, which provides confidence in the deeper understandings aggregated in the report.

In today’s digital landscape, where data breaches and cyberattacks are rampant, businesses face increasing security challenges. One of the most prevalent threats is credential stuffing—a cyberattack in which malicious actors use stolen username and password combinations to gain unauthorized access to user accounts. As more personal and financial data gets leaked or sold on the dark web, these attacks become more sophisticated, and the consequences for businesses and consumers alike can be devastating.But there are ways to proactively fight credential stuffing attacks and protect your organization and customers. Solutions like our identity protection services and behavioral analytics capabilities powered by NeuroID, a part of Experian, are helping businesses prevent fraud and ensure a safer user experience. What is credential stuffing? Credential stuffing is based on the simple premise that many people reuse the same login credentials across multiple sites and platforms. Once cybercriminals can access a data breach, they can try these stolen usernames and passwords across many other sites, hoping that users have reused the same credentials elsewhere. This form of attack is highly automated, leveraging botnets to test vast numbers of combinations in a short amount of time. If an attacker succeeds, they can steal sensitive information, access financial accounts, or carry out fraudulent activities. While these attacks are not new, they have become more effective with the proliferation of stolen data from breaches and the increased use of automated tools. Traditional security methods—such as requiring complex passwords or multi-factor authentication (MFA)—are useful but not enough to prevent credential stuffing fully. How we can help protect against credential stuffing We offer comprehensive fraud prevention tools and multi-factor authentication solutions to help you identify and mitigate credential stuffing threats. We use advanced identity verification and fraud detection technology to help businesses assess and authenticate user identities in real-time. Our platform integrates with existing authentication and risk management solutions to provide layered protection against credential stuffing, phishing attacks, and other forms of identity-based fraud. Another key element in our offering is behavioral analytics, which goes beyond traditional methods of fraud detection by focusing on users' data entry patterns and interactions. NeuroID and Experian partner to combat credential stuffing We recently acquired NeuroID, a company specializing in behavioral analytics for fraud detection, to take the Experian digital identity and fraud platform to the next level.  Advanced behavioral analytics is a game-changer for preventing credential-stuffing attacks. While biometrics track characteristics, behavioral analytics track distinct actions. For example, with behavioral analytics, every time a person inputs information, clicks in a box, edits a field, and even hovers over something before clicking on it or adding the information to it, those actions are tracked. However, unlike biometrics, this data isn’t used to connect to a single identity. Instead, it’s information businesses can use to learn more about the experience and the intentions of someone on the site. NeuroID and Experian’s paired fraud detection capabilities offer several distinct advantages in preventing credential stuffing attacks: Real-time threat detection: Analyze thousands of behavioral signals in real-time to detect user behavior that suggests bots, fraud rings, credential stuffing attempts, or any number of other cybercriminal attack strategies.  Fraud risk scoring: Based on behavioral patterns, assign a fraud risk score to each user session. High-risk sessions can trigger additional authentication steps, such as CAPTCHA or step-up authentication, helping to stop credential stuffing before it occurs. Invisible to the user: Unlike traditional authentication methods, behavioral analytics work seamlessly in the background. Users do not need to take extra steps—such as answering additional security questions or entering one-time passwords. Adaptive and self-learning: As users interact with your website or app, our system continuously adapts to their unique behavior patterns. Over time, the system becomes even more effective at distinguishing between legitimate and malicious users without collecting any personally identifiable information (PII). Why behavioral data is critical in combating credential stuffing Credential stuffing attacks rely on the ability to mimic legitimate login attempts using stolen credentials. Behavioral analytics, however, can spot the subtle differences between human and bot behavior, even if the attacker has the correct credentials. By integrating behavioral analytics, you can: Prevent automated attacks: Bots often interact with websites in unnatural ways—speeding through form fields, using erratic mouse movements, or attempting logins from unusual or spoofed geographic locations. Behavioral analytics can flag these behaviors before an account is compromised. Detect account takeovers early: If a legitimate user’s account is taken over, behavioral analytics can detect the change in interactions. By monitoring behavior, businesses can detect account takeover attempts much earlier than traditional methods. Lower false positive rates: Traditional fraud prevention tools often rely on rigid rule-based systems that can block legitimate users, especially if their login patterns slightly differ from the norm. On the other hand, behavioral analytics analyzes a user's real-time behavioral data without relying on traditional static data such as passwords or personal information. This minimizes unnecessary flags on legitimate customers (while still detecting suspicious activity). Improve customer experience: Since behavioral analytics is invisible to users and requires no extra friction (like answering security questions), the login and transaction verification process is much smoother. Customers are not inconvenienced, and businesses can reduce the risk of fraud without annoying their users. The future of credential stuffing prevention Credential stuffing is a growing threat in today’s interconnected world, but with the right solutions, businesses can significantly reduce the risk of these attacks. By integrating our fraud prevention technologies and behavioral analytics capabilities, you can stay ahead of the curve in securing user identities and preventing unauthorized access. The key benefits of combining traditional identity verification methods with behavioral analytics are higher detection rates, reduced friction for legitimate users, and an enhanced user experience overall. In an era of increasingly sophisticated cybercrime, using data-driven behavioral insights to detect user riskiness is no longer just a luxury—it’s a necessity. Learn more Watch webinar

The credit card market is rapidly evolving, driven by technological advancements, economic volatility, and changing consumer behaviors. Our new 2025 State of Credit Card Report provides an in-depth analysis of the credit card landscape and strategy considerations for financial institutions. Findings include: Credit card debt reached an all-time high of $1.17 trillion in Q3 2024. About 19 million U.S. households were considered underbanked in 2023. Bot-led fraud attacks doubled from January to June 2024. Read the full report for critical insights and strategies to navigate a shifting market. Access report

Scott Brown presents at Reuters Next “If I were to look into a crystal ball, traditional lending methodology and processes will not be replaced; they will be augmented by consumers connecting to banks via APIs, contributing the data they are comfortable with, and banks using that in conjunction with historical credit data to offer newer and better products they didn’t have access to before. The convergence of data, tech and AI leads to more financial inclusion and a more modern way of underwriting.”Scott Brown, Group President Financial Services, Experian North America Scott Brown, Group President of Financial Services for Experian North America, recently presented at Reuters Next discussing the transformative power of AI and data analytics in financial services. The session also covered the top challenges that financial institutions face today and how advances in technology are helping organizations overcome those challenges. This keynote presentation was a timely follow-up to Brown’s previous appearance at the Money20/20 conference in Las Vegas, where he revealed the details of Experian’s latest innovation in GenAI technology, Experian Assistant. Brown, in a conversation with TV writer, producer and anchor Del Irani, spoke about the ethical considerations of AI innovation, what the future of underwriting may look like, and how open banking can drive financial inclusion and have a significant positive impact on both businesses and consumers. “If you are extending a line of credit to a given consumer, how do you do so in a way that’s integrated into their everyday lives? That’s where the concept of embedded finance comes in, and how to embed finance into a consumer’s life, and not the other way around.”Scott Brown, Group President Financial Services, Experian North America By embedding finance into consumers’ lives, and not the other way around, organizations can develop better strategies to balance risk and generate more revenue. He also focused on three foundational steps to take advantage of the capabilities AI offers: data quality, transparency, and responsibility. Areas of focus for implementing AI As organizations rely on more sophisticated approaches, data quality inputs are more important than ever. Inaccurate data can lead to poor business decisions that can have a negative impact on organizations’ bottom line. Transparency is also a crucial component of implementing AI solutions. Companies should be able to explain how their models work and why the end results make sense while avoiding biases. Leveraging data with AI tools allows organizations to get a better view of the consumer, which is a goal of most banks and lending institutions. Using that consumer data responsibly is important for financial institutions to establish and maintain trust with the people who use their services. While incorporating AI solutions into everyday business operations is important for financial institutions to better serve their consumers and remain competitive in the industry, a lack of access to AI tools can prevent some organizations from doing so. A fragmented approach leads to higher costs, lower efficiency, and greater risk Until recently, financial institutions have had to rely on several different technology providers and tools to optimize customer experience and operational efficiency while protecting consumers from the risk of identity theft and fraud. This fragmented approach can result in increased costs for organizations and higher risk for consumers. Now, AI technology is solving this issue by integrating functionality into a single platform, such as the Experian Ascend Technology Platform™. This streamlined access to a comprehensive suite of tools can help accelerate time-to-value while also eliminating compliance risks. Full interview available now Brown’s full interview at Reuters Next reveals more details about how Experian is empowering organizations to better serve their consumers’ financial needs through AI innovation while also helping more than 100 million Americans who don’t have access to the mainstream credit ecosystem due to being credit invisible, unscoreable, or have a low credit score. Watch the full interview to learn more about how Experian is continuing to bring financial power to all through innovative technology. Watch the full interview now

Today’s fast-paced, digital-first hiring environment calls for a more comprehensive approach to pre-employment screening. With growing pressure on employers and HR teams to make swift, accurate, and secure hiring decisions, having access to the tools and data to enhance efficiency and security is more important than ever. By evolving beyond traditional screening methods, background screeners can better meet these needs and deliver added value to their clients.  Fraud remains a significant challenge. In fact, fraud scams resulted in a staggering $485.6 billion in losses in 20231 — and hiring teams aren’t exempt from these risks. Fraudulent resumes, synthetic identities, and the risk of non-compliance with evolving regulations create a challenging landscape for pre-employment verifications. What if there was a way to make smarter, faster, and more secure hiring decisions? This article explores how background screeners can optimize pre-employment verification processes, reduce fraud risks, and ensure compliance — all while delivering a positive candidate experience. What is pre-employment screening? Employers conduct pre-employment screenings to thoroughly evaluate job candidates and make informed hiring decisions. It’s designed to verify key details about candidates, such as their identity, employment history, and references among others to assess their suitability for a role and ensure compliance with industry regulations. Enhancing traditional screening processes For decades, pre-employment background checks have been a cornerstone of the hiring process. While effective, many traditional methods face challenges in keeping up with the evolving demands of modern hiring. Delays in hiring: Background checks can oftentimes rely on manual processes, which could extend timelines leading to delays of days or even weeks. This not only slows down hiring cycles but can make it harder for employers to compete for top talent in a tight labor market. Errors and inaccuracies: Human errors, incomplete data, and inconsistencies across systems can lead to missed insights or red flags. Fraudulent activity: As hiring becomes increasingly digital, identity theft and synthetic identities present growing challenges to verifying candidate-provided data.  Regulatory challenges: With regulations like the Equal Employment Opportunity Commission (EEOC) and Fair Credit Reporting Act (FCRA), companies must navigate complex compliance requirements to avoid legal and financial repercussions. 1 in 3 HR professionals report losing top candidates due to slow pre-employment screening processes.2 These challenges highlight the opportunity to build on existing screening practices with tools that enhance speed, provide actionable insights and prevent fraud. Adapting to the evolving fraud landscape Employment fraud is becoming increasingly sophisticated, fueled by trends like the rise of remote work and digital applications. In fact, the employment sector accounted for 45% of all false document submissions in 2023, making it the most targeted industry for fraud.3 From fake references and degrees to synthetic identities created using stolen personal information, the risks are higher than ever. Synthetic identity fraud: This form of fraud — where fake identities are created by combining real and fabricated data — makes up more than 80% of all new account fraud.4 Fake credentials: Many candidates falsify qualifications or work histories to enhance their chances of securing a role. Compliance risks: Failure to verify candidate information accurately can result in legal penalties, brand reputation damage, or internal security breaches. Modernizing pre-employment screening The good news? Experian offers advanced solutions that complement existing screening processes, empowering background screeners to deliver more efficient, secure and reliable results for their clients looking to higher faster, and with greater confidence.  Gain a more holistic view of a candidate’s risk profile: Experian’s nationwide database contains files on more than 245 million credit-active consumers, providing the most current, accurate, and comprehensive information available in the industry. Conduct real-time identity verification: Leverage a range of identity verification solutions to authenticate and verify a candidate’s identity by accessing a breadth set of non-credit and credit data sources to create a robust social footprint that defines each consumer as unique individuals. Integrate advanced fraud detection: Powered by purpose-built analytics and machine learning algorithms, Experian’s fraud detection tools can detect synthetic identities, inconsistencies, and other red flags while ensuring a seamless candidate experience. Enhance compliance efforts: Experian’s solutions are designed to help businesses navigate complex compliance requirements with ease. Fraud prevention playbook in preemployment Uncover essential strategies for fraud prevention and identity verification in employment screening. Download now The pre-employment screening landscape is evolving, and staying ahead requires tools that enhance the efficiency and effectiveness of your processes. Experian’s advanced solutions are designed to complement your existing screening services, helping you reduce fraud risks, maintain compliant, and deliver data-driven insights that empower smarter hiring decisions. Get started today Ready to transform your pre-employment verification process with fraud mitigation and identity verification solutions? Explore our innovative solutions today. Learn more 1 Nasdaq finds scams led to $486 billion in losses in 2023, 2024. 2 Research reveals Candidates’ Frustrations with Hiring Process, 2024. 3 Employment Identity Fraud: Do You Know Who You’re Hiring, 2024. 4 Report: Synthetic identity fraud is growing, 2024.

Protecting consumer information is paramount in today’s digital age, especially for financial institutions. With cyber threats on the rise, robust user authentication methods are essential to safeguard sensitive data. This guide will walk you through the various user authentication types and methods, focusing on solutions that can help financial institutions enhance their security measures and protect consumers’ personal information. Understanding user authentication types Single-factor authentication (SFA) Single-factor authentication is the most basic form of authentication, requiring only one piece of information, such as a password. While it's easy to implement, SFA has significant drawbacks, particularly in the financial sector where security is critical. Passwords can be easily compromised through phishing or brute force attacks, making SFA insufficient on its own. Two-factor authentication (2FA) Two-factor authentication uses two different factors to verify a user's identity. For example, a bank might require a consumer to enter their password and then confirm their identity with a code sent to their mobile device. This method enhances security without overcomplicating the user experience. Multi-factor authentication (MFA) Multi-factor authentication adds an extra layer of security by requiring two or more verification factors. These factors typically include something you know (a password), something you have (a token or smartphone), and something you can present with your body, such as a fingerprint or facial scan (biometric data). MFA significantly reduces the risk of unauthorized access, making it a crucial component for financial institutions. Common authentication methods Password-based authentication Passwords are the most common form of authentication. However, they come with challenges, especially in the financial sector. Weak or reused passwords can be easily exploited. Financial institutions should enforce strong password policies and educate consumers on creating secure passwords. Biometric authentication Biometric authentication uses unique biological characteristics, such as fingerprints, facial recognition, or iris scans to verify identity. This method is becoming increasingly popular in banking due to its convenience and high level of security. However, a potential drawback is that it also raises privacy concerns. Token-based authentication Token-based authentication involves the use of physical or software tokens. Physical tokens, like smart cards, generate a one-time code for login. Software tokens, such as mobile apps, provide similar functionality. This method is highly secure and is often used in financial transactions. Certificate-based authentication Certificate-based authentication uses digital certificates to establish a secure connection. This method is commonly used in secure communications within financial systems. While it offers robust security, implementing and managing digital certificates can be complex. Two-factor authentication (2FA) solutions 2FA is a practical and effective way to enhance security. Popular methods include SMS-based codes, app-based authentication, and email-based verification. Each method has its pros and cons, but all provide an additional layer of security that is vital for protecting financial data. Many financial institutions have successfully implemented two factor authentication solutions. For example, a bank might use SMS-based 2FA to verify transactions, significantly reducing fraud. Another institution might adopt app-based 2FA, offering consumers a more secure and convenient way to authenticate their identity. Multi-factor authentication (MFA) solutions MFA is essential for financial institutions aiming to enhance security. Multifactor authentication solutions can provide multiple layers of protection and ensure that even if one factor is compromised, unauthorized access is still prevented. Implementing MFA requires careful planning. Financial institutions should start by assessing their current security measures and identifying areas for improvement. It's crucial to choose MFA solutions that integrate seamlessly with existing systems. Training staff and educating consumers on the importance of MFA can also help ensure a smooth transition. Knowledge-based authentication (KBA) solutions What is KBA? Knowledge-based authentication relies on information that only the user should know, such as answers to security questions. There are two types: static KBA, which uses pre-set questions, and dynamic KBA, which generates questions based on the user's transaction history or other data. Effectiveness of KBA While KBA can be effective, it has its limitations. Static KBA is vulnerable to social engineering attacks, where fraudsters gather information about the user to answer security questions. Dynamic KBA offers more security but can be more complex to implement. Financial institutions should weigh the pros and cons of KBA and consider combining it with other methods for enhanced security. Enhancing KBA security To improve KBA security, financial institutions can combine it with other user authentication types, such as MFA or 2FA. This layered approach ensures that even if one method is compromised, additional layers of security are in place. Best practices for knowledge based authentication solutions include regularly updating security questions and using questions that are difficult for others to guess. Using authentication methods to protect consumer information Choosing the right authentication methods is crucial for financial institutions to protect consumer information and maintain trust. By understanding and implementing robust authentication solutions like MFA, 2FA, and KBA, banks and financial services can significantly enhance their security posture. As cyber threats continue to evolve, staying ahead with advanced authentication methods will be key to safeguarding sensitive data and ensuring consumer confidence. Experian’s multifactor authentication solutions can enhance your existing authentication process while reducing friction, using risk-assessment tools to apply the appropriate level of security. Learn how your organization can provide faster, more agile mobile transactions, risk protection for your business, and security and peace of mind for your consumers. Visit our website to learn more This article includes content created by an AI language model and is intended to provide general information.