Market Trends

Open banking is revolutionizing the financial services industry by encouraging a shift from a closed model to one with greater transparency, competition, and innovation. But what does this mean for financial institutions, and how can you adapt to this new landscape, balancing opportunity against risk? In this article, we will define open banking, illustrate how it operates, and weigh the challenges and benefits for financial institutions. What is open banking? Open banking stands at the forefront of financial innovation, embodying a shift toward a more inclusive, transparent, and consumer-empowered system. At its core, open banking relies on a simple yet powerful premise: it uses consumer-permissioned data to create a networked banking ecosystem that benefits both financial institutions and consumers alike.  By having secure, standardized access to consumer financial data — granted willingly by the customers themselves — lenders can gain incredibly accurate insights into consumer behavior, enabling them to personalize services and offers like never before. How does open banking work? Open banking is driven by Application Programming Interfaces (APIs), which are sets of protocols that allow different software components to communicate with each other and share data seamlessly and securely. In the context of open banking, these APIs enable: Account Information Services (AIS): These services allow third-party providers (TPPs) to access account information from financial institutions (with customer consent) to provide budgeting and financial planning services. Payment Initiation Services (PIS): These services permit TPPs to initiate payments on behalf of customers, often offering alternative, faster, or cheaper payment solutions compared to traditional banking methods. Financial institutions must develop and maintain robust and secure APIs that TPPs can integrate with. This requires significant investment in technology and cybersecurity to protect customer data and financial assets. There must also be clear customer consent procedures and data-sharing agreements between financial institutions and TPPs. Benefits of open banking Open banking is poised to create a wave of innovation in the financial sector. One of the most significant benefits is the ability to gain a more comprehensive view of a consumer’s financial situation. With a deeper view of consumer cashflow data and access to actionable insights, you can improve your underwriting strategy, optimize account management and make smarter decisions to safely grow your portfolio.  Additionally, open banking promotes financial inclusion by enabling financial institutions to offer more tailored products that suit the needs of previously underserved or unbanked populations. This inclusivity can help bridge the gap in financial services, making them accessible to a broader segment of the population. Furthermore, open banking fosters competition among financial institutions and fintech companies, leading to the development of better products, services, and competitive pricing. This competitive environment not only benefits consumers but also challenges banks to innovate, improve their services, and operate more efficiently. The collaborative nature of open banking encourages an ecosystem where traditional banks and fintech startups co-create innovative open banking solutions. This synergy can accelerate the pace of digital transformation within the banking sector, leading to the development of cutting-edge technologies and platforms that address specific market gaps or consumer demands.  Challenges of open banking While open banking presents a plethora of opportunities, its adoption is not without challenges. Financial institutions must grapple with several hurdles to fully leverage the benefits open banking offers. One of the most significant challenges is fraud detection in banking and ensuring data security and privacy. The sharing of financial data through APIs necessitates robust cybersecurity measures to protect sensitive information from breaches and fraud. Banks and TPPs alike must invest in advanced security technologies and protocols to safeguard customer data. Additionally, regulatory compliance poses a considerable challenge. Open banking regulations vary widely across different jurisdictions, requiring banks to adapt their operations to comply with diverse legal frameworks. Staying abreast of evolving regulations and ensuring compliance can be resource-intensive and complex. Furthermore, customer trust and awareness are crucial to the success of open banking. Many consumers are hesitant to share their financial data due to privacy concerns. Educating customers on the benefits of open banking and the measures taken to ensure their data’s security is essential to overcoming this obstacle. Despite these challenges, the strategic implementation of open banking can unlock remarkable opportunities for innovation, efficiency, and service enhancement in the financial sector. Banks that can successfully navigate these hurdles and capitalize on the advantages of open banking are likely to emerge as leaders in the new era of financial services. Our open banking strategy Our newly introduced open banking solution, Cashflow Attributes, powered by Experian’s proprietary data from millions of U.S. consumers, offers unrivaled categorization and valuable consumer insights. The combination of credit and cashflow data empowers lenders with a deeper understanding of consumers. Furthermore, it harnesses our advanced capabilities to categorize 99% of transaction Demand Deposit Account (DDA) and credit card data, guaranteeing dependable inputs for robust risk assessment, targeted marketing and proactive fraud detection.  Watch open banking webinar Learn more about Cashflow Attributes

Click here to watch our recent webinar on first-time homebuyers. The younger generations comprise nearly 70% of first-time homebuyers, according to recent Experian Mortgage research. Understanding the generational traits of first-time homebuyers, particularly motivated younger generations, is critical to building highly targeted marketing strategies. Gen Z and Gen Y are essential in the first-time homebuyer market and represent close to 40% of repeat buyers, indicating they consider homeownership important beyond just their first purchase. Generation Y borrowers lead the pack Generation Y borrowers see homeownership as part of the American Dream but have waited longer than previous generations to purchase their first home.1 Additionally, as digital natives, they have grown up in a world with online resources and digital tools, making the home buying process more convenient for them. They can effortlessly research homes, compare mortgage rates, and even complete paperwork without leaving their home – a time and cost-saving advantage. With their desire for stability and their technological proficiency, it comes as no surprise that Gen Y borrowers are at the forefront of the homebuying market, accounting for 52% of all first-time buyers. Keep your eye on the next wave: Generation Z borrowers Although Generation Z is the youngest group with both young adults and those entering adulthood, they should not be overlooked in the real estate market. Despite their age, Gen Z possesses characteristics and tendencies that make them legitimate potential first-time homebuyers. Having grown up in an era characterized by technical advancements and economic instability, Gen Z has observed various challenges, such as the impact of the 2008 financial crisis on their families. They have also witnessed their parents and older siblings navigating student loan debt and a volatile job market. As a result, Gen Z individuals tend to approach life decisions with a cautious mindset. However, it is important to note that Gen Z is a generation known for their ambition and determination. They have an entrepreneurial spirit. A strong desire for stability. According to a recent survey conducted by Chase2, homeownership holds an important place in the dreams of nearly 90% of Generation Z individuals. This unwavering aspiration for owning a home and increasing purchasing power establishes Generation Z as a significant influence in the real estate market. Market to each generation where they are most comfortable, for Y and Z it is online and on the go To get the attention of these younger generations, mortgage lenders must understand that for these groups, digital technology is the norm, integrated into all aspects of their lives. They rely heavily on social media, online reviews, and mobile apps for research and communication. Therefore, it is crucial for lenders to implement a marketing strategy that encompasses social media platforms and personalized email, and, increasingly, text communications, to resonate with the tech savvy nature of these generations. That said, there is nuance in every population, and we see this when observing communication preferences across generations. We know, for example, that first-time homebuyers are considerably more likely than the general public to respond to e-mail offers. Understanding communication preferences for each prospect is important for tailoring your omni-channel marketing approach. Growing up in a world where technology is constantly advancing, Generations Y and Z are accustomed to having immediate access to information and services at their fingertips. As a result, they expect an efficient mortgage lending process that uses online, smartphone-enabled tools and platforms. They count on the ability to complete applications and paperwork online, receive updates and notifications via email or text, and have access to resources and tools to track and manage their mortgage journey. Lenders embracing these realities about Gen Y and Gen Z and connecting with them where they are, will be better positioned to serve this demographic and grow their own business. For more information about the lending possibilities for first-time homebuyers, download our latest white paper. Download white paper 1 “Bank of America’s 2023 Homebuyer Insights Report Explores How Hopeful Buyers are Forging Ahead,” bankofamerica.com.  2 “Millennial and Gen Z Adults Still See American Dream Within Reach Despite Challenges,” chase.com.  

Current economic conditions present genuine challenges for mortgage lenders. In this environment, first-time homebuyers offer exciting, perhaps unexpected, business growth potential. Market uncertainties have kept potential borrowers anxious and on the sidelines. The Federal Reserve's recent announcement that interest rates will remain steady for now has added to borrower anxiety. First-time homebuyers are no exception. They are concerned about the “right” time to jump in, buy a home, and own a mortgage. Despite worries over high interest rates and low inventory, many first-time homebuyers are tired of waiting for rates to drop and inventory to blossom. First-time buyers are eager to explore all avenues necessary to achieve homeownership. They show a willingness to be flexible when it comes to finding a house, considering options like a fixer upper or expanding their search to more affordable locations. The desire to escape the uncertainty and financial burden of renting is a strong driving force for first-time buyers. They see homeownership as a way to establish stability and build equity for their future. Despite the obstacles renters face in the competitive housing market, these potential buyers are motivated. Lenders who take time to understand who these buyers are and what matters to them will be ahead of the game. Notwithstanding stubbornly high interest rates, first-time homebuyers historically have shown remarkable resilience amid market fluctuations. According to a recent deep dive by Experian Mortgage experts into the buying patterns of first-time homebuyers, this group made 35-48% of all new purchases and 8-12% of all refinances between July 2022 and September 2023. First-time buyers represent both immediate potential and long-term client opportunities. How can lenders attract first-time homebuyers and drive growth from this market? The first-time homebuyer market largely consists of individuals in their early 40s and younger, also known as Gen Y and Gen Z. Rising costs of renting a home frustrate these individuals who are trying to save money for a down payment on a house and ultimately, buy their dream home. They want to settle down and look ahead to the future. For mortgage lenders who focus on understanding this younger first-time buyer market and developing targeted business strategies to attract them, great growth potential exists. Often, younger people feel locked out of buying opportunities, which creates uncertainty and apprehension about entering the market. This presents mortgage industry professionals with an incredible opportunity to show their value and grow their client base. To attract this market segment, lenders must adapt. Lenders must develop a comprehensive picture of this younger generation. Who are they? How do they shop? Where do they want to live? What is their financial situation? What are their financial and personal goals?  Acknowledging difficulties in the housing market and showing them a well-conceived path forward to home ownership will win the day for the lender and the buyer. As interest rates are poised to decrease in 2024-2025, there is potential for a surge in demand from first-time homebuyers. Lenders should prepare for these potential buyers, now. It is crucial to reevaluate how to approach first-time buyers to identify new opportunities for expansion. Experian Mortgage examined first-time homebuyer trends to pinpoint prospects with good credit and provide analysis on potential areas of opportunity. For more information about the lending possibilities for first-time homebuyers, download our white paper. Download white paper

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. As we near the end of the first quarter, the U.S. economy has maintained its solid standing. We're also starting to see some easing in a few areas. This month saw a slight uptick in unemployment, slowed spending growth, and a slight increase in annual headline inflation. At the same time, job creation was robust, incomes continued to grow, and annual core inflation cooled. In light of the mixed economic landscape, this month’s upcoming Federal Reserve meeting and their refreshed Summary of Economic Projections should shine some light on what’s in store in the coming months. Data highlights from this month’s report include: Annual headline inflation increased from 3.1% to 3.2%, while annual core inflation cooled from 3.9% to 3.8%. Job creation remained solid, with 275,000 jobs added this month. Unemployment increased to 3.9% from 3.7% three months prior. Mortgage delinquencies rose for accounts (2.3%) and balances (1.8%) in February, contributing to overall delinquencies across product types. Check out our report for a deep dive into the rest of March’s data, including consumer spending, the housing market, and originations. To have a holistic view of our current environment, we must understand our economic past, present, and future. Check out our annual chartbook for a comprehensive view of the past year and download our latest forecasting report for a look at the year ahead. Download March's State of the Economy report  Download latest forecast For more economic trends and market insights, visit Experian Edge.

This article was updated on March 6, 2024. Advances in analytics and modeling are making credit risk decisioning more efficient and precise. And while businesses may face challenges in developing and deploying new credit risk models, machine learning (ML) — a type of artificial intelligence (AI) — is paving the way for shorter design cycles and greater performance lifts. LEARN MORE: Get personalized recommendations on optimizing your decisioning strategy Limitations of traditional lending models Traditional lending models have worked well for years, and many financial institutions continue to rely on legacy models and develop new challenger models the old-fashioned way. This approach has benefits, including the ability to rely on existing internal expertise and the explainability of the models. However, there are limitations as well. Slow reaction times:  Building and deploying a traditional credit risk model can take many months. That might be okay during relatively stable economic conditions, but these models may start to underperform if there's a sudden shift in consumer behavior or a world event that impacts people's finances. Fewer data sources:  Traditional scoring models may be able to analyze some types of FCRA-regulated data (also called alternative credit data*), such as utility or rent payments, that appear in credit reports. Custom credit risk scores and models could go a step further by incorporating data from additional sources, such as internal data, even if they're designed in a traditional way. But AI-driven models can analyze vast amounts of information and uncover data points that are more highly predictive of risk. Less effective performance:  Experian has found that applying machine learning models can increase accuracy and effectiveness, allowing lenders to make better decisions. When applied to credit decisioning, lenders see a Gini uplift of 60 to 70 percent compared to a traditional credit risk model.1 Leveraging machine learning-driven models to segment your universe From initial segmentation to sending right-sized offers, detecting fraud and managing collection efforts, organizations are already using machine learning throughout the customer life cycle. In fact, 79% are prioritizing the adoption of advanced analytics with AI and ML capabilities, while 65% believe that AI and ML provide their organization with a competitive advantage.2 While machine learning approaches to modeling aren't new, advances in computer science and computing power are unlocking new possibilities.3 Machine learning models can now quickly incorporate your internal data, alternative data, credit bureau data, credit attributes and other scores to give you a more accurate view of a consumer's creditworthiness. By more precisely scoring applicants, you can shrink the population in the middle of your score range, the segment of medium-risk applicants that are difficult to evaluate. You can then lower your high-end cutoff and raise your low-end cutoff, which may allow you to more confidently swap in  good accounts (the applicants you turned down with other models that would have been good) and swap out bad accounts (those you would have approved who turned bad). Machine learning models may also be able to use additional types of data to score applicants who don't qualify for a score  from traditional models. These applicants aren't necessarily riskier — there simply hasn't been a good way to understand the risk they present. Once you can make an accurate assessment, you can increase your lending universe by including this segment of previously "unscorable" consumers, which can drive revenue growth without additional risk. At the same time, you're helping expand financial inclusion to segments of the population that may otherwise struggle to access credit. READ MORE: Is Financial Inclusion Fueling Business Growth for Lenders? Connecting the model to a decision Even a machine learning model doesn't make decisions.4 The model estimates the creditworthiness of an applicant so lenders can make better-informed decisions. AI-driven credit decisioning software can take your parameters (such cutoff points) and the model's outputs to automatically approve or deny more applicants. Models that can more accurately segment and score populations will result in fewer applications going to manual review, which can save you money and improve your customers' experiences. CASE STUDY:  Atlas Credit, a small-dollar lender, nearly doubled its loan approval rates while decreasing risk losses by up to 20 percent using a machine learning-powered model and increased automation. Concerns around explainability One of the primary concerns lenders have about machine learning models come from so-called “black box" models.5 Although these models may offer large lifts, you can't verify how they work internally. As a result, lenders can't explain why decisions are made to regulators or consumers — effectively making them unusable. While it's a valid concern, there are machine learning models that don't use a black box approach. The machine learning model doesn't build itself and it's not really “learning" on its own — that's where the black box would come in. Instead, developers can use machine learning techniques to create more efficient models that are explainable, don't have a disparate impact on protected classes and can generate reason codes that help consumers understand the outcomes. LEARN MORE: Explainability: Machine learning and artificial intelligence in credit decisioning Building and using machine learning models Organizations may lack the expertise and IT infrastructure required to develop or deploy machine learning models. But similar to how digital transformations in other parts of the business are leading companies to use outside cloud-based solutions, there are options that don't require in-house data scientists and developers. Experian's expert-guided options can help you create, test and use machine learning models and AI-driven automated decisioning; Ascend Intelligence Services™ Acquire:  Our model development service allows you to prebuild and test the performance of a new model before Experian data scientists complete the model. It's collaborative, and you can upload internal data through the web portal and make comments or suggestions. The service periodically retrains your model to increase its effectiveness. Ascend Intelligence Services™ Pulse:  Monitor, validate and challenge your existing models to ensure you're not missing out on potential improvements. The service includes a model health index and alerts, performance summary, automatic validations and stress-testing results. It can also automatically build challenger models and share the estimated lift and financial benefit of deployment. PowerCurve® Originations Essentials:  Cloud-based decision engine software that you can use to make automated decisions that are tailored to your goals and needs. A machine learning approach to credit risk and AI-driven decisioning can help improve outcomes for borrowers and increase financial inclusion while reducing your overall costs. With a trusted and experienced partner, you'll also be able to back up your decisions with customizable and regulatorily-compliant reports. Learn more about our credit decisioning solutions. Learn more When we refer to "Alternative Credit Data," this refers to the use of alternative data and its appropriate use in consumer credit lending decisions as regulated by the Fair Credit Reporting Act (FCRA). Hence, the term "Expanded FCRA Data" may also apply in this instance and both can be used interchangeably.1Experian (2024). Improving Your Credit Risk Machine Learning Model Deployment2Experian and Forrester Research (2023). Raising the AI Bar3Experian (2022). Driving Growth During Economic Uncertainty with AI/ML Strategies4Ibid5Experian (2020). Explainability ML and AI in Credit Decisioning

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. In February, economic growth and job creation outperformed economists’ expectations, likely giving confirmation to the Federal Reserve that it remains too early to begin cutting rates. Data highlights from this month’s report include: U.S. real GDP rose 3.3% in Q4 2023, driven by consumer spending and bringing the average annual 2023 growth to 2.5%, the same as the five-year average growth prior to the pandemic. The labor market maintained its strength, with 353,000 jobs added this month and unemployment holding at 3.7% for the third month in a row. Consumer sentiment rose 13% in January, following a 14% increase in December, as consumers are feeling some relief from cooling inflation. Check out our report for a deep dive into the rest of February’s data, including inflation, the latest Federal Reserve announcement, the housing market, and credit card balances. To have a holistic view of our current environment, we must understand our economic past, present, and future. Check out our annual chartbook for a comprehensive view of the past year and register for our upcoming Macroeconomic Forecasting webinar for a look at the year ahead. Download report Register for webinar For more economic trends and market insights, visit Experian Edge.

Our Econ to Action podcast series dives into the top economic trends and the implications of those trends in the market. In each episode, we explore the challenges different market segments are facing and how businesses in the segment are navigating the current economic climate. Listen to our host, Josee Farmer, Economic Analyst, discuss these topics with other Experian experts. In a special episode of Econ to Action to commemorate the start of the new year, Josee is joined by three market experts to discuss the 2024 forecast. The experts discuss the broader U.S. economic forecast, according to the Federal Reserve’s SEP (Summary of Economic Projections), as well as the forecasts for the mortgage, collections and national bank market segments. Shawn Rife, Client Executive, returns to Econ to Action with more collections insights, along with new guests Kendall Hellman, Senior Account Executive, Strategic Sales and Rob Rollo, Senior Account Executive, Strategic Mortgage Sales. Watch our first video episode and learn how the 2024 forecast will affect the market. Be sure to go back and catch up on previous episodes on our Econ to Action podcast hub and visit Experian Edge for our latest economic, credit and market insights.  

This article was updated on February 12, 2024. The Buy Now, Pay Later (BNPL) space has grown massively over the last few years. But with rapid growth comes an increased risk of fraud, making "Buy Now, Pay Never" a crucial fraud threat to watch out for in 2024 and beyond. What is BNPL? BNPL, a type of short-term financing, has been around for decades in different forms. It's attractive to consumers because it offers the option to split up a specific purchase into installments rather than paying the full total upfront. The modern form of BNPL typically offers four installments, with the first payment at the time of purchase, as well as 0% APR and no hidden fees. According to an Experian survey, consumers cited managing spending (34%), convenience (31%), and avoiding interest payments (23%) as main reasons for choosing BNPL. Participating retailers generally offer BNPL at point-of-sale, making it easy for customers to opt-in and get instantly approved. The customer then makes a down payment and pays off the installments from their preferred account. BNPL is on the rise The fintech and online-payment-driven world is seeing a rise in the popularity of BNPL. According to Experian research, 3 in 4 consumers have used BNPL in 2023, with 11% using BNPL weekly to make purchases. The interest in BNPL also spans generations — 36% of Gen Z, 43% of Millennials, 32% of Gen X, and 12% of Baby Boomers have used this payment method. The risks of BNPL While BNPL is a convenient, easy way for consumers to plan for their purchases, experts warn that with lax checkout and identity verification processes it is a target for digital fraud. Experian predicts an uptick in three primary risks for BNPL providers and their customers: identity theft, first-party fraud, and synthetic identity fraud. WATCH: Fraud and Identity Challenges for Fintechs Victims of identity theft can be hit with charges from BNPL providers for products they have never purchased. First-party and synthetic identity risks will emerge as a shopper's buying power grows and the temptation to abandon repayment increases. Fraudsters may use their own or fabricated identities to make purchases with no intent to repay. This leaves the BNPL provider at the risk of unrecoverable monetary losses and can impact the business' risk tolerance, causing them to narrow their lending band and miss out on properly verified consumers. An additional risk lies with fraudsters who may leverage account takeover to gain access to a legitimate user's account and payment information to make unauthorized purchases. READ: Payment Fraud Detection and Prevention: What You Need to Know Mitigating BNPL risks Luckily, there are predictive credit, identity verification, and fraud prevention tools available to help businesses minimize the risks associated with BNPL. Paired with the right data, these tools can give businesses a comprehensive view of consumer payments, including the number of outstanding BNPL loans, total BNPL loan amounts, and BNPL payment status, as well as helping to detect and apply the relevant treatment to different types of fraud. By accurately identifying customers and assessing risk in real-time, businesses can make confident lending and fraud prevention decisions. To learn more about how Experian is enabling the protection of consumer credit scores, better risk assessments, and more inclusive lending, visit us or request a call. And keep an eye out for additional in-depth explorations of our Future of Fraud Forecast. Learn more Future of Fraud Forecast

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.  As 2024 unfolds, the economy is beginning to shift from last year’s trends. Instead of focusing on rate hikes, we’re looking at the potential for rate cuts. Our labor market is beginning to ease, and inflation is moving closer to the Federal Reserve’s 2% mark. Each month’s data gives us a clearer picture of our economic trajectory and the Federal Reserve’s (Fed) policy moving forward, as well as new and direct implications on credit metrics. Data highlights from this month’s report include: The U.S. economy added 216,000 jobs in December, but after November and October levels were revised, three-month average job creation now sits below the pre-pandemic level. While there was no change in November, annual core inflation, which excludes the volatile food and energy components, cooled in December from 4.0% to 3.9%. Consumer sentiment rose 14% in December, reversing the past four monthly declines, driven by increased optimism toward the trajectory of inflation. Check out our report for a deep dive into the rest of this month’s data, including student loans, consumer spending, the housing market, and delinquencies. To have a holistic view of our current environment, we must understand our economic past, present, and future. Keep an eye out for this year’s chartbook for a comprehensive view of the past year and download our latest forecast for a view of what’s to come. Download report View forecast For more economic trends and market insights, visit Experian Edge.

This article was updated on October 31, 2023 In a series of articles, we talk about understanding the different types of fraud and how to solve for them. This article will explore first-party fraud and how it's similar to biting into a cookie you think is chocolate chip, only to find that it’s filled with raisins. The raisins in the cookie were hiding in plain sight, indistinguishable from chocolate chips without a closer look, much like first-party fraudsters. What is first-party fraud? First-party fraud refers to instances when an individual makes a promise of future repayments in exchange for goods or services without the intent to repay. The first-party fraudster might accomplish this by applying for a loan or credit card they won’t pay back or misrepresenting their financial situation to get a more favorable rate. First-party fraud sometimes presents via “mules” or consumers who are persuaded to use their own information to obtain credit or merchandise on behalf of a larger fraud ring. This type of fraud has become especially prevalent as more consumers are active online. Money mules constitute up to 0.3% of accounts at U.S. financial institutions, or an estimated $3 billion in fraudulent transfers. First-party fraud is often miscategorized as credit loss and written off as bad debt, which causes problems when businesses later try to determine how much they’ve lost to fraud versus credit risk, and then make future lending decisions. How does first-party fraud impact me? Firstly, there are often substantial losses associated with first-party fraud. An imperfect first-party fraud solution can also strain relationships with good customers and hinder growth. When lenders have to interpret actions and behavior to assess customers, there’s a lot of room for error and losses. Those same losses hinder growth when, as mentioned before, businesses anticipate credit losses that aren’t actually credit losses. This type of fraud isn’t a single-time event, and it doesn’t occur at just one point in the customer lifecycle. It occurs when good customers develop fraudulent intent, when new applicants who have positive history with other lenders have recently changed circumstances, or when seemingly good applicants have manipulated their identities to mask previous defaults. Finally, first-party fraud impacts how your organization categorizes and manages risk – and that’s something that touches every department. Solving the first-party fraud problem First-party fraud detection requires a change in how we think about the fraud problem. It starts with the ability to separate first- and third-party fraud to treat them differently. Because first-party fraud doesn’t have a victim, you can’t work with the person whose information was stolen to confirm the fraud. Instead, you’ll have to work implement a consistent monitoring system and make a determination internally when fraud is suspected. As we’ve already discussed, the fraud problem is complex. However with a partner like Experian, you can leverage the fraud risk management strategies required to perform a closer examination and the ability to differentiate between the types of fraud so you can determine the best course of action moving forward. Additionally, our robust fraud management solutions can be used for synthetic identity fraud and account takeover fraud prevention, which can help you minimize customer friction to improve and deepen your relationships while preventing fraud. Contact us if you’d like to learn more about how Experian is using our identity expertise, data, and analytics to improve identity resolution and detect and prevent all types of fraud. Contact us

This article was updated on August 24, 2023. The continuous shift to digital has made a tremendous impact on consumer preferences and behaviors, with 81% thinking more highly of brands that offer multiple digital touchpoints. As a result, major credit card issuers are making creative pivots to their credit marketing strategies, from amplifying digital features in their card positioning to promoting partnerships and incentives on digital channels. But as effective as it is to reach consumers where they most frequent, credit card marketing will need to be more customer-centric to truly captivate and motivate audiences to engage.  So, what does this innovative period of credit marketing mean for financial institutions? How can these institutions stand out in a competitive, ever-changing market?  To target and acquire the right consumers, here are three credit card marketing strategies financial institutions should consider:  Maximize share of voice through targeted approaches  About half of consumers say personalization is the most important aspect of their online experience. Because today’s consumers are now expecting to engage digitally with brands, it’s important for financial institutions to not only be seen and mentioned on the right digital channels, but to deliver content that will resonate with their specific audiences. To do this, lenders must leverage fresh, comprehensive data sets to gain a more holistic view of consumers. This way, they can create targeted, customer-centric prescreen campaigns, allowing for enhanced personalization and increased response rates.  Seek new opportunities to provide value to customers  77% of Gen Zers believe having an established credit history is important to being less financially dependent on their parents. Changes in consumer needs and lifestyles provide great opportunities to deliver value to customers. For example, younger consumers starting their credit journeys may look for brands that offer financial education or tools to help them build credit. Financial institutions that are open to pivoting their strategies to adapt to these needs and behaviors are those that will succeed in attracting new customers and maintaining long-lasting relationships with existing ones.  Amplify points of differentiation in their products and marketing  Before buying a product, consumers likely want to know more about the items they are purchasing and how they compare to different players in the market. To help set their products apart from other offerings, financial institutions should clearly define their product’s key differentiators and convey them in a personalized and compelling manner.  Enhance your credit card marketing campaigns  From identifying the right prospects to saturating your targeting criteria with data-rich insights, Experian offers credit marketing solutions to help you level up your campaigns and stand out from the competition. Learn more

This article was originally published on multifamilyinsiders.com One of the challenges currently facing the rental housing industry is the amount of lease application fraud. An Entrata study found a 111% increase in lease application fraud between 2019 and 2020. In the same study, 55% of surveyed apartment managers and rental operators said their properties experience fraudulent lease application attempts every few months, and 15% said their communities were subjected to multiple attempts each month. One-third of respondents described themselves as "very concerned" about application fraud. Just as alarming as the rise in attempts is the apparent likelihood of success. In the study, 65% of apartment managers said they are not confident in their current fraud prevention efforts. Some applicants can use a range of tools to commit fraud such as fake pay stubs, bank statements, employment records, and other falsified documents. Unfortunately, readily available computer technology makes it all too easy for applicants to produce these falsified documents. Tools to fight against fraud Apartment communities that rely on an overly manual screening process may find themselves at a disadvantage in the current landscape. Relying on associates to manually verify things like income and employment history can increase the risk of a deceitful applicant being successful. In addition, these processes can be extraordinarily time-consuming, which means leasing associates have less bandwidth for their many other important duties and responsibilities. Not to mention, the units stay unoccupied while these time-consuming verifications are being done manually. Among the general screening technologies that operators should consider: Automated verification of income, assets and employment — These solutions eliminate the need for operators to collect this kind of documentation from applicants. Furthermore, it eliminates the opportunity for applicants to supply falsified supporting documentation. Frictionless authentication — A multi-layered identity verification process for those applying for rental housing, frictionless authentication detects the subtle and not-so-subtle signs that an applicant is, to one degree or another, using a false identity. By highlighting discrepancies, the process assigns a “score” to quantify the likelihood that misrepresentation is taking place. Additional confirmation of the applicant’s identity can be completed using a one-time passcode (OTP) or knowledge-based authentication (KBA). This technology also uses device intelligence to recognize the risks associated with the physical devices (such as computers, tablets, and smartphones) that consumers use for online applications to identify potential imposters. In today's landscape, apartment owners and operators need to make sure they're protecting themselves against fraudulent applicants, who may not fulfill their financial obligations as outlined in their leases. By embracing the ever-growing array of advanced screening tools and technologies, owners and operators can achieve that protection and reduce their risk significantly — and save their associates time and energy.

As 2023 unfolds, rental housing owners and operators find themselves faced with a slightly different market than in the recent past. While rents are still high, rent growth has slowed somewhat, and the prospect of a cooler U.S. economy means more renters could be facing economic hardships in the months ahead. So, who is today's renter? In The State of the U.S. Rental Housing Market, a new report from Experian, we uncover that today’s renters are typically younger. According to our data derived from Experian RentBureau® and our analysis, 68.8% of today’s renters are either millennials (41.8%) or Gen Z (27%). Meanwhile, 17.3% are Gen X, 11.9% are baby boomers and only 2.2% are from the Silent Generation. Similarly, when you look at the renters who have a higher propensity to move — and thus need a new apartment or home to rent — they tend to skew younger. Our analysis shows that, of the renters who made two or more moves during the last two years, 43.2% were Gen Y (millennials). The younger Gen Y segment accounts for 25.2% of the frequent movers. As the population of renters has increased over the past decade, the concentration of growth appears to be among households earning $75,000 or more in annual income. About 7.6 million of these households were renters in 2009; by 10 years later, that figure had increased to 11.2 million. What is their financial status? Also, by some measurements, U.S. consumers — and, by extension, renters — improved their financial standing during the pandemic era. Credit scores rose as consumers used stimulus payments to pay down debt and save, but this trend is starting to normalize. The median conventional credit score rose above 700 in 2022, up from just above 680 in 2019. Still, according to Experian RentBureau, 63% of all renter households are low- to moderate-income earners, meaning they make less than 80% of the area median income. Furthermore, the average renter spends 38.6% of their income on rent. Households that spend more than 30% of their income on housing costs — including rent or mortgage payments, utilities and other fees — are considered “housing cost burdened” by the U.S. Department of Housing and Urban Development. For more insight and analysis of today’s rental-housing market, click here to download your free copy of The State of the U.S. Rental Housing Market report.

After a period of historic, double-digit rent growth and razor-thin vacancy rates, the rental housing market has shown some signs of softening in recent months. And economic uncertainty still looms. The potential of a downturn this year and the existing economic strains faced by large swaths of renters may impact many rental-housing owners and managers nervous about their ability to find renters who can fulfill their lease terms. In The State of the U.S. Rental Housing Market, a new report from Experian, our data scientists and analysts offer key insights into the U.S. housing market and its impact on renters. The analysis in this report is derived from synthesizing various data samples and sources, including Experian credit attributes and models as well as data from the U.S. Census Bureau and Experian RentBureau®. Experian RentBureau is the largest rental payment database and contains over 4.4 million transactions and more than 25 million renter profiles. This report yields three major takeaways: Soaring interest rates and a slowing mortgage sector over the last year have taken heat out of the homebuying market, leading to more renters remaining in the renter pool. Inflation and other economic strains continue to squeeze renters’ finances. As rent prices increase and negative payment activity becomes more frequent, rental-housing owners and operators are striving to grow without expanding default risk and need to find renters with the best chances of fulfilling the terms of their leases. Among the report’s other notable findings: The average renter spends 38.6% of their income on rent. Households that spend more than 30% of their income on housing costs — including rent or mortgage payments, utilities and other fees — are considered “housing cost burdened” by the U.S. Department of Housing and Urban Development. Experian data shows 28% of renters with negative payment activity in 2022 (negative payment activity is defined as having late charges, insufficient funds, write-offs or outstanding balances). The figure represented an increase of 5.7 percentage points from 2021 and 3.8 percentage points from 2020. Also of note, low-to-moderate income renters are twice as likely to have a negative payment activity compared to other renters. Rent-to-income ratios are highest in the West and the Northeast. Among all 50 states, the leaders are Washington D.C. (40.9%), California (39.7%), Washington state (35.6%), Utah (35.6%) and New York (35.3%). Keep pace with trends in future blog posts that will dive deeper into the current conditions affecting the rental housing market and renters. In the meantime, click here to download your free copy of The State of the U.S. Rental Housing Market Report in full.

Experian’s eighth annual identity and fraud report found that consumers continue to express concerns with online security, and while businesses are concerned with fraud, only half fully understand its impact – a problem we previously explored in last year’s global fraud report. In our latest report, we explore today’s evolving fraud landscape and influence on identity, the consumer experience, and business strategies. We surveyed more than 2,000 U.S. consumers and 200 U.S. businesses about their concerns, priorities, and investments for our 2023 Identity and Fraud Report. This year’s report dives into: Consumer concerns around identity theft, credit card fraud, online privacy, and scams such as phishing.Business allocation to fraud management solutions across industries.Consumer expectations for both security and their experience.The benefits of a layered solution that leverages identity resolution, identity management, multifactor authentication solutions, and more. To identify and treat each fraud type appropriately, you need a layered approach that keeps up with ever-changing fraud and applies the right friction at the right time using identity verification solutions, real-time fraud risk alerts, and enterprise orchestration. This method can reduce fraud risks and help provide a more streamlined, unified experience for your consumers. To learn more about our findings and how to implement an effective solution, download Experian’s 2023 Identity and Fraud Report. Download the report