Data & Analytics

A data-driven customer experience certainly has a nice ring, but can your organization deliver on the promise? What we're really getting at is whether you can provide convenience and personalization throughout the customer journey. Using data to personalize the customer journey About half of consumers say personalization is the most important aspect of their online experience. Forward-thinking lenders know this and are working to implement digital transformations, with 87 percent of business leaders stating that digital acceleration has made them more reliant on quality data and insights. For many organizations, lack of data isn't the issue — it's collecting, cleaning and organizing this data. This is especially difficult if your departments are siloed or if you're looking to incorporate external data. What's more, you would need the capabilities to analyze and execute the data if you want to gain meaningful insights and results. LEARN: Infographic: Automated Loan Underwriting Journey Taking a closer look at two important parts of the customer journey, here's how the right data can help you deliver an exceptional user experience. Prescreening To grow your business, you want to identify creditworthy consumers who are likely to respond to your credit offers. Conversely, it's important to avoid engaging consumers who aren't seeking credit or may not meet your credit criteria. Some of the external data points you can incorporate into a digital prescreening strategy are: Core demographics: Identify your best customers based on core demographics, such as location, marital status, family size, education and household income. Lifestyle and financial preferences: Understand how consumers spend their time and money. Home and auto loan use: Gain insight into whether someone rents or owns a home, or if they'll likely buy a new or used vehicle in the upcoming months. Optimized credit marketing strategies can also use standard (and custom) attributes and scores, enabling you to segment your list and create more personalized offers. And by combining credit and marketing data, you can gain a more complete picture of consumers to better understand their preferred channels and meet them where they are. CASE STUDY: Clear Mountain Bank used Digital Prescreen with Micronotes to extend pre-approved offers to consumers who met their predetermined criteria. The refinance marketing campaign generated over $1 million in incremental loans in just two months and saved customers an average of $1,615. Originations Once your precise targeting strategy drives qualified consumers to your application, your data-driven experience can offer a low-friction and highly automated originations process. Alternative credit data: Using traditional and alternative credit data* (or expanded FCRA-regulated data), including consumer-permissioned data, allows you to expand your lending universe, offer more favorable terms to a wider pool of applicants and automate approvals without taking on additional risk. Behavioral and device data: Leveraging behavioral and device data, along with database verifications, enables you to passively authenticate applicants and minimize friction. Linked and digital applications: Offering a fully digital and intuitive experience will appeal to many consumers. In fact, 81 percent of consumers think more highly of brands after a positive digital experience that included multiple touchpoints. And if you automate verifications and prefill applications, you can further create a seamless customer experience. READ: White paper: Getting AI-driven decisioning right in financial services Personalization depends on persistent identification The vast majority (91 percent) of businesses think that improving their digital customer journey is very important. And rightly so: By personalizing digital interactions, financial institutions can identify the right prospects, develop better-targeted marketing campaigns and stay competitive in a crowded market. DOWNLOAD: A 5-Step Checklist for Identifying Credit-Active Prospect To do this, you need an identity management platform that enables you to create a single view of your customer based on data streams from multiple sources and platforms. From marketing to account management, you can use this persistent identity to inform your decisions. This way, you can ensure you're delivering relevant interactions and offers to consumers no matter where they are. WATCH: Webinar: Omnichannel Marketing - Think Outside the Mailbox Personalization offers a win-win Although they want personalization, only 33 percent of consumers have high confidence in a business' ability to recognize them repeatedly.4 To meet consumer expectations and remain competitive, you must deliver digital experiences that are relevant, seamless, and cohesive. Experian Consumer View helps you make a good first impression with consumer insights based on credit bureau and modeled data. Enrich your internal data, and use segmentation solutions to further refine your target population and create offers that resonate and appeal. You can then quickly deliver customized and highly targeted campaigns across 190 media destinations. From there, the Experian PowerCurve® Originations Essentials, an automated decisioning engine, can incorporate multiple external and internal data sources to optimize your strategy. *Disclaimer: 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. Hence, the term “Expanded FCRA Data" may also apply in this instance and both can be used interchangeably.

Many organizations commit to diversity, equity, and inclusion (DEI) policies and practices to build a more diverse and just workplace. Organizations that  live by these values ensure they're reflected in the products and services they offer, and in how they attract and interact with customers. For financial institutions, there could be a direct link between their DEI efforts and financial inclusion, which can open up growth opportunities. Defining DEI and financial inclusion DEI and financial inclusion aren't new concepts, but it's still important to understand how organizations are using these terms and how you might define a successful outcome. What is DEI? DEI policies help promote and support individuals and groups regardless of their backgrounds or differences. In the Experian 2022 Diversity, Equity and Inclusion Report, we define these terms more specifically as: Diversity: The presence of differences that may include thought, style, sexual orientation, gender identity/expression, race, ethnicity, dis(ability), culture, and experience. Equity: Promoting justice, impartiality, and fairness within the procedures, processes, and distribution of resources by institutions or systems. Inclusion: An outcome to ensure those who self-identify as diverse feel and are welcomed. You meet your inclusion outcomes when you, your institution, and your programs are inviting to all. We also recognize the importance of belonging, or “a sense of fitting in or feeling you are an important member of a group." A company's DEI strategy might include internal efforts, such as implementing hiring and promotion practices to create a more diverse workforce, and supporting employee resource groups to foster a more inclusive culture. Companies can also set specific and trackable goals, such as Experian's commitment to increase its representation of women in senior leadership roles to 40 percent by 2024.1 But DEI efforts can expand beyond internal workforce metrics. For example, you might review how the products or services you sell — and the messaging around those offerings — affect different groups. Or consider whether the vendors, suppliers, nonprofits, communities, and customers you work with reflect your DEI strategy. What is financial inclusion? Financial inclusion is less specific to a company or organization. Instead, it describes the strategic approach and efforts that allow people to affordably and readily access financial products, services, and systems. Financial institutions can promote financial inclusion in different ways. A bank can change the requirements or fees for one of its accounts to better align with the needs of people who are currently unbanked. Or it can offer a solution to help people who are credit invisible or unscoreable by conventional scoring models establish their credit files for the first time. For example, Mission Asset Fund, a San Francisco-based nonprofit, organizes credit-building lending circles that have historical roots in savings programs from around the world. Participants can use them to build credit without paying any interest or fees. In particular, the organization focuses on helping immigrants establish and improve their credit in the U.S. Financial institutions are also using non-traditional data scoring to lend to applicants that conventional scoring models can't score. By incorporating alternative credit data1 (also known as expanded FCRA-regulated data) into their marketing and underwriting, lenders can expand their lending universe without taking on additional risk. READ MORE: Experian's Improving Financial Health Report 2022 has many examples of internal products and external partnerships that help promote financial literacy and inclusion. DEI and financial inclusion can complement each other Although DEI and financial inclusion involve different strategies, there's an undeniable connection that should ultimately be tied to a business's overall goal and mission. The groups who are historically underrepresented and underpaid in the workforce also tend to be marginalized by the established financial system. For example, on average, Black and Hispanic/Latino workers earn 76 percent and 73 percent, respectively, as much as white workers.2 And 27 percent of Black and 26 percent of Hispanic/Latino consumers are either credit invisible or unscoreable, compared to only 16 percent of white consumers.3 Financial institutions that work to address the inequities within their organizations and promote financial inclusion may find that these efforts complement each other. During a webinar in 2022 discussing how financial growth opportunities can also benefit underserved communities, Experian asked participants what they thought was the greatest business advantage of executing financial inclusion in their financial institution or business. The majority of respondents (78 percent) chose building trust and retention with customers and communities — undoubtedly an important outcome. But the second most popular choice (14 percent) was enhancing their brand and commitment to DEI, highlighting how these efforts can be interconnected.4 By building a more diverse workforce, organizations can also bring on talent that better relate to and understand consumers who weren't previously part of the company's target market. If the company culture supports a range of ideas, this can unlock new ways to propel the business forward. In turn, employees can be more engaged and excited about their work. Find partners that can help you succeed Setting measurable outcomes for your DEI and financial inclusion efforts and tracking your progress can be an important part of implementing successful programs. But you can also leverage partnerships to further define and achieve your goals. Experian launched Inclusion ForwardTM with these partnerships in mind. Building on our commitment to DEI and financial inclusion, we offer various tools to help consumers build and understand their credit and to help financial institutions reach underserved communities. Products like Experian GoTM and Experian BoostTM help consumers establish their credit file and add positive utility, rent, and streaming service payments to their Experian credit report. Lenders can benefit from access to various non-traditional credit data and expanded FCRA-regulated scoring models, including Experian's Lift PremiumTM, which can score 96 percent of U.S. adults. Whether you've established your strategy and need help with implementation or are at the starting stages, Experian can help you promote DEI and enhance your financial inclusion efforts. Learn more about driving financial inclusion to bring change  1Experian (2022). 2022 Diversity, Equity and Inclusion Report 2U.S. Department of Labor (N/A). Earnings Disparities by Race and Ethnicity 3Oliver Wyman (2022). Financial Inclusion and Access to Credit 4Experian (2022). Three Ways to Uncover Financial Growth Opportunities that Benefit Underserved Communities.

Machine learning (ML) is a powerful tool that can consume vast amounts of data to uncover patterns, learn from past behaviors, and predict future outcomes. By leveraging ML-powered credit risk models, lenders can better determine the likelihood that a consumer will default on a loan or credit obligation, allowing them to score applicants more accurately. When applied to credit decisioning, lenders can achieve a 25 percent reduction in exposure to risky customers and a 35 percent decrease in non-performing loans.1 While ML-driven models enable lenders to target the right audience and control credit losses, many organizations face challenges in developing and deploying these models. Some still rely on traditional lending models with limitations preventing them from making fast and accurate decisions, including slow reaction times, fewer data sources, and less predictive performance. With a trusted and experienced partner, financial institutions can create and deploy highly predictive ML models that optimize their credit decisioning. Case study: Increase customer acquisition with improved predictive performance Looking to meet growth goals without increasing risk, a consumer goods retailer sought out a modern and flexible solution that could help expand its finance product options. This meant replacing existing ML models with a custom model that offers greater transparency and predictive power. The retailer partnered with Experian to develop a transparent and explainable ML model. Based on the model’s improved predictive performance, transparency, and ability to derive adverse action reasons for declines, the retailer increased sales and application approval rates while reducing credit risk. Read the case study Learn about our custom modeling capabilities 1 Experian (2020). The Art of Decisioning in Uncertain Times

Recent statistics certainly illustrate why many renters are feeling anxious lately. More than 40% of renter households in the U.S. — that’s 19 million households — spent more than 30% of their total income on housing costs during the 2017–2021 period, according to the U.S. Census Bureau’s new American Community Survey (ACS). 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. Digging a little deeper, nearly 8% of the nation’s 3,143 counties had a median housing cost ratio for renters above 30% during the five-year period, according to ACS, and nearly a third of all U.S. renters lived in these counties. Unsurprisingly, 60% of Americans say they’re “very concerned” about the cost of housing, according to the Pew Research Center. The financial plight of renters today underscores the importance of incorporating renter payment history into screening efforts. It also indicates why reporting positive rent payments to credit bureaus can be such a powerful amenity. Rental data: The key to optimizing the screening process Simply put, a screening process that includes an applicant’s rental payment history provides a more comprehensive understanding of their risk profile and likelihood of paying rent on time and in full. That’s especially critical in an environment when paying rent can be something of a financial burden for many. Wouldn’t an apartment manager want to make a leasing decision by taking into consideration every possible bit of relevant data, especially the most relevant data available — rental payment history? Credit scores are often at the heart of an operator’s screening process. A credit score can give a very general sense of the risk posed by a prospect, but it doesn't provide crystal-clear insight into the likelihood of an applicant paying their rent on time and in full. Even people who are financially responsible and diligent about paying their rent can find themselves with less-than-ideal credit scores. Maybe they were injured in an accident, came down with a serious illness or lost their job, and then suffered a host of financial consequences that harmed their credit score. It can't be assumed people who have been through these situations won't pay their rent on time. At the same time, especially given the burden rent payments pose for many renters, reporting positive payments to credit bureaus can serve as an effective way to attract residents. Unfortunately, unlike homeowners, apartment residents traditionally have not seen a positive impact on their credit reports for making their rent payments on time and in full, even though these payments can very large and usually make up their largest monthly expense. Rental reporting According to the Credit Builders Alliance (CBA), renters are seven times more likely to be credit invisible — meaning they lack enough credit history to generate a credit score — when compared to homeowners. But by reporting their on-time rent payments to credit bureaus, apartment communities can help renters build their credit histories, which can make it easier for them to do things such as secure a car loan or credit card — and to do so at favorable interest rates. Additionally, rent reporting gives residents a strong incentive to pay their rent on time and in full. And it can provide apartment communities with a competitive advantage since this financial amenity is not widespread throughout the rental-housing industry. The data is clear: this is a challenging time for many renters. But by making rental payment histories part of their screening, operators can minimize their risk. And by reporting positive rental payments, they can attract residents and help them build a better financial future. To learn more about Experian’s largest rental payment database and how to start reporting with us, visit us online. Experian RentBureau™

As economic conditions shift and consumer behavior fluctuates, first- and third-party debt collectors must adapt to continually maintain effective debt collection strategies. In this article, we explore collections best practices that can empower collectors to improve operational efficiency, better prioritize accounts and enhance customer interactions, all while ensuring compliance with changing regulations. Best practices for improving your collection efforts 1. Implement a data-driven collection strategy Many collectors are already using artificial intelligence (AI) and machine learning (ML) to gain a more complete view of their consumers, segment accounts and create data-driven prioritization strategies. The data-backed approach is clearly a trend that's going to stick. But access to better (i.e., more robust and hygienic) data and debt collection analytics will distinguish the top performers.You can use traditional credit data, alternative credit data, third-party data and advanced analytics to more precisely segment consumers based on their behavior and financial situation — and to determine their propensity to pay. Supplementary data sources can also help with verifying consumers' current contact information and improving your right-party contact rates.Cloud-based platforms and access to various data sources give debt collectors real-time insights. Quickly identifying consumers who may be stretched thin or trending in the wrong direction allows you to proactively reach out with an appropriate pre-collection plan.And for consumers who are already delinquent, the more precise segmentation and tracking can help you determine the best contact channels, times and personalized treatments. For instance, you could optimize outreach based on specific account details (rather than general time-based metrics) and offer payment plans that the customer can likely afford. 2. Use technology to maximize your resources Data-driven prioritization strategies can help you determine who to contact, how to contact them and the treatment options you offer. But you may need to invest in technology to efficiently execute these findings. Although budgets may be limited, the investment in debt recovery tools can be important for handling rising account volumes without increasing headcount. Some opportunities include: Automate processes and outreach: Look for opportunities to automate tasks, particularly monotonous tasks, to reduce errors and free up your agents' time to focus on more valuable work. You could also use automated messages, texts, chatbots and virtual negotiators with consumers who will likely respond well to these types of outreaches. Establish self-service platforms: Create self-service platforms that give consumers the ability to choose how and when to make a payment. This can be especially effective when you can accurately segment consumers based on the likelihood that they'll self-cure and then automate your outreach to that segment. Keep consumer data up to date: Have systems in place that will automatically verify and update consumers' contact information, preferences and previous collection attempts. Reprioritize old accounts based on significant changes: Tools like Experian's Collection Triggers℠ allow you to monitor accounts and automatically get alerted when consumers experience a significant change, such as a new job, that could prompt you to put their account back into your queue. 3. Prioritize customer experience In some ways, debt collectors today often work like marketers by embracing digital debt collection and a customer-first philosophy to improve the consumers' experiences. Your investment in technology goes together with this approach. You'll be able to better predict and track consumers' preferences and offer self-cure options for people who don't want to speak directly with an agent. You also may need to review your regular onboarding and training programs. Teaching your call center agents to use empathy-based communication techniques and work as a partner with consumers to find a viable payment plan can take time. But the approach can help you build trust and improve customer lifetime value. 4. Continue to carefully monitor regulatory requirements Keeping up with regulatory requirements is a perennial necessity for collectors, and you'll need to consider how to stay compliant while adding new communications channels and storing consumer data. For example, make sure there are “clear and conspicuous" opt-out notices in your electronic communications and that your systems can track which channels consumers opt out of and their electronic addresses.1In some cases, the customer-first approach may help minimize regulatory risks, as you'll be training agents to listen to consumers and act in their interest. Similarly, data-driven optimizations can help you increase collections with fewer contacts.WATCH: Explore credit union collection trends and successful account management strategies. Partner with a top provider to achieve success Experian has partnered with many debt collectors to help them overcome challenges and increase recovery rates. There are multiple solutions available that you can use to improve your workflow: TrueTrace™ and TrueTrace Live™: Leverage access to the consumer credit database that has information on over 245 million consumers, and additional alternative databases, to maintain current addresses and phone numbers. PriorityScore for Collections ℠ Know which accounts you should focus on with over 60 industry-specific debt recovery scores. You can choose to prioritize based on likelihood to pay or expected recovery amount. Collection Triggers℠: Daily customer monitoring can tell you when it's time to approach a consumer based on life events, such as new employment or recent credit inquiries. Phone Number ID™ with Contact Monitor™: Increase right-party contact rates and avoid Telephone Consumer Protection Act (TCPA) violations with real-time phone ownership and type monitoring from over 5,000 local exchange carriers. Experian's PowerCurve® Collections and Experian® Optimize solutions also make AI-driven automated systems accessible to debt collectors that previously couldn't afford such advanced capabilities. Building on Experian's access to many sources of credit and non-credit data, these solutions can help you design debt collection strategies, predict consumer behavior and automate decisioning.Learn more about Experian's debt collection solutions. Learn more This article includes content created by an AI language model and is intended to provide general information.

"Out with the old and in with the new" is often used when talking about a fresh start or change we make in life, such as getting a new job, breaking bad habits or making room in our closets for a new wardrobe. But the saying doesn't exactly hold true in terms of business growth. While acquiring new customers is critical, increasing customer retention rates by just 5% can increase profits by up to 95%.1 So, what can your organization do to improve customer retention? Here are three quick tips: Stay informed Keeping up with your customers’ changing interests, behaviors and life events enables you to identify retention opportunities and create personalized credit marketing campaigns. Are they new homeowners? Or likely to purchase a vehicle within the next five months? With a comprehensive consumer database, like Experian’s ConsumerView®, you can gain granular insights into who your customers are, what they do and even what they will potentially do. To further stay informed, you can also leverage Retention TriggersSM, which alert you of your customers changing credit needs, including when they shop for new credit, open a new trade or list their property. This way, you can respond with immediate and relevant retention offers. Be more than a business – be human Gen Z's spending power is projected to reach $12 trillion by 2030, and with 67% looking for a trusted source of personal finance information,2 financial institutions have an opportunity to build lifetime loyalty now by serving as their trusted financial partners and advisors. To do this, you can offer credit education tools and programs that empower your Gen Z customers to make smarter financial decisions. By providing them with educational resources, your younger customers will learn how to strengthen their financial profiles while continuing to trust and lean on your organization for their credit needs. Think outside the mailbox While direct mail is still an effective way to reach consumers, forward-thinking lenders are now also meeting their customers online. To ensure you’re getting in front of your customers where they spend most of their time, consider leveraging digital channels, such as email or mobile applications, when presenting and re-presenting credit offers. This is important as companies with omnichannel customer engagement strategies retain on average 89% of their customers compared to 33% of retention rates for companies with weak omnichannel strategies. Importance of customer retention Rather than centering most of your growth initiatives around customer acquisition, your organization should focus on holding on to your most profitable customers. To learn more about how your organization can develop an effective customer retention strategy, explore our marketing solutions. Increase customer retention today 1How investing in cardholder retention drives portfolio growth, Visa. 2Experian survey, 2023.

Believe it or not, 2023 is underway, and the new year could prove to be a challenging one for apartment operators in certain ways. In 2021 and into the beginning of 2022, demand for apartment rentals approached record levels, which shrunk vacancy rates and increased monthly rents. The rest of the year remained stagnant while other regions saw some decline, but inflation and other economic factors have many apartment communities confronted with labor shortages, and other challenges which can certainly make leasing and operating properties difficult. Against that backdrop, here are some of the technologies and solutions operators should consider for optimizing their success and efficiencies in 2023 and beyond. Tools that allow prospective residents to have a fully digital and contactless leasing experience — During the pandemic, many operators rushed to implement virtual tours, onsite self-guided tours and other solutions that allowed prospects to apply for and finalize their leases remotely. Prospective renters have undoubtedly grown fond of navigating the leasing process from their homes and taking self-guided tours when onsite, and the demand for digital solutions will surely continue even after COVID distancing is no longer a factor. Therefore, apartment owners and operators should think of these capabilities as long-term investments and always seek ways to optimize the digital leasing experience they provide. Along those lines, forward-thinking operators are employing solutions that allow them to embed credit functionality into their websites and mobile apps using modern, RESTful APIs like the Experian ConnectSM API. Not only does it enhance the information included in a lease application with credit report data, but it also allows prospective renters to easily apply for more than one property at once, enhancing their experience at the same time. Automated lease application form fill — By using information entered by a lease applicant (such as first name, last name, postal code and the last four digits of a Social Security number), this technology uses information from credit files to automatically fill other data fields in a lease application. This tool reduces the effort required by prospective renters to complete the application process, resulting in a better user experience, faster completions, greater accuracy and reduced application abandonment. Automated verification of income, assets, and employment — These solutions eliminate the need for associates to manually verify these components of a lease application. Manual verification is both time-consuming and prone to human error. In addition, automated tools eliminate the opportunity for applicants to supply falsified supporting documentation. The best part about verification is the variety of options available; leasing managers can pick and choose verification options that meet their needs. Renter Risk Score™ and custom-built scores and models applying RentBureau data — These options offer a score designed expressly to predict the likelihood that an applicant will pay rent. Renter risk score can be purchased with preset score logic, or for high-volume decisions, a model can be built calibrated for your specific leasing decisioning needs. A rental payment history report — The RentBureau Consumer Profile tool can provide detailed insight into a lease applicant's history of meeting their lease obligations, which is invaluable information during the lease application process. Having a tool to report rental payment histories to credit bureaus can be a powerful financial amenity. By reporting these payments, operators can help residents build credit histories and improve financial well-being. Such an amenity can attract and retain residents and provide them with a powerful incentive to pay rent on time and in full. In the end, tools that seek to manage risk and create improved experiences for prospective renters have a multitude of benefits. They create meaningful efficiencies for onsite staff by greatly reducing the time, resources and paperwork required to process applications and verify applicant information. This gives overextended associates more time to handle their many other responsibilities. Beyond just efficiency savings, these technologies and solutions also can help operators avoid the complications and loss of income that result from evictions. In fact, the National Association of Realtors estimates that average eviction costs $7,685. Managing risk and providing the best possible customer experience should always be top of mind for rental housing operators. And with the solutions outlined above, they can effectively accomplish those goals in 2023 and beyond.

Putting customers at the center of your credit marketing strategy is key to achieving higher response rates and building long-term relationships. To do this, financial institutions need fresh and accurate consumer data to inform their decisions. Atlas Credit was looking to achieve higher response rates on its credit marketing campaigns by engaging consumers with timely and personalized offers. The company implemented Experian’s Ascend Marketing, a customer marketing and acquisition engine that provides marketers with accurate and comprehensive consumer credit data to build and deploy intelligent marketing campaigns. With deeper insights into their consumers, Atlas Credit created timely and customized credit offers, resulting in a 185% increase in loan originations within the first year of implementation. Additionally, the company was able to effectively manage and monitor its targeting strategies in one place, leading to improved operational efficiency and lower acquisition costs. To learn more about creating better-targeted marketing campaigns and enhancing your strategies, read the full case study. Download the case study Learn more

For a credit prescreen marketing campaign to be successful, financial institutions must first define their target audience. But just because you’ve identified your ideal customers, it doesn’t mean that every individual within that group has the same needs, interests or behaviors. As such, you’ll need to use data-driven customer segmentation to create messages and offers that truly resonate. Customer segmentation example Customer segmentation is the practice of dividing your target audience into smaller sub-groups based on shared characteristics, behaviors or preferences. This allows you to develop highly targeted marketing campaigns and engage with individual groups in more relevant and meaningful ways. What role does data play in customer segmentation? When it comes to segmenting customers, there isn’t a one-size-fits-all approach that works perfectly for all campaigns and markets. However, regardless of the campaign, you’ll need accurate and relevant data to inform your segmenting strategy. Let’s walk through a customer segmentation example. Say you want to launch a credit marketing campaign that targets creditworthy consumers in the market for a new mortgage. Some of the most influential data points to consider when segmenting include: Demographics Demographic data allows you to get to know your customers as individuals in terms of age, gender, education, occupation and marital status. If you want to create a segment that consists of only middle-aged consumers, leveraging demographic data makes it easier to identify these individuals, refine your messaging and predict their future buying behaviors. Life stage Life event data, such as new parents and new homeowners, helps you connect with consumers who have experienced a major life event. Because you’re targeting consumers in the market for a new mortgage, using fresh and accurate life stage data can help you create an engaging, event-based marketing campaign relevant to their timeline. Financial Financial data segments go beyond income and estimate the way consumers spend their money. With deeper insights into customers’ financial behaviors, you can more accurately assess creditworthiness and make smarter lending decisions. Transactional Transactional data segments group your customers according to their unique buying habits. By getting to know why they purchase your products or their frequency of spend, you can gain a better understanding of who your most engaged customers are, segment further and find opportunities for cross-sell and upsell. Why is data-driven customer segmentation critical for your business? With data-driven customer segmentation, you can develop relevant marketing campaigns and messages that speak to specific audiences, enabling you to demonstrate your value propositions more clearly and deliver personalized customer experiences. Additionally, because customer segmentation enables you to tailor your marketing efforts to those most likely to respond, you can achieve higher conversions while cutting down on marketing spend and resources. Ready to get started? While data-driven customer segmentation may seem overwhelming, Experian can help fill your marketing gaps with custom-based data, audiences and solutions. Armed with a better understanding of your consumers’ patterns and journeys, you can start targeting them more effectively. Create highly targeted credit marketing campaigns

From chatbots to image generators, artificial intelligence (AI) has captured consumers' attention and spurred joy — and sometimes a little fear. It's not too different in the business world. There are amazing opportunities and lenders are increasingly turning to AI-driven lending decision engines and processes. But there are also open questions about how AI can work within existing regulatory requirements, how new regulations will impact its use and how to implement advanced analytics in a way that increases equitable inclusion rather than further embedding disparities. How are lenders using AI today? Many financial institutions have implemented — or at least tested — AI-driven tools throughout the customer lifecycle to: Target the right consumers: With tools like Ascend Intelligence ServicesTM Target (AIS Target), lenders can better identify consumers who match their credit criteria and send right-sized offers, which enables them to maximize their acceptance rates. Detect and prevent fraud: Fraud detection tools have used AI and machine learning techniques to detect and prevent fraud for years. These systems may be even more important as new fraud risks emerge, from tried-and-true methods to generative AI (GenAI) fraud. Assess creditworthiness: ML-based models can incorporate a range of internal and external data points to more precisely evaluate creditworthiness. When combined with traditional and alternative credit data*, some lenders can even see a Gini uplift of 60 to 70 percent compared to a traditional credit risk model. Manage portfolios: Lenders can also use a more complete picture of their current customers to make better decisions. For example, AI-driven models can help lenders set initial credit limits and suggest when a change could help them increase wallet share or reduce risk. Lenders can also use AI to help determine which up- and cross-selling offers to present and when (and how) to reach out. Improve collections: Models can be built to ease debt collection processes, such as choosing where to assign accounts, which accounts to prioritize and how to contact the consumer. Additionally, businesses can implement AI-powered tools to increase their organizations' productivity and agility. GenAI solutions like Experian Assistant accelerate the modeling lifecycle by providing immediate responses to questions, enhancing model transparency and parsing through multiple model iterations quickly, resulting in streamlined workflows, improved data visibility and reduced expenses. WATCH: Explore best practices for building, fine-tuning and deploying robust machine learning models for credit risk. The benefits of AI in lending Although lenders can use machine learning models in many ways, the primary drivers for adoption in underwriting include: Improving credit risk assessment Faster development and deployment cycles for new or recalibrated models Unlocking the possibilities within large datasets Keeping up with competing lenders Some of the use cases for machine learning solutions have a direct impact on the bottom line — improving credit risk assessment can decrease charge-offs. Others are less direct but still meaningful. For instance, machine learning models might increase efficiency and allow further automation. This takes the pressure off your underwriting team, even when application volume is extremely high, and results in faster decisions for applicants, which can improve your customer experience. Incorporating large data sets into their decisions also allows lenders to expand their lending universe without taking on additional risk. For example, they may now be able to offer risk-appropriate credit lines to consumers that traditional scoring models can't score. And machine learning solutions can increase customer lifetime value when they're incorporated throughout the customer lifecycle by stopping fraud, improving retention, increasing up- or cross-selling and streamlining collections. Hurdles to adoption of machine learning in lending There are clear benefits and interest in machine learning and analytics, but adoption can be difficult, especially within credit underwriting. A recent Forrester Consulting study commissioned by Experian found that the top pain points for technology decision makers in financial services were reported to be automation and availability of data. Explainability comes down to transparency and trust. Financial institutions have to trust that machine learning models will continue to outperform traditional models to make them a worthwhile investment. The models also have to be transparent and explainable for financial institutions to meet regulatory fair lending requirements. A lack of resources and expertise could hinder model development and deployment. It can take a long time to build and deploy a custom model, and there's a lot of overhead to cover during the process. Large lenders might have in-house credit modeling teams that can take on the workload, but they also face barriers when integrating new models into legacy systems. Small- and mid-sized institutions may be more nimble, but they rarely have the in-house expertise to build or deploy models on their own. The models also have to be trained on appropriate data sets. Similar to model building and deployment, organizations might not have the human or financial resources to clean and organize internal data. And although vendors offer access to a lot of external data, sometimes sorting through and using the data requires a large commitment. How Experian is shaping the future of AI in lending Lenders are finding new ways to use AI throughout the customer lifecycle and with varying types of financial products. However, while the cost to create custom machine learning models is dropping, the complexities and unknowns are still too great for some lenders to manage. But that's changing. Experian built the Ascend Intelligence Services™ to help smaller and mid-market lenders access the most advanced analytics tools. The managed service platform can significantly reduce the cost and deployment time for lenders who want to incorporate AI-driven strategies and machine learning models into their lending process. The end-to-end managed analytics service gives lenders access to Experian's vast data sets and can incorporate internal data to build and seamlessly deploy custom machine learning models. The platform can also continually monitor and retrain models to increase lift, and there's no “black box" to obscure how the model works. Everything is fully explainable, and the platform bakes regulatory constraints into the data curation and model development to ensure lenders stay compliant. 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.

The only thing constant is change. And as 2022 wraps up and businesses and consumers look toward 2023, the need for insights and data is at an all-time high to help forge the path ahead. With recent slowing economic growth, and uncertain macroeconomic and geopolitical climates, leading organizations are turning to credit, market, and economic trends, to help shape and inform future strategies. The challenge? With so many sources of information, it can be overwhelming to determine which information is relevant.  Experian Edge, our new thought leadership hub, compiles proprietary Experian data, and economic, credit and market trends in a single, easy-to-consume place. Covering the automotive, financial services, healthcare, retail and small business sectors, Experian Edge helps businesses navigate tomorrow with today’s insights.   Featured Publication: 2022 Experian Edge Chartbook  The data stories told during 2022 - particularly credit and economic trends - run the full gamut. From economic growth and the labor market, to consumer health and inflation, there is no shortage of insights to glean. The inaugural 2022 Experian Edge Chartbook compiles those key insights giving a comprehensive look at economic and credit trends and what they could mean for 2023. Download 2022 Experian Edge Chartbook Want more insights? Examples of what else you’ll find on Experian Edge include:  State of the Automotive Finance Market Report: Exclusive quarterly report on the latest trends and analysis of the U.S. automotive finance market. State of Alternative Credit Data Report: A deep dive into the uses of alternative data in consumer and small business lending.  State of Claims: 200 executive healthcare professionals shed light on the current claims environment.  Holiday Retail Guide 2022: Learn what types of behaviors you can expect to see from consumers this holiday shopping season. Beyond the Trends Report: Quarterly insights and commentary on economic conditions and future small business performance. Visit and bookmark Experian Edge for the latest intel you need to propel your business forward.  Visit Experian Edge

Financial institutions have gone through a whirlwind in the last few years, with the pandemic forcing many to undergo digital transformations. More recently, rising interest rates and economic uncertainty are leading to a pullback, highlighting the need for lenders to level up their marketing strategies to win new customers. To get started, here are a few key trends to look out for in the new year and fresh marketing ideas for lenders. Challenges and consumers expectations in 2023 It might be cliche to mention the impact that the pandemic had on digital transformations — but that doesn't make it any less true. Consumers now expect a straightforward online experience. And while they may be willing to endure a slightly more manual process for certain purchases in their life, that's not always necessary. Lenders are investing in front-end platforms and behind-the-scenes technology to offer borrowers faster and more intuitive services. For example, A McKinsey report from December 2021 highlighted the growth in nonbank mortgage lenders. It suggested nonbank lenders could hold onto and may continue taking market share as these tech-focused lenders create convenient, fast and transparent processes for borrowers.2 Marketers can take these new expectations to heart when discussing their products and services. To the extent you have one in place, highlight the digital experience that you can offer borrowers throughout the application, verifications, closing and loan servicing. You can also try to show rather than tell with interactive online content and videos. Build a data-driven mortgage lending marketing strategy The McKinsey report also highlighted a trend in major bank and nonbank lenders investing in proprietary and third-party technology and data to improve the customer experience.2 Marketers can similarly turn to a data-driven credit marketing strategy to help navigate shifting lending environments. Segment prospects with multidimensional data Successful marketers can incorporate the latest technological and multidimensional data sources to find, track and reach high-value prospects. By combining traditional credit data with marketing data and Fair Credit Report Act-compliant alternative credit data* (or expanded FCRA-regulated data), you can increase the likelihood of connecting with consumers who meet your credit criteria and will likely respond. For example, Experian's mortgage-specific In the Market Models predict a consumer's propensity to open a new mortgage within a one to four-month period based on various inputs, including trended credit data and Premier Attributes. You can use these propensity models as part of your prescreen criteria, to cross-sell current customers and to help retain customers who might be considering a new lender. But propensity models are only part of the equation, especially when you're trying to extend your marketing budget with hyper-segmented campaigns. Incorporating your internal CRM data and non-FCRA data can help you further distinguish look-alike populations and help you customize your messaging. LEARN MORE: Use this checklist to find and fix gaps in your prospecting strategy Maintain a single view of your borrowers An identity management platform can give you a single view of a consumer as they move through the customer journey. The persistent identity can also help you consistently reach consumers in a post-cookie world and contact them using their preferred channel. You can add to the persistent identity as you learn more about your prospects. However, you need to maintain data accuracy and integrity if you want to get a good ROI. Use triggers to guide your outreach You can also use data-backed credit triggers to implement your marketing plan. Experian's Prospect Triggers actively monitors a nationwide database to identify credit-active consumers who have new tradelines, inquiries or a loan nearing term. Lenders using Prospect Triggers can receive real-time or periodic updates and customize the results based on their screening strategy and criteria, such as score ranges and attributes. They can then make firm credit offers to the prospects who are most likely to respond, which can improve cross-selling opportunities along with originations. Benefit from our expertise Forward-thinking lenders should power their marketing strategies with a data-backed approach to incorporate the latest information from internal and external sources and reach the right customer at the right time and place. From list building to identity management and verification, you can turn to Experian to access the latest data and analytics tools. Learn about Experian credit prescreen and marketing solutions. Explore our credit prescreen solutions Learn about our marketing solutions 1Mortgage Bankers Association (October 2022). Mortgage Applications Decrease in Latest MBA Weekly Survey 2McKinsey & Company (2021). Five trends reshaping the US home mortgage industry

Today’s changing economy is directly impacting consumers’ financial behaviors, with some individuals doing well and some showing signs of payment stress. And while these trends may pose challenges to financial institutions, such as how to expand their customer base without taking on additional risk, the right credit attributes can help them drive smarter and more profitable lending decisions. With Experian’s industry-leading credit attributes, organizations can develop precise and explainable acquisition models and strategies. As a result, they can: Expand into new segments: By gaining deeper insights into consumer trends and behaviors, organizations can better assess an individual’s creditworthiness and approve populations who might have been overlooked due to limited or no credit history. Improve the customer experience: Having a wider view of consumer credit behavior and patterns allows organizations to apply the best treatment at the right time based on each consumer’s specific needs. Save time and resources: With an ongoing managed set of base attributes, organizations don’t have to invest significant resources to develop the attributes themselves. Additionally, existing attributes are regularly updated and new attributes are added to keep pace with industry and regulatory changes. Case study: Enhance decision-making and segmentation strategies A large retail credit card issuer was looking to grow their portfolio by identifying and engaging more consumers who met their credit criteria. To do this, they needed to replace their existing custom acquisition model with one that provided a granular view of consumer behavior. By partnering with Experian, the company was able to implement an advanced custom acquisition model powered by our proprietary Trended 3DTM and Premier AttributesSM. Trended 3D analyzes consumers’ behavior patterns over time, while Premier Attributes aggregates and summarizes findings from credit report data, enabling the company to make faster and more strategic lending decisions. Validations of the new model showed up to 10 percent improvement in performance across all segments, helping the company design more effective segmentation strategies, lower their risk exposure and approve more accounts. To learn how Experian can help your organization make the best data-driven decisions, read the full case study or visit us. Download case study Visit us

Today's top lenders use traditional and alternative credit data1 – or expanded Fair Credit Reporting Act (FCRA) regulated data – including consumer permissioned data, to enhance their credit decisioning. The ability to gain a more complete and timely understanding of consumers' financial situation allows lenders to better gauge creditworthiness, make faster decisions and grow their portfolios without taking on additional risk. Why lenders need to go beyond traditional credit data Traditional credit data is — and will remain — important to understanding the likelihood that a borrower will repay a loan as agreed. However, lenders who solely base credit decisions on traditional credit data and scores may overlook creditworthy consumers who don't qualify for a credit score — sometimes called unscorable or credit invisible consumers. Additionally, they may be spending time and money on manual reviews for applications that are low risk and should be automatically approved. Or extending offers that aren't a good fit. What is consumer permissioned data? Consumer permissioned data, or user permissioned data, includes transactional and account-level data, often from a bank, credit union or brokerage account, that a consumer gives permission to view and use in credit decisioning. To access the data, lenders create secure connections to financial institutions or data aggregators. The process and approach give consumers the power to authorize (and later retract) access to accounts of their choosing — putting them in control of their personal information — while setting up security measures that keep their information secure. In return for sharing access to their account information, consumers may qualify for more financial products and better terms on credit offers. What does consumer permissioned data include? Consumers can choose to share different types of information with lenders, including their account balances and transaction history. While there may be other sources for estimated or historic account-level data, permissioned data can be updated in real-time to give lenders the most accurate and timely view of a consumer's finances. There is also a wealth of information available within these transaction records. For example, consumers can use Experian Boost™ to get credit for non-traditional bills, including phone, utility, rent and streaming service payments. These bills generally don't appear in traditional credit reports and don't impact every type of credit score. But seeing a consumer's history of making these payments can be important for understanding their overall creditworthiness. What are the benefits of leveraging consumer permissioned data? You can incorporate consumer permissioned data into custom lending models, including the latest explainable machine learning models. As part of a loan origination system, the data can help with: Portfolio expansion Accessing and using new data can expand your lending universe in several ways. There are an estimated 28 million U.S. adults who don't have a credit file at the bureaus, and an additional 21 million who have a credit file but lack enough information to be scorable by conventional scoring models. These people aren't necessarily a credit risk — they're simply an unknown. Increased insights can help you understand the real risk and make an informed decision. Additionally, a deeper insight into consumers' creditworthiness allows you to swap in applications that are a good credit risk. In other words, approving applications that you wouldn't have been able to approve with an older credit decision process. Increase financial inclusion Many credit invisibles and thin-file applicants also fall into historically marginalized groups.2 Almost a third of adults in low-income neighborhoods are credit invisible.3 Black Americans are much more likely (1.8 times) to be credit invisible or unscorable than white Americans.4 Recent immigrants may have trouble accessing credit in the U.S., even if they had a good credit history in their home country.5 As a result, using consumer permissioned data to expand your portfolio can align with your financial inclusion efforts. It's one example of how financial inclusion is good for business and society. Enhance decisioning and minimize risk Consumer-permissioned data can also improve and expand automated decisions, which can be important throughout the entire loan underwriting journey. In particular, you may be able to: Verify income faster: By linking to consumers’ accounts and reviewing deposits, lenders can quickly verify their income and ability to pay. Make better decisions: Consumer permissioned data also give lenders a new lens for understanding an applicant’s credit risk, which can let you say yes more often without taking on additional risk. Process more applications: A better understanding of applicants’ credit risk can also decrease how many applications you send to manual review, which allows you to process more applications using the same resources. Increase customer satisfaction: Put it all together, and faster decisions and more approvals lead to happier customers. While consumer permissioned data can play a role in all of these, it's not the only type of alternative data that lenders use to grow their portfolios. What are other types of alternative data sources? In addition to consumer permissioned data, alternative credit data can include information from: Alternative financial services: Credit data from alternative financial services firms includes information on small-dollar installment loans, single-payment loans, point-of-sale financing, auto title loans and rent-to-own agreements. Rental agreement: Rent payment data from landlords, property managers, collection companies and rent payment services. Public records: Full-file public records go beyond what’s in a consumer’s credit report and can include professional and occupational licenses, property deeds and address history. Why partner with Experian? As an industry leader in consumer credit and data analytics, Experian is continuously building on its legacy in the credit space to help lenders access and use various types of alternative data. Along with Experian Boost™ for consumer permissioned data, Experian RentBureau and Clarity Services are trusted sources of alternative data that comply with the FCRA. Experian also offers services for lenders that want help understanding and using the data for marketing, lending and collections. For originations, the Lift Premium™ credit model can use alternative credit data to score over 65% of traditionally credit-invisible consumers. Expand your lending universe Lenders are turning to new data sources to expand their portfolios and remain competitive. The results can provide a win-win, as lenders can increase approvals and decrease application processing times without taking on more risk. At the same time, these new strategies are helping financial inclusion efforts and allowing more people to access the credit they need. Learn more 1When 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. Hence, the term “Expanded FCRA Data" may also apply in this instance and both can be used interchangeably.2-5Oliver Wyman (2022). Driving Growth With Greater Credit Access

When your marketing strategies don’t go as planned, don’t you wish you could have taken a “mulligan?” In today’s marketing world, it’s normal and critical to measure marketing effectiveness.