Data Quality

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More than half of U.S. businesses say they discuss fraud management often, making fraud detection in banking top-of-mind. Banking fraud prevention can seem daunting, but with the proper tools, banks, credit unions, fintechs, and other financial institutions can frustrate and root out fraudsters while maintaining a positive experience for good customers. What is banking fraud? Banking fraud is a type of financial crime that uses illegal means to obtain money, assets, or other property owned or held by a bank, other financial institution, or customers of the bank. This type of fraud can be difficult to detect when misclassified as credit risk or written off as a loss rather than investigated and prevented in the future. Fraud that impacts financial institutions consists of small-scale one-off events or larger efforts perpetrated by fraud rings. Not long ago, many of the techniques utilized by fraudsters required in-person or phone-based activities. Now, many of these activities are online, making it easier for fraudsters to disguise their intent and perpetrate multiple attacks at once or in sequence. Banking fraud can include: Identity theft: When a bad actor steals a consumer’s personal information and uses it to take money, open credit accounts, make purchases, and more. Check fraud: This type of fraud occurs when a fraudster writes a bad check, forges information, or steals and alters someone else’s check. Credit card fraud: A form of identity theft where a bad actor makes purchases or gets a cash advance in the name of an unsuspecting consumer. The fraudster may takeover an existing account by gaining access to account numbers online, steal a physical card, or open a new account in someone else’s name.  Phishing: These malicious efforts allow scammers to steal personal and account information through use of email, or in the case of smishing, through text messages. The fraudster often sends a link to the consumer that looks legitimate but is designed to steal login information, personally identifiable information, and more. Direct deposit account fraud: Also known as DDA fraud, criminals monetize stolen information to open new accounts and divert funds from payroll, assistance programs, and more. Unfortunately, this type of fraud doesn’t just lead to lost funds – it also exposes consumer data, impacts banks’ reputations, and has larger implications for the financial system. Today, top concerns for banks include generative AI (GenAI) fraud, peer-to-peer (P2P) payment scams, identity theft and transaction fraud. Without the proper detection and prevention techniques, it’s difficult for banks to keep fraudsters perpetrating these schemes out. What is banking fraud prevention? Detecting and preventing banking fraud consists of a set of techniques and tasks that help protect customers, assets and systems from those with malicious intent. Risk management solutions for banks identify fraudulent access attempts, suspicious transfer requests, signs of false identities, and more. The financial industry is constantly evolving, and so are fraudsters. As a result, it’s important for organizations to stay ahead of the curve by investing in new fraud prevention technologies. Depending on the size and sophistication of your institution, the tools and techniques that comprise your banking fraud prevention solutions may look different. However, every strategy should include multiple layers of friction designed to trip up fraudsters enough to abandon their efforts, and include flags for suspicious activity and other indicators that a user or transaction requires further scrutiny.   Some of the emerging trends in banking fraud prevention include: Use of artificial intelligence (AI) and machine learning (ML). While these technologies aren’t new, they are finding footing across industries as they can be used to identify patterns consistent with fraudulent activity – some of which are difficult or time-consuming to detect with traditional methods. Behavioral analytics and biometrics. By noting standard customer behaviors — e.g., which devices they use and when — and how they use those devices — looking for markers of human behavior vs. bot or fraud ring activity — organizations can flag riskier users for additional authentication and verification. Leveraging additional data sources. By looking beyond standard credit reports when opening credit accounts, organizations can better detect signs of identity theft, synthetic identities, and even potential first-party fraud.     With real-time fraud detection tools in place, financial institutions can more easily identify good consumers and allow them to complete their requests while applying the right amount and type of friction to detect and prevent fraud.   How to prevent and detect banking fraud In order to be successful in the fight against fraud and keep yourself and your customers safe, financial institutions of all sizes and types must: Balance risk mitigation with the customer experience Ensure seamless interactions across platforms for known consumers who present little to no risk Leverage proper identity resolution and verification tools Recognize good consumers and apply the proper fraud mitigation techniques to riskier scenarios With Experian’s interconnected approach to fraud detection in banking, incorporating data, analytics, fraud risk scores, device intelligence, and more, you can track and assess various activities and determine where additional authentication, friction, or human intervention is required. 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Published: July 19, 2023 by Guest Contributor

‘Big data’ might not be the buzzword du jour, but it's here to stay. Whether trying to improve your customer experience, portfolio performance, automation, or new AI capabilities, access to quality data from varying data sources can create growth opportunities. 85 percent of organizations believe that poor-quality customer contact data negatively affects their operations and efficiencies, which leads to wasted resources and damages their brand. And 77 percent said that inaccurate data hurt their response to market changes during the pandemic.1 If you want to use data to drive your business forward, consider where the data comes from and how you can glean useful insights. What is a data source? A data source is a location where you can access information. It's a broad description because data sources can come in different formats — the definition depends on how the data is being used rather than a specific storage type. For example, you can get data from a spreadsheet, sensors on an internet of things device or scrape it from websites. You might store the data you gather using different types of databases. And in turn, those databases can be data sources for other programs or organizations. Types of data sources Many organizations have chief data officers, along with data engineers, scientists and analysts who gather, clean, organize and manage data. This important work relies on understanding the technical aspects of varying data sources and connections. And it can turn a disorganized pool of data into structured databases that business leaders can easily access and analyze. From a non-technical point of view, it’s important to consider where the data comes from and the pros and cons of these data sources. For instance, marketers might define data sources as: First-party data: The data collected about customers and prospects, such as account details, transaction history and interactions with your website or app. The data can be especially valuable and insightful when you can connect the dots between previously siloed data sources within your organization.Zero-party data: Some organizations have a separate classification for information that customers voluntarily share, such as their communication preferences and survey results. It can be helpful to view this data separately because it reflects customers' desires and interests, which can be used to further customize your messaging and recommendations.Second-party data: Another organization's first-party data can be your second-party data if you purchase it or have a partnership that involves data sharing or data collaboration. Second-party data can be helpful because you know exactly where the information comes from and it can complement information you already have about customers or prospects.Third-party data: Third-party data comes from aggregators that collect and organize information from multiple sources. It can further enrich your customer view to improve marketing, underwriting, customer service and collection efforts. READ: The Realizing a Single Customer View white paper explores how organizations can use high-quality data to better understand their customers. How can a data-driven approach benefit your business? Organizations use data science to make sense of the increasingly large flow of information from varying data sources. A clear view can be important for driving growth and responding to changing consumer preferences and economic uncertainty. A 2022 survey of U.S. organizations found high-quality data can help:2 Grow your business: 91 percent said investing in data quality helped business growth.Improve customer experience: 90 percent said better data quality led to better customer experiences.Increase agility: 89 percent said best practices for data quality improved business agility. You can see these benefits play out in different areas. For example, you can more precisely segment customers based on reliable geographic, demographic, behavioral and psychographic data. Or combine data sources to get a more accurate view of consumer risk and increase your AI-powered credit risk decisioning capabilities. But building and scaling data systems while maintaining good quality isn't easy. Many organizations have to manage multiple internal and external data sources, and these can feed into databases that don't always communicate with one another. Most organizations (85 percent) are looking toward automation to improve efficiency and make up for skill shortages. Most are also investing in technology to help them monitor, report and visualize data — making it easier to understand and use.3 WATCH: See how you can go from data to information to insight and foresight in the Using Business Intelligence to Unlock Better Lending Decisions webinar. Access high-quality data from Experian Digital acceleration has made accessing quality data more important than ever. This includes learning how to collect and manage your zero- and first-party data. Experian's data quality management solutions can help you aggregate, cleanse and monitor your data. And the business intelligence tools and platform democratize access, allowing non-technical business leaders to find meaningful insights. You can also enhance your data sets with second- and third-party data. Our industry-leading data sources have information on over 245 million consumers and 32 million businesses, including proprietary data assets. These include traditional credit bureau data, alternative credit data, automotive data, commercial credit data, buy now pay later data, fraud data and residential property data. And you can use our API developer portal to access additional third-party data sources within the same interface. Learn more about Experian's data sources. 1. Experian (2022). 2022 Global Data Management Research Report2. Experian (2022). The Data Quality Imperative3. Ibid.

Published: June 22, 2023 by Julie Lee

Every data-driven organization needs to turn raw data into insights and, potentially, foresight. There was a time when lack of data was a hindrance, but that's often no longer the case. Many organizations are overwhelmed with too much data and lack clarity on how to best organize or use it. Modern business intelligence platforms can help. And financial institutions can use business intelligence analytics to optimize their decisioning and uncover safe growth opportunities. What is business intelligence? Business intelligence is an overarching term for the platforms and processes that organizations use to collect, store, analyze and display data and information. The ability to go from raw data to useful insights and foresight presents organizations with a powerful advantage, and can help them greatly improve their operations and efficiencies. Let’s pause and break down the below terms before expanding on business intelligence. Data: The raw information, such as customers' credit scores. Many organizations collect so much data that keeping it all can be an expensive challenge. Access to new types of data, such as alternative credit data, can assist with decisioning — but additional data points are only helpful if you have the resources or expertise to process and analyze them.Information: Once you process and organize data points, you can display the resulting information in reports, dashboards, and other visualizations that are easier to understand. Therefore, turning raw data into information. For example, the information you acquire might dictate that customers with credit scores over 720 prefer one of your products twice as much as your other products.Insight: The information tells you what happened, but you must analyze it to find useful and actionable insights. There could be several reasons customers within a specific score band prefer one product over another, and insights offer context and help you decide what to do next. In addition, you could also see what happened to the customers who were not approved.Foresight: You can also use information and insights to make predictions about what can happen or how to act in the future given different scenarios. For example, how your customers' preferences will likely change if you offer new terms, introduce a new product or there's a large economic shift. Business intelligence isn't new — but it is changing. Traditionally, business intelligence heavily relied on IT teams to sift through the data and generate reports, dashboards and other visualizations. Business leaders could ask questions and wait for the IT team to answer the queries and present the results. Modern business intelligence platforms make that process much easier and offer analytical insights. Now even non-technical business leaders can quickly answer questions with cloud-based and self-service tools. Business intelligence vs. business intelligence analytics Business intelligence can refer to the overall systems in place that collect, store, organize and visualize your data. Business intelligence tends to focus on turning data into presentable information and descriptive analytics — telling you what happened and how it happened. Business intelligence analytics is a subset of business intelligence that focuses on diagnostics, predictive and prescriptive analytics. In other words, why something happened, what could happen in the future, and what you should do. Essentially, the insights and foresight that are listed above. How can modern business intelligence benefit lenders? A business intelligence strategy and advanced analytics and modeling can help lenders precisely target customers, improve product offerings, streamline originations, manage portfolios and increase recovery rates. More specifically, business intelligence can help lenders uncover various trends and insights, such as: Changes in consumers' financial health and credit behavior.How customers' credit scores migrate over time.The risk performance of various portfolios.How product offerings and terms compare to competitors.Which loans are they losing to peers?Which credit attributes are most predictive for their target market? Understanding what's working well today is imperative. But your competitors aren't standing still. You also need to monitor trends and forecast the impact — good or bad — of various changes. WATCH: Webinar: Using Business Intelligence to Unlock Better Lending Decisions Using business intelligence to safely grow your portfolio Let's take a deeper dive into how business intelligence could help you grow your portfolio without taking on additional risk. It's an appealing goal that could be addressed in different ways depending on the underlying issue and business objective. For example, you might be losing loans to peers because of an acquisition strategy that's resulting in declining good customers. Or, perhaps your competitors' products are more appealing to your target customers. Business intelligence can show you how many applications you received, approved, and booked — and how many approved or declined applicants accepted a competitor's offer. You can segment and analyze the results based on the applicant’s credit scores, income, debt-to-income, loan amounts, loan terms, loan performance and other metrics. An in-depth analysis might highlight meaningful insights. For example, you might find that you disproportionately lost longer-term loans to competitors. Perhaps matching your competitors' long-term loan offerings could help you book more loans. READ: White paper: Getting AI-driven decisioning right in financial services Experian's business intelligence analytics solutions Lenders can use modern business intelligence platforms to better understand their customers, products, competitors, trends, and the potential impact of shifting economic circumstances or consumer behavior. Experian's Ascend Intelligence Services™ suite of solutions can help you turn data points into actionable insights. Ascend Intelligence Services™ Acquire Model: Create custom machine learning models that can incorporate internal, bureau and alternative credit data to more accurately assess risk and increase your lending universe.Ascend Intelligence Services™ Acquire Strategy: Get a more granular view of applicants that can help you improve segmentation and increase automation.Ascend Intelligence Services™ Pulse: A model and strategy health dashboard that can help you proactively identify and remediate issues and nimbly react to market changes.Ascend Intelligence Services™ Limit: Set and manage credit limits during account opening and when managing accounts to increase revenue and mitigate risk.Ascend Intelligence Services™ Foresight: A modern business intelligence platform that offers easy-to-use tools that help business leaders make better-informed decisions. Businesses can also leverage Experian's industry-leading data assets and expertise with various types of project-based and ongoing engagements. Learn more about how you can implement or benefit from business intelligence analytics.

Published: May 31, 2023 by Julie Lee

On average, the typical global consumer owns three or more connected devices.1 80% of consumers bounce between devices, while 31% who turned to digital channels for their last purchase used multiple devices along the way.2 Considering these trends, many lenders are leveraging multiple channels in addition to direct mail, including email and mobile applications, to maximize their credit marketing efforts. The challenge, however, is effectively engaging consumers without becoming overbearing or inconsistent. In this article, we explore what identity resolution for credit marketing is and how the right identity tools can enable financial institutions to create more cohesive and personalized customer interactions. What is identity resolution? Identity resolution connects unique identifiers across touchpoints to build a unified identity for an individual, household, or business. This requires an identity graph, a proprietary database that collects, stitches, and stores identifiers from digital and offline sources. As a result, organizations can create a persistent, high-definition customer view, allowing for more consistent and meaningful brand experiences. What are the types of identity resolution? There are two common approaches to identity resolution: probabilistic ID matching and deterministic ID matching. Probabilistic ID matching uses multiple algorithms and data sets to match identity profiles that are most likely the same customer. Data points used in probabilistic models include IP addresses and device types. Deterministic ID matching uses first-party data that customers have produced, enabling you to merge new data with customer records and identify matches among existing identifiers. Examples of this type of data include phone numbers and email addresses. What role does identity resolution play in credit marketing? Maintaining a comprehensive customer view is crucial to credit marketing — the insights gained allow lenders to determine who they should engage and the type of offer or messaging that would resonate most. But there are many factors that can prevent financial institutions from doing this effectively: poor data quality, consumers bouncing between multiple devices, and so on. Seven out of 10 consumers find it important that companies they interact with online identify them across visits. Identity resolution for credit marketing solves these issues by matching and linking customer data from disparate sources back to a single profile. This enables lenders to: Create highly targeted campaigns. If your data is incomplete or inaccurate, you may waste your marketing spend by engaging the wrong audience or sending out irrelevant credit offers. An identity resolution solution that leverages expansive, regularly updated data gives you access to high-definition views of individuals, resulting in more personalization and greater campaign engagement. Deliver seamless, omnichannel experiences. To further improve your credit marketing efforts, you’ll need to keep up with consumers not only as their needs or preferences change, but also as they move across channels and devices. Instead of creating multiple identity profiles for the same person, identity resolution can recognize an individual across touchpoints, allowing you to create consistent offers and cohesive experiences. Picking the right marketing identity resolution solution While the type of identity resolution for marketing solution can vary depending on your business’s goals and challenges, Experian can help you get started. To learn more, visit us today. 1 Global number of devices and connections per capita 2018-2023, Statista. 2 Cross Device Marketing - Statistics and Trends, Go-Globe.

Published: May 25, 2023 by Theresa Nguyen

Customer-driven marketing isn't just a buzzword — it's a strategic priority, especially in today's competitive digital landscape. Rather than pushing product-centric messaging, leading financial institutions (FIs) are shifting to strategies that put the customer at the core of every decision, message and experience. This means providing personalized experiences that enable customers to feel seen and heard. What is customer-driven marketing? Customer-driven marketing doesn't just improve visibility — it turns customers into brand advocates. It's a strategy that begins by understanding and prioritizing the needs, motivations and behaviors of customers, and then aligning every campaign, channel and touchpoint with those insights. This methodology focuses on relevance, personalization and responsiveness to customer signals. Why does customer-driven credit marketing matter? Today's consumers expect FIs to understand them beyond surface-level demographics. They demand tailored content, offers that match their needs and seamless interactions across channels. An effective customer-driven marketing strategy: Enhances personalization and relevance. By understanding consumer preferences, life stages and intent signals, FIs can move beyond generic messaging and create timely, relevant communications that resonate. The result is stronger engagement, higher response rates and more meaningful customer interactions. Boosts customer acquisition and retention. Customer-driven marketing enables FIs to identify and reach the most profitable, highly responsive prospects in the most efficient way, while also engaging with current customers to improve long-term retention. Improves campaign ROI and performance. By focusing marketing investments on the right audiences, customer-driven marketing ensures budgets are allocated strategically and impact is maximized. Enables stronger brand loyalty and trust. Customer-driven marketing fosters trust by respecting consumer preferences, delivering helpful content and creating seamless omnichannel experiences. Over time, this builds deeper brand loyalty, increases customer lifetime value and turns satisfied customers into advocates. Step-by-step: Developing the strategy Customer-driven marketing is less funnel, more spiral. You research, test, refine and repeat, all while taking into account customer feedback and campaign results. Start with deep audience understanding The foundation of effective customer-driven marketing lies in data-informed customer insights. Unlock a comprehensive view of your customers by combining first-party data with enriched analytics from trusted data partners. For example, Experian’s ConsumerView database lets marketers build audiences of more than 300 million U.S. consumers and 126 million households, supporting granular segmentation and personalization. Define and prioritize target segments Once your data foundation is in place, identify high-value segments based on behavior, purchase history, and life stage — not just basic demographics. This is where customer-driven marketing shines: instead of broad audience buckets, you target precise groups with tailored communications that feel 1:1. Deliver personalized experiences across channels Customers interact with brands in many ways — from email and social media to connected TV, search and in-store visits. A customer-driven marketing strategy ensures your brand message feels cohesive, relevant and timely across every touchpoint. Measure, learn and iterate A core part of customer-driven marketing is continuous improvement. Track how audiences respond to messaging and experiences — and refine your approach based on performance metrics. This “research, test, refine, repeat” mindset is essential for staying aligned with evolving customer expectations and maximizing ROI over time. Importance of a customer-driven marketing strategy Putting consumers at the center of credit marketing strategies — and at the center of your business as a whole — is the foundation for personalized experiences that can ultimately increase response rates and customer satisfaction. For more on how your organization can develop an effective customer-driven marketing strategy, learn about our credit marketing solutions.   Learn more

Published: May 19, 2023 by Theresa Nguyen

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

Published: January 30, 2023 by Theresa Nguyen

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

Published: December 8, 2022 by Guest Contributor

With consumers having more credit options than ever before, it’s imperative for lenders to get their message in front of ideal customers at the right time and place. But without clear insights into their interests, credit behaviors or financial capacity, you may risk extending preapproved credit offers to individuals who are unqualified or have already committed to another lender. To increase response rates and reduce wasted marketing spend, you must develop an effective customer targeting strategy. What makes an effective customer targeting strategy? A customer targeting strategy is only as good as the data that informs it. To create a strategy that’s truly effective, you’ll need data that’s relevant, regularly updated, and comprehensive. Alternative data and credit-based attributes allow you to identify financially stressed consumers by providing insight into their ability to pay, whether their debt or spending has increased, and their propensity to transfer balances and consolidate loans. With a more granular view of consumers’ credit behaviors over time, you can avoid high-risk accounts and focus only on targeting individuals that meet your credit criteria. While leveraging additional data sources can help you better identify creditworthy consumers, how can you improve the chances of them converting? At the end of the day, it’s also the consumer that’s making the decision to engage, and if you aren’t sending the right offer at the precise moment of interest, you may lose high-value prospects to competitors who will. To effectively target consumers who are most likely to respond to your credit offers, you must take a customer-centric approach by learning about where they’ve been, what their goals are, and how to best cater to their needs and interests. Some types of data that can help make your targeting strategy more customer-centric include: Demographic data like age, gender, occupation and marital status, give you an idea of who your customers are as individuals, allowing you to enhance your segmentation strategies. Lifestyle and interest data allow you to create more personalized credit offers by providing insight into your consumers’ hobbies and pastimes. Life event data, such as new homeowners or new parents, helps you connect with consumers who have experienced a major life event and may be receptive to event-based marketing campaigns during these milestones. Channel preference data enables you to reach consumers with the right message at the right time on their preferred channel. Target high-potential, high-value prospects By using an effective customer targeting strategy, you can identify and engage creditworthy consumers with the greatest propensity to accept your credit offer. To see if your current strategy has what it takes and what Experian can do to help, view this interactive checklist or visit us today. Review your customer targeting strategy Visit us

Published: October 10, 2022 by Theresa Nguyen

Whether your goal is to gain new business or create cross-sell opportunities, being proactive in your credit marketing approach can help drive higher response rates and more meaningful customer experiences. But without knowing when your ideal customers are actively seeking credit, you may risk losing business to lenders who have already engaged. So, how can you identify new opportunities when they occur? Given that 91% of consumers say they’re more likely to shop with brands that provide relevant offers, you’ll need to reach the right consumers at the right moment to increase response rates and stay ahead of competitors. Event-based credit triggers can help you identify new tradelines, inquiries and certain loans nearing term to locate highly responsive, credit-active individuals. By receiving updates on consumers’ recent credit activities, you can make firm credit offers immediately so you never miss an opportunity. Case Study: Deliver timely offers with credit trigger leads Vantage West Credit Union serves over 170,000 members across Arizona. With their members looking elsewhere for their mortgage needs, Vantage West aimed to drive as many of these members back to the credit union as possible. To do this, they looked for a solution that could help them identify and target members who are in the market for a new mortgage. By augmenting their prescreen process with Experian’s Prospect Triggers for mortgages, the credit union was able to quickly pinpoint consumers that not only met their credit criteria but were also likely to respond to their credit offers. Within two years of implementing Prospect Triggers, Vantage West funded an additional $18 million in mortgages and is continuing to grow by making timely offers to credit-active prospects. Prospect Triggers is available for banks, credit card issuers, mortgage lenders, retailers and automotive lenders. To learn how Experian can help bring precision and profitability to your credit marketing campaigns, read the full case study or visit us. Download the case study Visit us

Published: September 26, 2022 by Theresa Nguyen

Earlier this year, I explored the potential impact of the end of the current Public Health Emergency (PHE). The U.S. federal government has been operating under a PHE for COVID-19 for more than 30 consecutive months since it was initially announced in January 2020. On July 15, 2022, this PHE was renewed for a tenth time. Following this latest extension, the Centers for Medicare & Medicaid Services (CMS) has released a roadmap for the end of the COVID-19 PHE. In a related blog, they reiterate the commitment to provide a 60-day notice prior to the end of the PHE, but urge states and healthcare providers to prepare for the end “as soon as possible.” With these upcoming changes in mind, I wanted to review key areas for providers to consider as they prepare for the end of the PHE. Enrollments continue to increase, putting state budgets at risk From the start of the PHE in February 2020 through April 2022, Medicaid/Children’s Health Insurance Plan (CHIP) enrollment has increased by more than 17M people and this is affecting every state. Nearly half of all states have experienced an increase of more than 25% during this time period, with some experiencing increases of more than 40%. Given an average Medicaid cost to states of more than $8.4K per capita, that translates to an increase of billions of dollars. Once the PHE expires, states will have 12 months to redetermine eligibility for continued enrollment in the program, or risk bearing 100% of the associated cost. Preparing for the end of the PHE To avoid unnecessary expenditures and ensure that citizens are receiving access to the correct services, states will have to conduct a holistic review of their Medicaid rolls to confirm eligibility. In CMS’s guidance for states to prepare for the end of the PHE, they recommend creating an automated process to handle this unprecedented review. With the right partner, agencies can perform redeterminations of their existing registration rolls, and prepare for future services requests. The right solution can allow citizens to easily apply for benefits, triggering the automatic, real-time pull of income and employment information so that the agency can verify eligibility. Experian is a trusted government partner that is ready to assist states with preparing and automating the process for redetermination of benefits. To learn more about how Experian can assist with citizen benefit redetermination and registration efforts, visit us or request a call. Learn more

Published: August 31, 2022 by Eric Thompson

From desktops and laptops to smartphones and tablets, consumers leverage multiple devices when engaging with businesses. For financial institutions, it’s important to identify and track consumers across devices to deliver personalized offers and increase opportunities for conversion. The problem with cookies Marketers have traditionally used cookies to determine what their audience’s interests are based on their browsing activity and past purchases. An example of this is when a user browses a product on a website and then leaves without buying. Later that day, they see an ad on social media featuring the same product they viewed earlier. While this may seem like an effective way for financial institutions to target or prescreen consumers, cookies are very limited — they can’t capture or connect a user’s behavior across multiple touchpoints. In other words, if a consumer were to browse a website on their mobile phone and then switch to their laptop, the business would view these sessions as two different visits from two different people, resulting in inconsistent messaging and a disjointed user experience. This is a huge problem because devices don’t decide to convert — people do. To reach the right consumers with the right message wherever they may be, financial institutions must look beyond cookies. This is where people-based marketing comes in. What is people-based marketing? People-based marketing takes a more personal marketing approach. Rather than targeting devices, people-based marketing connects businesses with real people, helping them understand who their customers are, what they’re looking for and how to engage them in more meaningful ways. It does this by gathering customer data from both online and offline sources to create a single customer profile. Let’s look at an example of people-based marketing by revisiting the scenario above. A user is browsing a company’s website on their mobile phone and decides to switch to their laptop. By capturing a single view of the user with a people-based marketing solution, the brand can recognize them and resume their experience on the new device. What’s more, the brand understands the user’s intent at that stage of their customer journey and leverages real-time data to make relevant offers and recommendations, helping further personalize their experience. Benefits of a people-based marketing approach To create better-targeted credit marketing campaigns, financial institutions must ensure they have the right data and technologies in place. Experian’s industry-leading database technology provides the freshest, most comprehensive consumer credit data to help organizations optimize their lending criteria and marketing campaigns. With Experian’s people-based marketing solutions, financial institutions can: Reach the right people: Leveraging fresh consumer data allows financial institutions to target the best prospects for their business needs and avoid making preapproved offers to nonqualified consumers. Deliver personalized credit offers: By gaining a more complete view of consumers, financial institutions can ensure they’re sending relevant offers to users where and when they’re most motivated to respond. Enhance their retargeting efforts: If a user isn’t ready to convert upon their first interaction, organizations can reach them on another device to reinforce their messaging in more personalized ways. Provide frictionless, omnichannel experiences: Seamless identity resolution allows organizations to accurately recognize consumers across devices, leading to more precise targeting and cohesive customer experiences. Reduce marketing spend: By focusing on the right audience with the right message, organizations can avoid unlikely prospects and reduce wasted marketing spend, all while increasing response rates. Expand their reach: With rich insights into their clients’ interests, demographics and behaviors, financial institutions can target prospects who share similar characteristics and are likely to convert. Leveraging an effective people-based marketing strategy is crucial to delivering personalized and consistent customer experiences in today’s multi-device world. To learn more about how Experian can help, visit us today. Learn about our people-based marketing solutions

Published: August 16, 2022 by Theresa Nguyen

Mortgage lenders are no stranger to income and employment verification. Leveraging a third-party solution provider for automated verifications is a standard practice in mortgage underwriting. Yet many lenders still struggle with time-consuming and complex verification experiences, which can be manual, inefficient and painful for borrowers. Since introducing Experian Verify™ to the market, we’ve had countless conversations with key players in the industry – from the largest banks to small independent mortgage brokers and everything in between. Through these conversations, we’ve learned quite a bit about some of the dos and don’ts when it comes to implementing a successful strategy for income and employment verification for mortgage. Lead with instant verification Digital transformation has forever changed borrower expectations for online experiences. The first key to a successful verification strategy is starting your workflow with an instant verification solution. This allows you to verify information in real time, delivering a completely frictionless experience for you and your borrowers. Consider building a waterfall process For instances when a borrower’s income and employment information is unable to be verified through an instant verification solution, add a consumer-permissioned (bank or payroll) option as a backup. Cascading from one digital solution to the next will ensure you can verify borrower information in seconds or minutes, as opposed to days or weeks. The goal is to prevent as many borrowers as possible from going through a costly manual process. Tap into unique data sources Many verification solutions in market today tap into the same data sources, which can make it difficult to differentiate between solutions and measure additive benefits. When evaluating options, look for verification solutions that leverage unique and exclusive data sources – allowing you to optimize hit rates and maximize value. Avoid a “one-size-fits-all” approach There is no silver bullet. Every market is unique and every lender has different needs. Your verification requirements are likely specific to your business, which means you need to leverage verification solutions that offer flexible options and enable you to build a verification experience that works best for you and your borrowers. Find a solution provider who’s all in It’s important to find a solution provider where income and employment verification isn’t just a “side hustle,” but is core to their business strategy. Find a provider who is fully committed – delivering new innovations, investing in key partnerships, maximizing accessibility through leading LOS / POS technology providers, and offers eligibility for key industry programs, such as Day 1 Certainty® from Fannie Mae. Challenge the status quo Many lenders have an existing relationship with a third-party solution provider. But it’s important not to put all your eggs in one basket. If your existing provider is not meeting all your needs, challenge the status quo. Consider adding a second provider to the top of your waterfall to help contain costs and tap into unique data that is not available from your existing provider. Ready for further insight? Learn more about income and employment verification for mortgage.

Published: June 28, 2022 by Jenna Ostmann

From awarding bonus points on food delivery purchases to incorporating social media into their marketing efforts, credit card issuers have leveled up their acquisition strategies to attract and resonate with today’s consumers. But as appealing as these rewards may seem, many consumers are choosing not to own a credit card because of their inability to qualify for one. As card issuers go head-to-head in the battle to reach and connect with new consumers, they must implement more inclusive lending strategies to not only extend credit to underserved communities, but also grow their customer base. Here’s how card issuers can stay ahead: Reach: Look beyond the traditional credit scoring system With limited or no credit history, credit invisibles are often overlooked by lenders who rely solely on traditional credit information to determine applicants’ creditworthiness. This makes it difficult for credit invisibles to obtain financial products and services such as a credit card. However, not all credit invisibles are high-risk consumers and not every activity that could demonstrate their financial stability is captured by traditional data and scores. To better evaluate an applicant’s creditworthiness, lenders can leverage expanded data sources, such as an individual’s cash flow or bank account activity, as an additional lens into their financial health. With deeper insights into consumers’ banking behaviors, card issuers can more accurately assess their ability to pay and help historically disadvantaged populations increase their chances of approval. Not only will this empower underserved consumers to achieve their financial goals, but it provides card issuers with an opportunity to expand their customer base and improve profitability. Connect: Become a financial educator and advocate Credit card issuers looking to build lifelong relationships with new-to-credit consumers can do so by becoming their financial educator and mentor. Many new-to-credit consumers, such as Generation Z, are anxious about their finances but are interested in becoming financially literate. To help increase their credit understanding, card issuers can provide consumers with credit education tools and resources, such as infographics or ‘how-to’ guides, in their marketing campaigns. By learning about the basics and importance of credit, including what a credit score is and how to improve it, consumers can make smarter financial decisions, boost their creditworthiness, and stay loyal to the brand as they navigate their financial journeys. Accessing credit is a huge obstacle for consumers with limited or no credit history, but it doesn’t have to be. By leveraging expanded data sources and offering credit education to consumers, credit card issuers can approve more creditworthy applicants and unlock barriers to financial well-being. Visit us to learn about how Experian is helping businesses grow their portfolios and drive financial inclusion. Visit us

Published: May 17, 2022 by Theresa Nguyen

Many financial institutions have made inclusion a strategic priority to expand their reach and help more U.S. consumers access affordable financial services. To drive deeper understanding, Experian commissioned Forrester to do new research to identify key focal points for firms and how they are moving the needle. The study found that more than two-thirds of institutions had a strategy created and implemented while one-quarter reported they are already up and running with their inclusion plans.1 Tapping into the underserved The research examines the importance of engaging new audiences such as those that are new to credit, lower-income, thin file, unbanked and underbanked as well as small businesses. To tap into these areas, the study outlines the need to develop new products and services, adopt willingness to change policies and processes, and use more data to drive better decisions and reach.2 Expanded data for improved risk decisioning The research underlines the use of alternative data and emerging technologies to expand reach to new audiences and assist many who have been underserved. In fact, sixty-two percent of financial institutions surveyed reported they currently use or are planning to use expanded data to improve risk profiling and credit decisions, with focus on: Banking data Cash flow data Employment verification data Asset, investments, and wealth management data Alternative financial services data Telcom and utility data3 Join us to learn more at our free webinar “Reaching New Heights Together with Financial Inclusion” where detailed research and related tools will be shared featuring Forrester’s principal analyst on Tuesday, May 24 from 10 – 11 a.m. PT. Register here for more information. Find more financial inclusion resources at www.experian.com/inclusionforward. Register for webinar Visit us 1 Based on Forrester research 2 Ibid. 3 Ibid.

Published: May 12, 2022 by Guest Contributor

As more consumers apply for credit and increase their spending1, lenders and financial institutions have an opportunity to expand their portfolios and improve profitability. The challenge is ensuring they’re extending credit responsibly and inclusively. Millions of Americans, many of whom are creditworthy, lack access to mainstream credit options. This may be because they have limited or no credit history, negative information within their credit file, or are a part of a historically disadvantaged group. To say “yes” to consumers they otherwise couldn’t or wouldn’t lend to, lenders must gain a deeper understanding of an individual’s stability, ability and willingness to pay. That’s where expanded FCRA-regulated and trended data come in. While traditional credit data has long been the primary means of gauging creditworthiness, it doesn’t tell the full story of a consumer’s financial situation. Let’s explore how differentiated data can help lenders make more informed credit decisions. Using differentiated data for deeper lending Expanded FCRA-regulated data provides supplemental credit data to help lenders gain a more holistic view of their current and prospective customers. Some examples of expanded FCRA-regulated data include alternative financial services data from nontraditional lenders, consumer-permissioned account data, rental payments and full-file public records. Because this data drives greater visibility and transparency around inquiry and payment behaviors, lenders can more accurately determine a consumer’s ability to pay and distinguish between reliable and high-risk applicants. In turn, lenders can approve more creditworthy consumers, grow their portfolios and increase financial opportunities for underserved communities, all while preventing and mitigating risk. 89% of lenders agree that expanded FCRA-regulated data allows them to extend credit to more consumers. Trended data empowers lenders with predictive insights into consumers by providing key balance and payment data for the previous 24 months. This is important as lenders can determine if a consumer’s credit behavior has improved or deteriorated over time. In turn, lenders can: Identify creditworthy customers: Establish if a consumer has a demonstrated ability to pay, is consistently paying more than the minimum payment, or shows no signs of payment stress. Increase response rates: Match the right products with the right prospects. Determine upsell and cross-sell opportunities: Present relevant offers based on anticipated needs and behaviors. Limit loss exposure: Understand the direction and velocity of payment performance to effectively manage risk exposure. Trended data helps lenders better predict future behavior, manage portfolio risk and design the best marketing offers. Turning insights into action Together, trended and expanded FCRA-regulated data benefit lenders and consumers alike. With a more holistic view of their customers, lenders gain powerful insights to lend deeper, ultimately helping them to expand their portfolios and drive greater access to credit for underserved communities. Learn more 1 The Recovery of Credit Applications to Pre-Pandemic Levels, Consumer Financial Protection Bureau, 2021.

Published: March 8, 2022 by Theresa Nguyen

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