Credit Lending

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 embraced — or at least tested — AI within several parts of their organization. The most advanced use of machine learning (ML) models tends to occur with credit card and unsecured personal loan underwriting.1 However, by late 2021, nearly three-quarters of businesses had used AI and machine learning, and 81 percent felt confident in using advanced analytics and AI in credit risk decisioning.2 READ MORE: AI and Machine Learning for Financial Institutions Today, lenders are implementing AI-driven tools throughout the customer lifecycle to: Target the right consumers: Lenders can sift through vast amounts of data to find 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 fraudsters invest in technology and conduct increasingly sophisticated attacks.Assess creditworthiness: Machine learning-based models can incorporate a range of internal and external data points to more precisely evaluate creditworthiness and create a 10 to 15 percent performance lift compared with traditional linear and logistic regression models.3Automate decisions:  More precise evaluations can increase how many applications flow into your automated approval and denial process rather than requiring a manual review.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 around the world have recognized improving customer acquisition and digital engagement as top priorities. In a recent Experian survey, companies ranked investing in AI second, behind investing in decisioning software, as the best way to improve their digital experiences.2 The benefits of AI in lending Although lenders can use machine learning models in many ways, the primary drivers for adoption in underwriting are:1 Improving credit risk assessmentFaster development and deployment cycles for new or recalibrated modelsUnlocking the possibilities within large datasetsKeeping 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. CASE STUDY:  Atlas Credit, a small-dollar lender, used a machine learning-powered model and automation to nearly double its loan approval rates and decrease credit losses by up to 20 percent. 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 increasecustomer 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. In August 2021, Forrester Consulting conducted a study commissioned by Experian and found the main barriers to adopting machine learning were:4 Explainability of machine learning models (35 percent)Model deployment into decisioning strategy management systems (34 percent)Model deployment into live operational runtime environment (31 percent)Lack of access to in-house transactional data (30 percent)Lack of access to a wide range of traditional and non-traditional data assets (30 percent) 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.1 WATCH:  Explainable Artificial Intelligence: The Case of Fair Lending A lack of resources and expertise could hinder model development and deployment. It can take around nine months to build and deploy a custom model, and there's a lot of overhead to cover during the process.5 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.5 Experian built the Ascend Intelligence Services™ to help smaller and mid-market lenders access the most advanced analytics tools. The managed service platform won a Fintech Breakthrough Award in 2021, and it 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.5 Learn more about our machine learning solutions. * 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. 1FinRegLab (2021). The Use of Machine Learning for Credit Underwriting: Market & Data Science Context2Experian (2021). Global Insights Report September/October 2021 3Experian (2020). Machine Learning Decisions in Milliseconds 4Experian (2022). Explainability: ML and AI in credit decisioning 5Experian (2021). Podcast: Advanced Analytics, Artificial Intelligence and Machine Learning in Lending

With an abundance of loan options in today’s market, retaining customers can be challenging for banks and credit unions, especially small or regional institutions. And as more consumers look for personalization and digital tools in their banking experience, the likelihood of switching to institutions that can meet these demands is increasing.1 According to a recent Experian survey, 78% of consumers have conducted personal banking activities online in the last three months. However, 58% of consumers don’t feel that businesses completely meet their expectations for a digital online experience. To remain competitive in today's market, organizations must enhance their prescreen efforts by accelerating their digital transformation. Prescreen in today's economic environment While establishing a strong digital strategy is crucial to meeting the demands of today’s consumers, economic conditions are continuing to change, causing many financial institutions to either tighten their marketing budgets or hold off on their prescreen efforts completely. Fortunately, lenders can still drive growth during a changing economy without having to make huge cuts to their marketing budgets. How? The answer lies in digital prescreen. Case study: Uncover hidden growth opportunities Wanting to grow their business and existing relationships, Clear Mountain Bank looked for a solution that could help them engage customers with money-saving product offers while delivering a best-in-class digital banking experience. Leveraging Digital Prescreen with Micronotes, the bank was able to identify and present dollarized savings to customers who held higher-priced loans with other lenders. What’s more, the bank extended these offers through personalized conversations within their online and mobile banking platforms, resulting in improved digital engagement and increased customer satisfaction. By delivering competitive prescreen offers digitally, Clear Mountain Bank generated more than $1 million in incremental loans and provided customers with an average of $1,615 in cost savings within the first two months of deployment. “Digital Prescreen with Micronotes supplied the infrastructure to create higher-quality, personalized offers, as well as the delivery and reporting. They made prescreen marketing a reality for us.” – Robert Flockvich, Director of Community Outreach and Retail Lending at Clear Mountain Bank To learn more about how you can grow your portfolio and customer relationships, read the full case study or visit us. Download the case study Visit us 1The Keys to Solving Banking’s Customer Loyalty & Retention Problems, The Financial Brand, 2022.

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

Conventional credit scoring systems are based on models developed over six decades. As consumer behavior evolves, it's important to seek newer, fresher sources of data to assess creditworthiness. Because the data used by conventional credit scoring models does not provide the full picture of a consumer's financial health, a large population segment of the United States is excluded from accessing credit.With changing times and new technology, forward-thinking financial institutions are using alternative data1 to gain a more holistic consumer view. A move toward inclusive finance, including incorporating alternative data in credit scoring models, is a crucial step towards promoting financial inclusion and helping millions of consumers achieve their financial and personal goals. More importantly, it provides the insight needed for lender confidence, which can help fuel business growth. Understanding limitations of the conventional scoring system Credit scores can be obtained from any one of the major credit bureaus based on information found in a consumer's credit report and are incorporated into a lender's credit-decisioning process. While there are various credit scoring models based on lender preference that could yield slightly different scores, all traditional scores are comprised of credit characteristics within these categories: payment history, credit mix, credit history length, amounts owed and new credit account inquires. Lenders use past credit performance to predict whether extending credit is a risk, posing a major challenge for credit invisible and thin-file consumers and leaving millions at a disadvantage. This dilemma also limits business growth for lenders. Consumers who are unable to access mainstream credit often turn to the alternative financial services (AFS) industry, a $140 billion market that continues to grow by 7-10 percent each year.2 The AFS industry offers consumers additional products, like payday loans, cash advances, short-term installment loans, and rent-to-own loans, none of which are included in a traditional credit file. With alternative credit data, lenders can obtain a more holistic view of creditworthiness and risk, helping to enhance inclusive lending by broadening their pool of potential loan candidates. Why conventional scoring models simply aren't enough Because of the criteria used to assess creditworthiness, conventional credit scoring models do not accurately capture an individual's financial behavior or health. Indeed, many people demonstrate financial responsibility in other legitimate ways that are not reported to the major credit bureaus.In contrast, non-traditional data considers a consumer's everyday financial behavior to provide a more accurate score for lenders. It can include a range of indicators, such as: Bill payments: Consistent payment history on typical household bills (which may have been paid from a debit account). Bank account data: Shows average balance and withdrawal activity and recurring payroll deposits (indicating that a consumer is employed and receives a regular income). Rental data: Indicates a consumer's long-term stability in making regular, on-time monthly rent payments. Registered licenses: Registered licenses or membership with a skilled  trade or profession can indicate the likelihood to generate income. Including this type of data can benefit both lenders and applicants. According to an Experian report, by adding alternative credit data to a near-prime population, lenders could see an increase in approvals for consumers historically being left behind. When Clear Early Risk Score™ is paired with the VantageScore® credit score, approvals climb to 16 percent of the population inside the same risk criteria, representing a 60 percent lift in credit approvals for near-prime consumers.2 The pool of people from whom this type of alternative data can reliably be collected is growing, with 70 percent of consumers willing to provide additional financial information to a lender if it increases their chance for approval or improves their interest rate for a mortgage or car loan.3 Plenty of available yet untapped data exists that can add value to a consumer's profile and lead to greater inclusive lending. For example, 95 percent of Americans own a cell phone and about two-thirds of households headed by young adults are being rented. Reporting on this data could potentially "thicken" a credit file and provide deeper insight into a consumer's credit behavior.3Indeed, turning to non-traditional data can expand the credit universe and lead to more inclusive credit scoring models, especially by leveraging existing technology and financial inclusion solutions. Research shows that with Lift Premium™, virtually all of the 21 million conventionally unscorable consumers would become scoreable, and over 1 million of them would have scores in the near-prime range or better. Of these, 1.7 million would be Black American and Hispanic/Latino people.3 For lenders, these numbers reveal potential opportunities to grow their businesses. Of the 255 million adults in the U.S., 19 percent of credit eligible adults are left out of mainstream scoring systems. 28 million are considered credit invisible – meaning they have no credit history (11%). 21 million are considered unscorable – have partial credit history but not enough to generate a score using conventional models (8%). Of the remaining credit eligible adults, 57 million were considered subprime (22%). 106 million U.S. adults can't get mainstream credit rates (42%). Adopting inclusive finance lending practices is not only the right thing to do but also provides financial institutions with the chance to reach untapped markets, grow their business and promote a healthier economy. Financial inclusion is not a destination, but an ever-evolving journey. Don't miss out on this critical opportunity to join the movement. Learn more about our financial inclusion tools to help enhance your inclusive lending approach. 1"Alternative Credit Data,” refers to the use of alternative data and its appropriate use in consumer credit lending decisions, as regulated by the Fair Credit Reporting Act. Hence, the term “Expanded FCRA Data” may also apply in this instance and both can be used interchangeably.2Experian: 2020 State of Alternative Credit Data.3Oliver Wyman white paper, “Financial Inclusion and Access to Credit," January 12, 2022.

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 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.2 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.3 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.3 Recent immigrants may have trouble accessing credit in the U.S., even if they had a good credit history in their home country.3 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. Read our latest report to learn more about accessing and using alternative credit data. Access now 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 an estimated 96 percent of American adults — compared to 81 percent with conventional scores using traditional credit data. And the enhanced scoring capabilities could enable 6 million subprime applicants to qualify for prime or near-prime credit.3 The last word 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 about leveraging consumer permissioned data 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 Oliver Wyman (2022). Driving Growth With Greater Credit Access3 Ibid.

More than seven million Americans who are unbanked cite high account fees, insufficient funds to meet minimum balances and a lack of needed products and services as the main reasons for not having a checking or savings account.1 Credit unions understand that being unbanked comes at a steep cost and have turned their focus to developing products and strategies that prioritize financial inclusion — a movement to combat inequities in banking and better serve the financial needs of marginalized communities. In 2022, the House passed Expanding Financial Access for Underserved Communities Act to allow federal credit unions to add underserved areas to their fields of membership as a means of improving financial inclusion. “We believe diversity, inclusion, equity, belonging and accessibility has to be weaved into the strategic fabric of an organization [and its] culture," says Max Villaronga, President and Chief Executive Officer of Raiz Federal Credit Union. “When we don't participate in [diversity, equity and inclusion], we are complicit in essentially keeping people out of the banking system." For credit unions, driving financial inclusion starts with setting a vision that will leave a lasting legacy that includes fostering financial empowerment, closing the credit gap and building generational wealth among the communities they serve. Here's a roadmap for getting started. Best practices for engagement Establishing a set of best practices is the essential starting point for improving financial inclusion. The process begins with the mission statement and extends to all aspects of operations from hiring procedures to sponsorships and donations. Villaronga advocates three strategies for engagement: Engage the leadership team Conversations about financial inclusion need to start at the top. The C-suite must be willing to be honest about the barriers and willing to adopt changes that will make credit unions more inclusive. “[T]hese systemic barriers will exist until somebody deliberately moves them out of the way," Villaronga says. “The people who are feeling those barriers are not in the position to do the moving it's up to [CEOs and CFOs] to decide to do something to make a difference." Making a difference starts with choosing a leadership team that reflects the demographics of local communities. Case in point: At Raiz Federal Credit Union in El Paso, Texas, senior management and the board have LGBTQIA+ representation and include members from diverse racial and ethnic identities. The board of directors has also prioritized creating a pipeline that will attract more diverse talent to the board. “Many of [our board members] come from underserved backgrounds in our border community," Villaronga says. “This is a very personal journey for them because they can see themselves in the lives of the people we're serving." Build trust in underserved communities According to an FDIC Survey, “unbanked" U.S. households listed a lack of trust in financial institutions as a top reason for not having a bank account. And lack of access to a checking or savings account is most prominent among racial and ethnic minorities and low-income communities.2 Actions speak louder than words, according to Villaronga. Raiz Federal Credit Union uses diverse images in its advertising and provides information in both English and Spanish. The credit union was also awarded the Juntos Avanzamos (Together We Advance) designation from Inclusiv for its commitment to serving and empowering Hispanic communities by providing safe, affordable and relevant financial services. Villaronga believes that a designation like Juntos Avanzamos sends the message to the community that the credit union is committed to improving general financial literacy and pre-loan education, as well as reducing higher charge-offs and other barriers to accessing financial services that exist in lending and serving underserved communities. Dispel financial inclusion myths Among traditional financial institutions, myths about financial inclusion are widespread and include falsehoods that pricing products for marginalized communities are too challenging, reaching out is not profitable, and providing financial products to underserved markets is too risky. “Credit unions were really built to extend credit [and] were also originally established to serve consumers that were being ignored by the existing systems that were in place but those consumers are still being ignored today," Villaronga says. “Are those communities too risky to serve? Some companies are serving them [and] they would not be doing so if it was not profitable." Raiz Federal Credit Union offers several affordable loan products — from credit builder loans to citizenship loans and payday lender payoff loans along with credit cards — that allow members to build their credit scores and establish positive credit histories. Rather than pricing loans based on what the competition is charging, Villaronga calculates the fixed and variable costs, failure fraction and target return on assets to get a floor pricing per unit. The approach, he adds, allowed Raiz Federal Credit Union to report earnings of over 150 basis points in 2021 while maintaining a 12 percent capital ratio, proving that financial inclusion is good for the bottom line. “THE IDEA THAT YOU CANNOT [ACHIEVE FINANCIAL INCLUSION] IN A WAY THAT'S SAFE AND SOUND AND SATISFIES THE [NATIONAL CREDIT UNION ADMINISTRATION] IS TRULY A MYTH." - Max Villaronga, President and CEO, Raiz Federal Credit Union Partner for Success For credit unions, an important part of achieving financial inclusion goals is identifying partners that can help. Raiz Federal Credit Union set a goal to increase automated lending from 20 percent to 60 percent, but using a traditional loan origination program was insufficient to hit that target. A partnership with Experian allowed the credit union to access tools that allowed it to better identify non-traditional risks and opportunities, as well as develop more robust lending and optimized decision strategies. Experian launched Inclusion ForwardTM, an initiative to help boost financial inclusion and close the wealth gap, and support financial institutions by enhancing their inclusion approach by leveraging FCRA-regulated data sources (otherwise known as alternative data).3 In addition to providing a deeper view of unbanked and underbanked consumers and reducing friction and speed of decisioning through increased automation, Experian Lift PremiumTM uses income and employer data, social security and financial management insights — transaction behaviors that were historically credit invisible or unscorable — to help credit unions meet the needs of underserved markets and increase opportunities for inclusion. “This automation also allows us to reduce our fixed cost per unit — [and] it's a really big deal because this is not by little, but a lot," Villaronga says. “This lower cost to produce [a loan] allows us to improve our interest rates to underserved members, further creating an appealing value proposition that's in line with our financial inclusion strategy." Access our case study to learn more about how Experian can help grow your business with a frictionless digital prequalification experience. Access now 1Federal Reserve Bank of Cleveland (May 2022). Unbanked in America: A Review of Literature 2 Federal Deposit Insurance Corporation (December 2021). American Banks: Household use of Banking and Financial Services 3When 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

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

The preference for digital is here to stay, with consumers reporting that they are online 25% more today than a year ago. The explosive growth in remote work and e-commerce results in more transactions, and opportunities for online fraud are occurring. This new reality means that organizations of all types will face more and newer types of fraud risks. External fraud generally results from deceptive activity intended to produce financial gain that is carried out by an individual, a group of people or an entire organization. Fraudsters may prey on any organization or individual, regardless of the size or nature of their activities. The tactics used are becoming increasingly sophisticated, requiring a multilayered defense strategy. Fraud mitigation involves using tools to reduce the frequency or severity of these risks, ultimately protecting the bottom line and the future of the organization. Fraud impacts the bottom line and so much more According to the Federal Trade Commission, consumers reported losing more than $5.8 billion to fraud in 2021, a 70% increase over 2020. Another report places the losses much higher, with credit card fraud alone representing an estimated $9.3 billion. These costs extend beyond the face value of the theft to include fees and interest incurred, fines and legal fees, labor and investigation costs and external recovery expenses. Aside from dollar losses and direct costs, fraud can also pose legal risks that lead to fines and other legal actions and diminish credibility with regulators. Word of deceptive activities can also create risk for the brand and reputation. These factors can, in turn, result in a loss of market confidence, making it difficult to retain clients and engage new business. Leveraging fraud mitigation best practices As the future unfolds, three things are fairly certain: 1) The future is likely to bring more technological advances and, thereby, new ways of working and creating. 2) Fraudsters will continue to look for ways to exploit those opportunities. 3) The future is here, today. Organizations that want to remain competitive in the digital economy should make fraud mitigation and prevention an integral part of their operational strategy. Assess the risk environment While enhancing revenue opportunities, the global digital economy has increased the complexity of risk management. Be aware of situations that require people to enforce fraud risk policies. While informed, experienced people are powerful resources, it is important to automate routine decisions where you can and leverage people on the most challenging cases. It is also critical to consider that not every fraud risk aligns directly to losses. Consider touchpoints where information can be exposed that will later be used to commit fraud. Information that crooks attempt to glean from idle chatter during a customer service call can be a source of unexpected vulnerability. These activities can benefit from greater transparency and automated oversight. Create a tactical plan to prevent and handle fraud Leverage analytics wherever possible to streamline decisions and choose the right level of friction that’s appropriate for the risk, and palatable for good customers. Consumers and small businesses have come to expect a customized and frictionless experience. Employee productivity, and ultimately revenue growth, requires the ability to operate with speed and informed confidence. A viable fraud mitigation strategy should incorporate these goals seamlessly with operational objectives. If not, prevention and mitigation controls may be sidelined to get legitimate business done, creating inroads for fraudsters. Look for a partner who can apply the right friction to situations depending on your risk appetite and use existing data (including your internal data and their own data resources) to better identify individual consumers. This identification process can actually smooth the way for known consumers while providing the right protection against fraudsters and giving consumers who are new to your organization a sense of safety and security when logging in for the first time. It's equally important that everyone in your organization is working together to prevent fraud. Establish and document best practices and controls, beginning with fostering a workplace culture in which fraud mitigation is part of everyone's job. Empower and train all staff to identify and report suspicious activity and ensure they know how to raise concerns. Consider implementing ways to encourage open and swift communication, such as anonymous or confidential reporting channels. Stay vigilant and tap into resources for managing risks It is likely impossible to think of every threat your organization might face. Instead, think of fraud mitigation as an ongoing process to identify and isolate any suspected fraud fast — before the activity can develop into a major threat to the bottom line — and manage any fallout. Incorporating technology and robust data collection can fortify governance best practices. Technology can also help you perform the due diligence faster, ensuring compliance with Know Your Customer (KYC) and other regulations. As necessary, work with risk assessment consultants to get an objective, experienced view.  Learn more about fraud mitigation and fraud prevention services. Learn more  

What is elder abuse fraud? Financial abuse is reportedly the fastest-growing form of elder abuse, leaving many Americans vulnerable to theft scams, and putting businesses and other organizations on the frontlines to provide protection and help prevent fraud losses.   Financial elder abuse fraud occurs when someone illegally uses a senior’s money or other property. This can be someone they know, or a third party – like fraudsters who are perpetrating romance scams Older consumers and other vulnerable digital newbies were prime targets for this type of abuse during the start of the pandemic when many of them became active online for the first time or started transacting in new ways. This made them especially attractive targets for social engineering (when a fraudster manipulates a person to divulge confidential or private information) and account takeover fraud. While most of us have become used to life online (in fact, there’s been a 25% increase in online activity since the start of the pandemic), some seniors still have risky habits such as poor password maintenance, that can make them more attractive targets for fraudsters. What is the impact of elder abuse fraud? According to the FBI’s Internet Crime Complaint Center (IC3), elder abuse fraud cost Americans over the age of 60 more than $966 million in 2020. In addition to the direct cost to consumers, elder abuse fraud can leave organizations vulnerable to the fallout from data breaches via account takeover, and lost time and money spent helping seniors and other vulnerable Americans recoup their losses, reset accounts, and more. Further, the victim may associate the fraud with the bank, healthcare provider, or other businesses where the account was taken over and decide to stop utilizing that entity all together. How can organizations prevent elder abuse fraud? Preventing elder abuse fraud can take many forms. Organizations should start with a robust fraud management solution that can help prevent account takeover, first-party, synthetic identity fraud, and more. This platform should also include the ability to use data analysis to detect and flag sudden changes in financial behavior, online activities, and transaction locations that could indicate abuse or takeover of the account. With the right fraud strategy in place, organizations can help prevent fraud and build trust with older generations. Given that 95% of Baby Boomers cite security as the most important aspect of their online experience, this step is too important to miss.   To learn more about how Experian is helping organizations develop and maintain effective fraud and identity solutions, be sure to visit us or request a call. Contact us  

Rapid improvements in technology and the rise in online activity are driving higher consumer expectations for fast and frictionless digital experiences. And yet, only 50% of credit unions are executing on a digital strategy compared to 79% of banks.1 What can credit unions do to stand out from the competition and keep up with increasing consumer demands? 23% of consumers say their expectations for the digital experience have only somewhat or not at all been met.2 The answer lies in digital prequalification. With a frictionless digital prequalification solution, members can prequalify themselves online in real time before starting the formal application process. This puts members in the driver’s seat, allowing them to see their eligibility for credit offers and choose whether they’d like to proceed with the application. By delivering immediate feedback and offers to members online, credit unions can increase response rates, improve digital engagement and enhance the prequalification experience. Case Study: Achieving growth through a seamless digital prequalification experience Gather Federal Credit Union is the largest neighbor-island credit union in Hawaii, providing financial products and services to more than 35,000 members. Wanting to grow more loans while providing members with a seamless and efficient online experience, the credit union looked for a comprehensive solution that could improve their decisioning and enhance their prequalification strategy. They partnered with Experian and Rate Reset to implement a frictionless digital experience that enables members to opt-in for prequalified offers. Leveraging the power of Experian’s PowerCurve® and Rate Reset’s The ButtonTM, Gather had flexible access to consumer data, attributes and scores, allowing them to verify user identities and match members with loan products before their application formally went through the credit underwriting process. By gaining a better understanding of which credit options they prequalified for, members were able to opt-in instantly, creating a faster, more personalized digital prequalification experience. Within three weeks of implementation, Gather booked over $600,000 in new personal loans and credit cards. Additionally, of all the applicants that passed the credit union’s credit prequalification criteria, 54% accepted their offer and received a loan. “With a few clicks, members and non-members alike can instantly prequalify themselves for a loan. We’re extremely pleased with this offering, which has enabled us to extend our reach and grow the Gather community,” said Justin Ganaden, Executive Vice President, Gather Federal Credit Union. Read the full case study to learn more about how Experian can help grow your business with a frictionless digital prequalification experience. Download the full case study 1 https://www.big-fintech.com/Media/BIG-News/ArticleID/779/New-Digital-Banking-Platform Digital Transformation Revolution – Is it Leaving Credit Unions Behind? 2 2022 Global Insights Report, Experian, 2022.

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

Even before the COVID-19 pandemic, many Americans lacked equal access to financial products and services — from tapping into affordable banking services to credit cards to financing a home purchase. The global pandemic likely exacerbated those existing issues and inequalities. That reality makes financial inclusion — a concerted effort to make financial products and services affordable and accessible to all consumers — more crucial than ever. The playing field wasn't level before the pandemic The Federal Reserve reported that in 2019, Black and Hispanic/Latino families had median wealth that was just 13 to 19 percent of that of White families — $24,100 and $36,100, respectively, compared to $188,200 for White families. That inequity is also reflected in credit score disparities. While credit scores, income, and wealth aren't synonymous, the traditional credit scoring system leads marginalized communities to be disproportionately labeled unscoreable or credit invisible, and face challenges in accessing credit. New research from Experian shows that in over 200 cities, there can be more than a 100-point difference in credit scores between neighborhoods — often within just a few miles from each other. Marginalized communities bore the financial brunt Minority communities were also disproportionately impacted by COVID-19 in terms of infections, job losses, and financial hardship. In mid-2020, the Economic Policy Institute (EPI) reported Black and Hispanic/Latino workers were more likely than White workers to have lost their jobs or to be classified as essential workers — leading to economic or health insecurity. Government initiatives — including the Coronavirus Aid, Relief, and Economic Security (CARES) Act, the Paycheck Protection Program (PPP) and the American Rescue Plan — created expanded unemployment benefits, paused loan payments, eviction moratoriums, and direct cash payments. These helped consumers' immediate financial well-being. The National Bureau of Economic Research found that, on average, U.S. households spent approximately 40 percent of their first two stimulus checks, with about 30 percent used for savings and another 30 percent used to pay down debt. In some communities highly affected by COVID-19, consumers were able to pay down nearly 40 percent of their credit card balances and close more than 9 percent of their bank card accounts, according to recent data. Stimulus payments have been credited with reducing childhood poverty and helping families save for financial emergencies. That being said, people on the upper end of the income scale were able to improve their financial situation even more. Their wealth grew at a much faster pace than people at the bottom end of the income distribution scale, according to data from the Federal Reserve. How the pandemic deepened financial exclusion Although hiring has picked up in low-wage industries, research indicates that low-wage jobs have been the slowest to return. According to a survey by the Pew Research Center, among respondents who said their financial situation worsened during the pandemic, 44 percent believe it will take three years or more to get back to where they were a year ago. About 10 percent don't think their finances will ever recover. Recent Experian data shows that consumers in certain communities that were already struggling to pay their debts fell into an even bigger hole. These consumers missed payments on 56 percent more accounts in the period between spring 2019 to spring 2020 compared to the year prior. Credit scores in these neighborhoods fell by an average of over 20 points during the first 18 months of COVID-19. That being said, U.S. consumers overall increased their median credit scores by an average of 21 points from the end of 2019 to the end of 2021. When consumers with deteriorating credit encounter financial stresses, often their only recourse is to pile on additional debt. Even worse, those who can't access traditional credit often turn to alternative credit arrangements, such as short-term loans, which may charge significantly higher interest rates. READ MORE: More Than a Score: The Case for Financial Inclusion What can the financial sector do? Without access to affordable financial services and products, subprime or credit invisible consumers may not get approved for a mortgage or car loan — things that might come much easier for consumers with better scores. This is just one reason why financial inclusion is so important — and why financial services companies have a big role to play in driving it. One place to start is by taking a broader view of what makes a creditworthy consumer. In addition to traditional credit scoring models, new tools can leverage artificial intelligence and machine learning, along with alternative data, to analyze the creditworthiness of consumers. By qualifying for credit, more consumers can access affordable mortgages, car loans, business loans and insurance - freeing up money for other expenses and allowing them to grow their wealth.. READ MORE: What Is Alternative and Non-Traditional Data? Last word Marginalized communities were already struggling economically before the pandemic, and the impact of COVID-19 has made the wealth disparities worse. With the pandemic waning, now is the time for financial institutions to take action on financial inclusion. Not only does it help improve your customers' lives and make them better prepared for the next crisis, but it also fuels your business's growth and bottom line.

There's no magic solution to undoing the decades of policies and prejudices that have kept certain communities unable to fully access our financial and credit systems. But you can take steps to address previous wrongs, increase financial inclusion and help underserved communities. If you want to engage consumers and keep them engaged, you could start with the following four areas of focus. 1. Find ways to build trust Historical practices and continued discriminatory behavior have created justifiable distrust of financial institutions among some consumers. In February 2022, Experian surveyed more than 1,000 consumers to better understand the needs and barriers of underserved communities. The respondents came from varying incomes, ethnicity and age ranges. Fewer than half of all the consumers (47 percent) said they trusted their bank's personal finance advice and information, and that dropped to 41 percent among Black Americans. In a follow-up webinar discussion of financial growth opportunities that benefitted underserved communities, we found that many financial institutions saw a connection between their financial inclusion efforts and building trust with customers and communities. Here is a sample question and a breakdown of the primary responses: What do you think is the greatest business advantage of executing financial inclusion in your financial institution or business?1 Building trust and retention with customers and communities (78%) Increasing revenue by expanding to new markets (6%) Enhancing our brand and commitment to DEI (14%) Staying in alignment with regulator and compliance guidelines (2%) Organizations may want to approach financial inclusion in different ways depending on their unique histories and communities. But setting quantifiable goals and creating a roadmap for your efforts is a good place to start. 2. Highlight data privacy and mobile access If you want to win over new customers, you'll need to address their most pressing needs and desires. Consumers' top four considerations when signing up for a new account were consistent, but the specific results varied by race. Keep this in mind as you consider messaging around the security and privacy measures. Also, consider how underserved communities might access your online services. Having an accessible and intuitive mobile app or mobile-friendly website is important and likely carries even more weight with these groups. According to the Pew Research Center, as of 2021, around a quarter of Hispanic/Latino and 17% of Black Americans are smartphone-dependent — meaning they have a smartphone but don't have broadband access at home. Low-income and minority communities are also less likely to live near bank branches or ATMs. 3. Offer lower rates and fees Low rates and fees are also a top priority across the board — everyone likes to save money. However, fewer Black and Hispanic households have $1,000 in savings or more compared to white households, which could make additional savings opportunities especially important. There have been several recent examples of large banks and credit unions eliminating overdraft fees. And the Bank On National Account Standards can be a helpful framework if you offer demand deposit accounts. Lowering interest rates on credit products can be more challenging, particularly when consumers don't have a thick (or any) credit file. But by integrating expanded FCRA-regulated data sources and new scoring models, such as Experian's Lift PremiumTM, creditors can score more applicants and potentially offer them more favorable terms. 4. Leverage credit education tools and messaging For consumers who've had negative credit experiences, are new to credit, or are recent immigrants with little understanding of the U.S. credit system, building and using credit can feel daunting. About 80% of women have little or no confidence in getting approved for credit or worry that applying could hurt them further. Only 20% of consumers who make less than $35,000 a year say they're "extremely" or "very" confident they'll be approved for credit. While most consumers haven't used credit education tools before, they're willing to try. More than 60 percent of Black and Hispanic respondents said they're likely to sign up for free credit education tools and resources from their banks. Offering these tools could be an opportunity to strengthen trust and help consumers build credit, which can also make it easier for them to qualify for financial products and services in the future. Moving forward with financial inclusion Broadening access to credit can be an important part of financial inclusion, and financial institutions can grow by expanding outreach to underserved communities. However, the relationship must be built on trust, security, and offerings that meet these consumers' needs. Through our Inclusion Forward™ initiative, Experian can support your financial inclusion goals — helping you empower underserved communities by helping them grow their financial futures. Learn more about Experian financial inclusion solutions and financial inclusion tools.

To drive profitable growth and customer retention in today’s highly competitive landscape, businesses must create long-term value for consumers, starting with their initial engagement. A successful onboarding experience would encourage 46% of consumers1 to increase their investments in a product or service. While many organizations have embraced digital transformation to meet evolving consumer demands, a truly exceptional onboarding experience requires a flexible, data-driven solution that ensures each step of customer acquisition in financial services is as quick, seamless, and cohesive as possible. Otherwise, financial institutions may risk losing potential customers to competitors that can offer a better experience. Here are some of the benefits of implementing a flexible, data-driven decisioning platform: Greater efficiency From processing a consumer’s application to verifying their identity, lenders have historically completed these tasks manually, which can add days, if not weeks, to the onboarding process. Not only does this negatively impact the customer experience, but it also takes resources away from other meaningful work. An agile decisioning platform can automate these tedious tasks and accelerate the customer onboarding process, leading to increased efficiency, improved productivity, and lower acquisition costs2. Reduced fraud and risk Onboarding customers quickly is just as important as ensuring fraudsters are stopped early in the process, especially with the rise of cybercrime. However, only 23% of consumers are very confident that companies are taking steps to secure them online. With a layered digital identity verification solution, financial institutions can validate and verify an applicant’s personal information in real time to identify legitimate customers, mitigate fraud, and pursue growth confidently. Increased acceptance rates Today’s consumers demand instant responses and easy experiences when engaging with businesses, and their expectations around onboarding are no different. Traditional processes that take longer and require heavy documentation, greater amounts of information, and continuous back and forth between parties often result in significant customer dropout. In fact, 40% of digital banking consumers3 abandon opening an account online due to lengthy applications. With a flexible solution powered by real-time data and cutting-edge technology, financial institutions can reduce this friction and drive credit decisions faster, leading to more approvals, improved profitability, and higher customer satisfaction. Having a proper customer onboarding strategy in place is crucial to achieving higher acceptance and retention rates. To learn about how Experian can help you optimize your customer acquisition strategy, visit us and be sure to check out our latest infographic. View infographic Visit us 1 The Manifest, Customer Onboarding Strategy: A Guide to Retain Customers, April 2021. 2 Deloitte, Inside magazine issue 16, 2017. 3 The Financial Brand, How Banks Can Increase Their New Loan Business 100%, 2021.