As telecommunications providers race to modernize networks, enable 5G, and manage soaring data volumes, they also face unprecedented challenges – from tightening regulations and economic uncertainty to increasing customer churn and fraud. In this climate, artificial intelligence (AI) in telecommunications isn’t just a buzzword; it’s becoming a cornerstone for strategic survival and competitive differentiation. But the promise of AI is only as powerful as the data that fuels it and the decisions it enables. In this blog post, we explore the pressing challenges telecom providers face, including the evolving economic and regulatory landscape, and how Experian’s telecom solutions are uniquely equipped to support telecom leaders using advanced analytics, data-driven decisioning, and fraud prevention solutions. The current state of telecommunications: a perfect storm Telecom providers are under pressure from multiple angles: Shrinking ARPU and rising competition Average Revenue Per User (ARPU) is declining in many regions as price competition increases and Over-the-Top (OTT) services continue to displace traditional service lines. In North America alone, mobile ARPU has dropped by more than 8% in recent years1. Customer experience expectations Modern customers expect seamless digital experiences. Yet, legacy systems and data silos often prevent real-time personalization and service optimization, increasing churn risk2. Regulatory scrutiny and data privacy Telecoms must comply with a complex web of data protection and privacy regulations (GDPR, CCPA, KYC, etc.) while also navigating policies around fair access, net neutrality, and cross-border data flow3. Fraud and credit risk The growing prevalence of synthetic identity fraud and account takeovers demands more robust, intelligent fraud prevention and credit risk strategies, especially in prepaid and postpaid customer segments. In 2023, synthetic identity fraud caused more than $2.6 billion in financial damage globally4. The role of advanced analytics and AI in telecommunications Against this backdrop, AI and telecommunications are becoming increasingly intertwined. By leveraging AI and advanced data analytics, telecom operators can move from reactive to proactive operations. This includes: Churn prediction and mitigation using machine learning. Network optimization through AI-driven traffic forecasting. Fraud detection via real-time anomaly detection models. Credit risk modeling with AI-powered segmentation. However, not all AI solutions deliver the same level of impact. For telecom providers, challenges like fragmented data ecosystems, model governance, and the need for explainable outcomes—especially in highly regulated environments – can limit AI’s full potential. Only Experian can: solving telecom’s data and decisioning challenges This is where Experian stands out. As a trusted leader in data and decisioning, Experian provides telecoms with scalable, regulatory-compliant tools that can help accelerate digital transformation. Purpose-built telecom solutions Our telecom solutions are designed specifically to address sector pain points like fraud, credit risk, and customer churn. Whether you're a traditional mobile network operator (MNO) or a disruptive MVNO, Experian can help you make smarter decisions—faster.'Our telecom solutions are designed specifically to address sector pain points like fraud, credit risk, and customer churn. Whether you're a traditional mobile network operator (MNO) or a disruptive MVNO, Experian can help you make smarter decisions—faster. Advanced analytics expertise Experian helps telecoms harness the power of advanced analytics to make sense of complex, high-volume data. From customer segmentation to behavioral modeling, our tools bring clarity and actionability that unlock new value from existing data. Predictive modeling solutions that drive results With our specialized predictive modeling solutions, telecoms can implement next-best-action strategies across acquisition, onboarding, and retention. These models are tested, explainable, and auditable—ensuring compliance while delivering ROI. Robust fraud and identity capabilities With rising fraud threats including synthetic identity and account takeovers, Experian can deliver AI-enhanced, layered fraud prevention strategies. Our tools detect anomalies in real-time, leveraging fraud analytics and behavior-based risk signals, helping you reduce losses without adding friction to the customer experience. Scalable, future-ready advanced analytics solutions Our full suite of advanced analytics solutions enables telecoms to future-proof their operations, ensuring they stay compliant while innovating faster than competitors. Data-driven innovation: use cases Here’s how telecoms are already seeing ROI with Experian: A leading North American communications company retained 30% of revenue by implementing Experian Optimize to improve the growth and retention of customers. A multichannel media company used Experian’s solutions to drive a customer-focused approach to campaign planning resulting in a 35% increase in customer revenue without increasing marketing spend. A European wireless telecom provider optimized collections allocations, segmenting customers by demographic and behavioral groups to provide a higher rate of reconnections. Results included a 10% increase in net customer value, a 15% increase in balance collected and a 9% increase in collections agency earnings. Navigating what’s next in telecom The future of AI in telecommunications is promising for providers who can bridge the gap between AI aspiration and execution. Telecommunication providers must not only adopt the right technologies but also partner with trusted data stewards who understand the regulatory, economic, and operational landscape. We’re that partner. At Experian, we help telecom leaders go beyond surface-level insights to power meaningful outcomes, whether that’s to drive smarter acquisition, stronger client retention and faster innovation. Our solutions are grounded in trusted data and measurable outcomes. The pressure on telecoms isn’t going away. But with the right AI-powered tools and data-driven strategies, providers can shift from playing defense to leading with innovation. Now is the time to rethink how you approach data, risk, and customer engagement. Ready to see how Experian can help your telecom organization unlock the power of AI and advanced analytics? Explore our telecom solutions or contact an Experian expert to start transforming your strategy today. Learn more Partner with our team

The necessity of integrated feature management Feature engineering is essential for financial institutions to identify valuable features that provide significant insights and predictive power in various analytics applications. By integrating feature engineering into the feature lifecycle, organizations can convert raw data into more accurate and value-driving features, better manage features for audit purposes and compliance efforts, and build higher-performing models. At Experian, we have developed a unified feature engineering solution that integrates capabilities across various tools such as the Ascend Analytical Sandbox™ and Ascend Ops™. This comprehensive approach streamlines the feature engineering process, making it more efficient and effective in supporting the complete feature lifecycle. The challenges in feature engineering 54% of source data used by financial institutions for credit decisioning is not model-building ready.1 Financial institutions need access to high-quality data sources and the ability to modify and combine data to make more profitable data-driven decisions. In addition, organizations need the necessary tools to solve the myriad of challenges involved with feature engineering. These challenges include: Costs: Sourcing and centralizing data can be expensive, and managing and updating data definitions for engineering and analytics is costly. Collaboration: Managing a centralized feature library is difficult and often skipped. As AI and analytics teams become more complex across the enterprise, maintaining and governing feature definitions in a centralized library is a must-have. Inconsistencies: Calculating features can vary. Different calculations in development and production use cases across the lending lifecycle create model risks and compliance issues. Governance risks: Tracking lineage of data definitions is important to avoid elevating risks. Data engineers and scientists need to visualize upstream and downstream impacts as they modify feature definitions. Resources: Teams often have skills gaps and require additional expertise, as they may lack an understanding of automated credit reports amongst resources. Integration: Evaluating and integrating features into the analytics lifecycle is difficult. This can hinder understanding of the value of models and strategies throughout the lending lifecycle and create friction at deployment. Experian Feature Builder: a comprehensive solution Experian Feature Builder is a modern, integrated custom feature solution that combines development, deployment, and management technologies. It accelerates the feature lifecycle through efficient data management and streamlined end-to-end workflows. Users can access the Ascend Analytical Sandbox for custom feature development and seamless connection to Ascend Ops for deployment and ongoing management. This integration also significantly enhances compliance and governance by adding a layer of visibility into feature performance, thereby reducing risks through feature monitoring. Leveraging best-in-class technologies Feature Builder Notebooks enables users to review feature code in Jupyter Notebooks within Ascend Analytical Sandbox, explore data, execute small sample feature calculations, examine feature distributions, edit feature code, and register to the feature library. Feature Builder Studio enables users to review and manage features in the feature library, set up feature calculation jobs, and define feature sets for deployment. Users can also add Ascend Ops to deploy to production with little to no friction. Supporting advanced analytics in consumer credit with integrated feature management Experian Feature Builder provides a centralized feature library, ultimately improving time to market and decisions to extend credit while managing default and fraud risks. Centralized access to data sources used in custom features and intermediation of third-party data sourcing. Advanced lineage tracking for a clear view of the history of upstream and downstream feature dependencies for governance purposes. Streamlined feature registry for built-in version management and tracking with feature correlations and distributions. Key statistical reporting for out-of-the-box data visualizations and monitoring of feature correlations and distributions. Comprehensive feature lifecycle support through integration with Ascend Analytical Sandbox for rapid analytics use case iteration and experimentation as well as production-grade execution and deployment with Ascend Ops. The future of feature engineering Understanding how essential feature engineering is in producing value-driving features, managing and monitoring features for audit and compliance purposes, and more predictive and high-performing models is pivotal to maintaining competitiveness in the financial services industry. Experian Feature Builder is the future of feature engineering. With integration for advanced analytics, model development through deployment, and enhanced feature management capabilities supporting compliance and governance, Experian Feature Builder supports the complete feature lifecycle. To learn more about how Experian Feature Builder can revolutionize your feature engineering, please visit our website and book a demo with your local Experian sales team. Learn more about Feature Builder 1 Experian research 2023

Lending institutions need to use the right business strategies to win more business while avoiding unnecessary risk, especially regarding lending policies. A recent study revealed that 48% of American loan applicants have been denied over the past year, with 14% facing multiple rejections. Additionally, 14% of rejected applicants felt pressured to seek alternative financing like cash advances or payday loans.1 These statistics highlight the need for financial institutions to offer attractive loan options to stay ahead in the industry. Understanding loan loss analysis Loan loss analysis is a powerful tool that helps lenders gain insights into why applicants book loans elsewhere. Despite efforts to target the right consumers at the right time with optimal offers, applicants sometimes choose to book their loans with different institutions. The lack of visibility into where these lost loans are booked can hinder a lender’s ability to improve their offerings and validate existing policies. By leveraging loan loss analysis, lenders can turn valuable data into actionable insights, creating more profitable business opportunities throughout the entire customer lifecycle. Gaining deep consumer insights Loan loss analysis provides visibility into various aspects of competitors’ loan characteristics, such as: Type of financial institution: Identifying whether applicants prefer banks, credit unions or finance companies can help lenders tailor their offerings. Average loan amount: Understanding how much other institutions offer allows lenders to adjust their loan amounts to be more competitive. Interest rates: Comparing interest rates with competitors helps lenders calibrate their rates to attract more business. Loan term length: Knowing the term lengths offered by competitors can inform decisions on loan terms to make them more appealing. Average risk score: Determining the risk scores of loans booked elsewhere helps lenders optimize their policies to maximize earning potential without increasing default risk. Making profitable decisions with business intelligence Experian's loan loss analysis solution, Ascend Intelligence Services™ Foresight, offers comprehensive insights to help lenders: Book more loans Increase profitability Enhance acquisition strategies Improve customer retention Optimize marketing spend By determining where applicants ultimately book their loans, lenders can unlock deep insights into competitors’ loan characteristics, leading to more intelligent business decisions. Read our latest e-book to discover how loan loss analysis can help you gain visibility into competitor offerings, improve your lending policies, book higher-performing loans, and minimize portfolio risk. Read the e-book Visit our website 1 Bankrate, February 2025. Survey: Almost half of loan applicants have been denied over the past 12 months.

Customer retention is crucial for lenders to maximize lifetime value, especially during economic uncertainty. Increasing customer retention rates by just 5% can boost profits by 25% to 95%. However, many lenders struggle with loyalty, as seen in Q2 2024 when mortgage servicers’ retention rates for refinances dropped to 20%, the second lowest in 17 years. Nonbanks and banks also saw significant declines. This is due to increased competition, changing economic conditions, and a lack of personalization. Key strategies for improving customer retention Lenders can improve retention by leveraging data for personalization, maintaining consistent communication, offering loyalty rewards, and utilizing retention triggers. Leverage data for personalization. Use customer data to offer tailored products and refinancing options based on financial behaviors. Using credit attributes, trended data and alternative credit data (alternative financial services data,  cashflow attributes, etc.) can help provide deeper insights of your customers. Maintain consistent communication. Keep customers informed with regular updates about interest rate changes or new loan products. Use a variety of communication channels, including email and in-app messaging, to ensure customers are kept in the loop. Ensure your customer service team is always available and responsive, offering clear answers to any financial concerns. Offer loyalty rewards. Develop programs that reward repeat business and referrals. Offer special rates or discounts for returning customers or for those who refer friends and family to your services. Increase customer lifetime value (LTV) by offering additional services like financial planning or credit score monitoring. Utilize retention triggers. Identify key events for engagement with automated retention triggers. For example, a borrower who has a mortgage with a fixed rate may be less likely to consider refinancing unless prompted. Experian’s Retention TriggersSM can notify lenders when refinancing might be beneficial to their customer, offering them personalized incentives or new product options at the right time. Why Experian’s Retention Triggers? By integrating Experian’s Retention Triggers, lenders can keep borrowers engaged, increase retention, and boost profitability even in tough economic times. Advanced data insights: Gain deeper insights into your customers’ behavior to identify those at risk of leaving and take proactive action. Personalized engagement: Automate personalized communications based on customer behaviors, ensuring timely engagement. Increased revenue: By offering personalized, timely and relevant offers, you can increase the likelihood of retaining your customers and growing your revenue. Make customer retention a priority In today’s challenging economic climate, lenders who focus on personalized experiences, consistent communication, and relevant offers will stand out and retain borrowers. Leverage tools like Experian’s Retention Triggers to proactively engage customers, reduce churn, and foster long-term relationships for increased profitability and success. Learn more

Loan loss analysis helps financial institutions identify the characteristics and performance of loans that have been lost to competitors.

GenAI is pushing financial institutions to focus on improving efficiency, productivity, and time to value during the modeling lifecycle. Experian Assistant provides robust tools for data exploration, model building, deployment, and performance monitoring, allowing users to drive better decision-making.

Consumers are experiencing the highest loan rejection rates in a decade, driven by strict lending standards.1 While crucial for mitigating risk, these measures can also limit growth opportunities for financial institutions. Our latest one pager explores how cashflow data, obtained from consumer-permissioned transaction data, empowers lenders with unique insights into consumers’ financial health, enabling them to expand their portfolios while managing risk effectively. Read the full one pager to learn how cashflow data can help you make smarter, more confident lending decisions. Access one pager 12024 Q4 Lending Conditions Chartbook, Experian.

While many industry pundits are assessing how macroeconomic changes may impact the future of the automotive market, recent data suggests consumers tend to stick to specific fuel types. According to Experian’s Automotive Market Trends Report: Q4 2024, over the last 12 months, 77.5% of electric vehicle (EV) owners replaced their EV with another one, with 15.6% returning to gas-powered vehicles. Meanwhile, 82.2% of gas vehicle owners replaced it with the same fuel type, while only 4.7% made the switch to electric. It’s important for professionals to recognize that most consumers tend to replace their vehicles with the same fuel type. Additionally, knowing who is making these purchases and the types of vehicles being registered allows better anticipation for consumer needs and ultimately enhances the buying experience while fostering consumer loyalty. Breaking down fuel types by generation Through Q4 2024, Baby Boomers predominantly registered new gasoline vehicles, accounting for 74.7% of their choices, while 15.9% opted for hybrids and 6.6% chose EVs. Millennials showed a similar trend, with 69.2% registering gas vehicles, followed by 15.1% selecting hybrids and 12.5% choosing EVs. Gen Z also favored gasoline vehicles at 74.0%, with hybrids making up 14.3% and EVs at 9.1% of their registrations. Although gasoline vehicles account for the majority of new registrations, EVs and hybrids are steadily gaining ground, particularly among the younger generations who are drawn to advanced features that align with their preferences. This will likely play a role in shaping the future of vehicle registrations as more gas alternative models hit the market and consumers make the switch. To learn more about vehicle market trends, view the full Automotive Market Trends Report: Q4 2024 presentation on demand.

Many organizations remain committed to financial inclusion to create better outcomes for underrepresented consumers and small businesses by unlocking barriers to financial well-being and closing the wealth gap. Organizations like credit unions, Community Development Financial Institutions (CDFIs), and Minority Deposit Institutions (MDIs) live by these values. These lenders work hard to ensure these values are reflected in the products and services they offer and in how they attract and interact with customers. While funding from the federal government is being scaled back for many of these community-based financial institutions, Experian is scaling up! We're still here to support CDFIs, Credit Unions, and their members, along their financial inclusion journey. The cross-walk between DEIB and financial inclusion Although Diversity, Equity, Inclusion and Belonging (DEIB) and financial inclusion involve different strategies, there’s an undeniable connection that should ultimately be tied to a business’s overall goal and mission. The communities that are historically underrepresented and underpaid in the workforce – including Black Americans, Hispanic/Latinos, and rural white Americans – also tend to be marginalized by the established financial system. Financial institutions that work to address the inequities within their organizations and promote financial inclusion may find that these efforts complement each other. DEIB policies help promote and support individuals and groups regardless of their backgrounds or differences. While financial inclusion is less specific to a company or organization, instead it describes the strategic approach and efforts that allow people to affordably and readily access financial products, services, and systems. The impact of financial inclusion Lenders can promote financial inclusion in different ways. A bank can change the requirements or fees for one of its accounts to better align with the needs of people who are currently unbanked. Or it can offer a solution to help people who are credit invisible, or unscoreable by conventional credit scoring models, establish their credit files for the first time. Financial institutions also use non-traditional data scoring to lend to applicants that conventional scoring models can’t score. By incorporating alternative credit data[1] (also known as expanded FCRA-regulated data) into their marketing and underwriting, lenders can expand their lending universe without taking on additional risk. Financial inclusion efforts for all Experian is a champion of financial inclusion by supporting both financial institutions and consumers. Through our Inclusion Forward – Experian Empowering Opportunities™ initiative, we work directly with lenders to reach underserved communities and extend greater credit access to consumers. We also offer various tools to help consumers build and understand their credit, and to help financial institutions reach underrepresented communities. We provide individuals with everything from financial inclusion solutions to literacy education to insights about their own financial profile, along with ways to help underrepresented communities improve their financial wellness.* One way that we are doing this is through our consumer programs called Experian Go® and Experian Boost® –that are available for free through the Experian app. These first-of-their-kind programs work together to help consumers improve their credit profile. Experian Go helps individuals establish a credit file, while Experian Boost assists with adding tradelines to an existing credit file. For example, with Experian Boost, individuals can connect positive payments to utility, rent, streaming services, and other accounts to improve their credit scores. Membership with Experian helps consumers monitor their credit, manage their money, and find ways to save money, including shopping for insurance. In fact, consumers saved an average of $828 per year when they switched and saved through Experian Insurance Marketplace.[2] Working together to create financial empowerment 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 financial institutions like credit unions, CDFIs and MDIs take steps every day to drive financial inclusion and help underrepresented communities. These values are a part of their business DNA, and Experian is here to help keep their legacy alive. Whether you’ve established your strategy or need help with implementation, we can help you enhance your financial inclusion efforts. Learn more about our helpful solutions. Experian will point you in the right direction to business growth. Visit our website [1] Using Alternative Credit Data for Credit Underwriting. [2] Experian research. *Experian Boost: Results will vary. Not all payments are boost-eligible. Some users may not receive an improved score or approval odds. Not all lenders use Experian credit files, and not all lenders use scores impacted by Experian Boost. Learn more.

In the latest episode of "The Chrisman Commentary" podcast, Experian experts Ken Tromer, Director, Mortgage Market Engagement, and Ted Wentzel, Senior Product Marketing Manager, talk about why price transparency is important in the verification process, and how Experian Verify ensures it. Listen to the full episode for all the details and tune in to the previous episode to learn more about reducing mortgage pipeline fallout and improving loan pull-through rate. Listen to podcast

While CUVs and SUVs continue to dominate the market, sedans remain a popular choice among consumers. According to Experian’s Automotive Consumer Trends Report: Q4 2024, sedans accounted for 18.4% of new retail registrations and 36.9% of used. Comparatively, CUVs/SUVs came in at 59.3% for new and 38.6% for used. For retail sedan registrations, the Toyota Camry made up the most market share for both new and used in the last 12 months, coming in at 10.5% and 6.0%, respectively. Meanwhile, the Honda Civic came in a close second for new sedan registrations at 10.1% and the Honda Accord followed closely for used at 5.9%. Knowing which sedan models are leading in registrations is important for professionals as it helps them understand evolving consumer preferences, enhance marketing strategies, and make informed inventory decisions. Understanding the key generations fueling the sedan segment When examining generational interest in this vehicle segment, data found Gen Z and Millennials over-indexed in new retail sedan registrations. In the past 12 months, Gen Z represented 12.4% of new retail sedan registrations, while their total new retail registration was 8.2%. Millennials had 27.3% of sedan registrations out of 27% total registrations. Understanding who is purchasing and what models they’re gravitating towards can unlock valuable insights as professionals craft their next move and position themselves one step ahead in a competitive market. To learn more about sedan insights, view the full Automotive Consumer Trends Report: Q4 2024 presentation.

Fake IDs have been around for decades, but today’s fraudsters aren’t just printing counterfeit driver’s licenses — they’re using artificial intelligence (AI) to create synthetic identities. These AI fake IDs bypass traditional security checks, making it harder for businesses to distinguish real customers from fraudsters. To stay ahead, organizations need to rethink their fraud prevention solutions and invest in advanced tools to stop bad actors before they gain access. The growing threat of AI Fake IDs   AI-generated IDs aren’t just a problem for bars and nightclubs; they’re a serious risk across industries. Fraudsters use AI to generate high-quality fake government-issued IDs, complete with real-looking holograms and barcodes. These fake IDs can be used to commit financial fraud, apply for loans or even launder money. Emerging services like OnlyFake are making AI-generated fake IDs accessible. For $15, users can generate realistic government-issued IDs that can bypass identity verification checks, including Know Your Customer (KYC) processes on major cryptocurrency exchanges.1 Who’s at risk? AI-driven identity fraud is a growing problem for: Financial services – Fraudsters use AI-generated IDs to open bank accounts, apply for loans and commit credit card fraud. Without strong identity verification and fraud detection, banks may unknowingly approve fraudulent applications. E-commerce and retail – Fake accounts enable fraudsters to make unauthorized purchases, exploit return policies and commit chargeback fraud. Businesses relying on outdated identity verification methods are especially vulnerable. Healthcare and insurance – Fraudsters use fake identities to access medical services, prescription drugs or insurance benefits, creating both financial and compliance risks. The rise of synthetic ID fraud Fraudsters don’t just stop at creating fake IDs — they take it a step further by combining real and fake information to create entirely new identities. This is known as synthetic ID fraud, a rapidly growing threat in the digital economy. Unlike traditional identity theft, where a criminal steals an existing person’s information, synthetic identity fraud involves fabricating an identity that has no real-world counterpart. This makes detection more difficult, as there’s no individual to report fraudulent activity. Without strong synthetic fraud detection measures in place, businesses may unknowingly approve loans, credit cards or accounts for these fake identities. The deepfake threat AI-powered fraud isn’t limited to generating fake physical IDs. Fraudsters are also using deepfake technology to impersonate real people. With advanced AI, they can create hyper-realistic photos, videos and voice recordings to bypass facial recognition and biometric verification. For businesses relying on ID document scans and video verification, this can be a serious problem. Fraudsters can: Use AI-generated faces to create entirely fake identities that appear legitimate Manipulate real customer videos to pass live identity checks Clone voices to trick call centers and voice authentication systems As deepfake technology improves, businesses need fraud prevention solutions that go beyond traditional ID verification. AI-powered synthetic fraud detection can analyze biometric inconsistencies, detect signs of image manipulation and flag suspicious behavior. How businesses can combat AI fake ID fraud Stopping AI-powered fraud requires more than just traditional ID checks. Businesses need to upgrade their fraud defenses with identity solutions that use multidimensional data, advanced analytics and machine learning to verify identities in real time. Here’s how: Leverage AI-powered fraud detection – The same AI capabilities that fraudsters use can also be used against them. Identity verification systems powered by machine learning can detect anomalies in ID documents, biometrics and user behavior. Implement robust KYC solutions – KYC protocols help businesses verify customer identities more accurately. Enhanced KYC solutions use multi-layered authentication methods to detect fraudulent applications before they’re approved. Adopt real-time fraud prevention solutions – Businesses should invest in fraud prevention solutions that analyze transaction patterns and device intelligence to flag suspicious activity. Strengthen synthetic identity fraud detection – Detecting synthetic identities requires a combination of behavioral analytics, document verification and cross-industry data matching. Advanced synthetic fraud detection tools can help businesses identify and block synthetic identities. Stay ahead of AI fraudsters AI-generated fake IDs and synthetic identities are evolving, but businesses don’t have to be caught off guard. By investing in identity solutions that leverage AI-driven fraud detection, businesses can protect themselves from costly fraud schemes while ensuring a seamless experience for legitimate customers. At Experian, we combine cutting-edge fraud prevention, KYC and authentication solutions to help businesses detect and prevent AI-generated fake ID and synthetic ID fraud before they cause damage. Our advanced analytics, machine learning models and real-time data insights provide the intelligence businesses need to outsmart fraudsters. Learn more *This article includes content created by an AI language model and is intended to provide general information. 1 https://www.404media.co/inside-the-underground-site-where-ai-neural-networks-churns-out-fake-ids-onlyfake/

In today's competitive market, expanding your organization’s customer base can be a daunting task. Limited marketing budgets, high acquisition costs, and the pressure of financial inclusion initiatives can lead to poor response rates and make it challenging to reach the right consumers. If your prescreen policies are too conservative, you might miss out on valuable opportunities. On the other hand, overly lenient policies can lead to wasted resources on uninterested consumers. So how can you strike the perfect balance and ensure your marketing efforts are both effective and efficient? Challenges for financial institutions Research shows that 55% of financial institutions reported building response models that don’t make it to production.[1] This can lead to wasted time and effort as employees work to build models that are never used, which can have a severe negative impact on organizations’ productivity and team members’ morale. In addition, most organizations are not well-equipped to conduct their own analytics, citing limited access to data for response modeling and challenges with incorporating models into a comprehensive campaign strategy. Many institutions are unsure of who to send offers to, which channels to utilize, which offers to send, or how often to send them. To effectively reach consumers, financial institutions need to: Easily access and understand the right data Quickly move to production Deploy models with little to no friction Monitor and refresh models to avoid deterioration Maintain regulatory compliance  So how can your organization accomplish all this to ensure you’re reaching the right consumers with your offers? Ascend Intelligence Services™ Target Ascend Intelligence Services Target (Target) is a cutting-edge solution designed to help businesses target the right consumers with precision. This service leverages custom response models and optimized prescreen strategies to enhance response rates and maximize revenue. At the heart of Target are custom response models developed by industry experts using advanced machine learning (ML) techniques. These models analyze historical data alongside Experian's best-in-class data to identify consumers who meet credit criteria and are more likely to respond to offers. By accurately predicting consumer behavior, these models enable organizations to maximize the return on investment (ROI) of their marketing campaigns and achieve their revenue goals. Additionally, exclusive access to alternative datasets from nontraditional lenders, rental data inputs, and full-file public records provides a comprehensive view of consumer behavior. The inclusion of 24 months of trended data and over 2,000 attributes can further enhance your ability to determine the next best action for each consumer. Watch this video to learn more about Ascend Intelligence Services Target. Optimized prescreen strategy Target's prescreen strategy is mathematically optimized to calculate the impact of your offer on each consumer simultaneously. This approach selects the best consumers to target, allowing you to: Increase response and take-up rates for improved portfolio performance. Minimize prescreen costs by targeting the right people who are more likely to respond to your offers. Expand your lending universe safely and meet diversity and inclusion initiatives by providing the right offer to previously overlooked consumers. Seamlessly integrate into your existing prescreen process for rapid time to value. By incorporating additional variables such as trended and alternative data, you can reach more consumers who might have been overlooked, improving financial inclusion and safely growing your portfolio. The power of optimization allows you to tailor your offers to each consumer, increasing response and take-up rates and enhancing the profitability of your campaigns. Visit our website to learn more about how your organization can utilize our prescreen strategies to maximize your revenue. Learn more [1] Experian research

The electric vehicle (EV) market continues to see remarkable growth as both new and used registrations rise year-over-year. For the first time, new EVs accounted for 9.2% of all retail vehicle registrations across the U.S. in 2024, according to Experian’s 2024 EV Year in Review Report, and used EV registrations climbed to just over 1%, from 0.7% the year prior. As we dove into the data, we found that Tesla remains the dominant player in both new and used sectors; however, the shift in consumer preferences is extending across various manufacturers with more models hitting the market. For instance, Tesla accounted for 50.7% of new retail registrations in 2024, from 60.6% in 2023. Meanwhile, Ford increased from 4.7% to 6.2% year-over-year and Hyundai went from 4.2% to 5.4%. On the used side, Tesla made up 59% of retail registrations, from 60% in 2023, while Chevrolet grew from 7.1% to 9% and Nissan was at 5.4%, from 8.3%. As the EV market continues to grow, it’s not just the various manufacturers making waves; geographical trends are also coming into play in shaping how these vehicles are being embraced nationwide. While EV adoption is expanding well beyond the traditional EV strongholds, California still holds the highest number of registrations, with Los Angeles accounting for more than 180,000 new retail EV registrations, followed by San Francisco at 91,000+ and San Diego with more than 31,000. Hartford and New Haven, Connecticut experienced the highest growth in new retail EV registrations over the last five years, reaching 110.5% in 2024. Close behind were El Paso, Texas (with a 99% increase), and Colorado Springs, Colorado (with an 85.7% spike). These shifts highlight the rapid expansion of EV adoption across the country as we see more consumers in diverse areas opting for the fuel type. Analyzing and leveraging the broader range of registrations will help automotive professionals as they identify emerging markets to effectively tailor their strategies. To learn more about EV insights, visit Experian Automotive’s EV Resource Center.

March is a time when the idea of luck is in the air, with St. Patrick’s Day celebrations and hopeful thoughts of pots of gold at the end of the rainbow. But while the "Luck of the Irish" may be a fun idea, scammers take advantage of this sentiment to exploit people through fraudulent lottery scams and prize schemes. Take, for example, the so-called "Luck of the Irish" scams that flood inboxes and phone lines every March. You might receive a message claiming you have won the "Irish National Lottery" or another grand prize, but there is a catch—you need to pay fees or provide sensitive personal information to claim it. Before you know it, the scammers have vanished with your money or used your data for further fraud. Red flags of lottery scams Financial institutions can help protect clients by educating them on the warning signs of fraudulent lottery schemes. According to the FTC website, here are three clear indicators that a prize is too good to be true: You must pay to claim your winnings – Legitimate lotteries do not require winners to pay taxes, fees, or handling charges upfront. If you are asked to send money to claim a prize, it is a scam. You never entered the lottery – If you did not buy a ticket or enter a sweepstake, you cannot win. Any message saying otherwise is a red flag. They ask for personal or financial information – No legitimate lottery will ask for your Social Security number, bank details, or credit card information to process winnings. How scammers operate Lottery scammers use a variety of tactics to trick victims, including: Impersonating well-known brands or government agencies to appear credible. Sending fake checks that later bounce after victims have sent money. Using high-pressure tactics, such as claiming the offer is time sensitive. Requesting payment through difficult-to-trace methods like gift cards, wire transfers, or cryptocurrency. How financial institutions can help clients stay safe Banks and financial institutions play a critical role in protecting their clients from falling victim to lottery scams. Here is how they can help: Educate clients: Provide fraud awareness materials explaining common scams, red flags, and safe financial practices. Implement transaction monitoring: Monitor for suspicious transactions, especially those involving large wire transfers or unusual payments to unknown entities. Encourage multi-factor authentication: Strengthening account security can prevent unauthorized transactions if scammers obtain a victim’s personal information. Offer a safe reporting channel: Encourage clients to report suspected scams so the institution can take preventive action and share warnings with others. Final thoughts Winning the lottery may be a dream for many, but no real jackpot comes with a catch. Financial institutions can be the first line of defense by helping clients recognize scams before they lose money. The best approach? Remind clients that the only "pot of gold" worth chasing is the one they have earned and safeguarded through smart financial habits. And finally, check out this educational tune with a catchy rhythm, designed to raise awareness about scams. Learn more