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  Managing digital identities is a necessity, responsibility and privilege. When done right, digital identity management solutions can help consumers feel recognized and safe. In turn, companies can build strong and personalized relationships with their customers while complying with regulatory requirements and combating hydra-like fraud attacks. What is digital identity? The concept and definition of a digital identity have expanded as everyday interactions increasingly happen in digital realms. Today, a digital identity is more than an online account. Identities can be created and depend on all the digital information associated with a unique entity, which may be a person, business or device. A person's digital identity often includes online and offline attributes that fall into one of three categories: Something a user knows, such as a username, password or PIN. Something a user has, such as a mobile phone or security token. Something that's part of the user, such as a fingerprint, iris, voice pattern, behavior or preferences. People are increasingly open to sharing this type of personal information if it serves a purpose. Our Global Identity and Fraud Report found that 57 percent of consumers are willing to share data if it ensures greater security or prevents fraud, and 63 percent of consumers think sharing data is beneficial (up from 51 percent in 2021).1 People can also use these identifiers to verify their identity at a later point. But digital identity verification tools should rely on more than user-provided verification alone. A person may have hundreds or thousands of digital interactions every day, and these can leave digital footprints that you can use to create or expand digital identities. These types of identifiers — such as search queries, geotags, behaviors and device information — can also help you authenticate a user and offer a more customized and seamless experience. However, when focusing on consumers' digital identities, it's important to remember that their identity is more than the sum of data points. A person's digital identity is unique and personal, and it should be managed accordingly. The business side's challenges A discussion of what makes up an identity can quickly turn philosophical. For instance, you can't authenticate identical twins based on a face scan or DNA test, so what is it that makes them unique? In some ways, the example gets to the heart of businesses' challenges today. To create a safe and enjoyable online identity verification experience, you need to be able to distinguish between a real person and an imitator, even when the two look nearly identical. Access to more information can make this easier, but you then need to ensure that you can keep this information secure. It can be a tricky balance, but if you get it right, your efforts will be rewarded. People want to be recognized as they move across channels and devices, and organizations want to be able to quickly and accurately identify users with a friction-right experience that also helps prevent fraud. However, while 84 percent of businesses say recognizing customers is "very" or "extremely" important, only about 33 percent of consumers are confident that they'll be repeatedly recognized online.1 There's a clear gap — and an opportunity to better meet customers' desires. Organizations across industries know they need a customer recognition strategy and 82% already have one in place.2 Some businesses address this challenge with identity platforms that are standardized and interoperable. Standardization allows the platform to gather and store the growing influx of data that it can use as part of a digital identity strategy. Interoperability allows the platform to match different types of data, including physical data, with a person to verify their digital identity and avoid the creation of duplicate identities. In short, the platforms can make sense of increasingly large amounts of internal and external data and easily incorporate new data sources as they become available. Regulatory compliance and digital identity Navigating the regulatory landscape is a significant challenge for organizations dealing with digital identities. Compliance is not only necessary for legal reasons but also critical to maintaining customer trust and safeguarding institutional reputation. Organizations must stay informed about the regulatory frameworks that affect digital identity, such as the General Data Protection Regulation (GDPR) in the European Union, the California Consumer Privacy Act (CCPA), and other pertinent laws in jurisdictions they operate. These regulations dictate how personal data can be collected, stored, used and shared. Staying ahead of regulatory changes: Regulatory landscapes are dynamic, particularly concerning digital data. Organizations should engage with policymakers and participate in industry forums to  stay ahead of changes. By proactively managing compliance, organizations can avoid costly penalties, operational disruptions and reputational damage. The consumer's perspective Some organizations are adopting a consumer-centric approach to digital identity that puts consumers' needs and desires first. These can broadly be broken into four categories: Security: While people want a seamless and personalized experience, security and privacy are listed as top concerns year after year.1 That might not be surprising given that data breaches continually make headlines and there are growing concerns over identity theft. Privacy: Security is related to privacy, but privacy means more than keeping consumers' information safe from hackers. Our April 2022 Global Insight Report found that 90 percent of consumers want some or complete control over how their personal data is used. 3 Recognition: People want to be continually recognized once they share and verify their identity, even if they move between devices or channels. And nearly 70 percent of consumers say it's important for businesses to recognize them across multiple visits.1 Inclusion: Consumers may have varying levels of access to technology, comfort with technology and access to physical identifiers. Creating digital identity solutions for these potential barriers can also increase financial inclusion. While these are all areas of focus, organizations also need to find the right fit for each person and interaction. For instance, consumers may expect and even appreciate a robust verification process when they're opening a new financial account. But they could quickly be turned off by a similar process if they're making a small purchase or trying to play a new online game. What to look for in a digital identity partner Digital identity solutions and services have grown increasingly sophisticated to meet today's challenges. Identity hubs and data orchestration engines can connect with multiple services to help create, resolve, verify and authenticate identities. By moving away from a siloed approach, businesses can offer customers a better experience while minimizing their risk throughout the customer journey. When comparing potential partners, look for a company that: Has a customer-first approach: If your business is customer-first, then you need a partner who has a similar view. Uses multidimensional data: The partner should be able to offer and use offline and digital data sources to resolve, verify and authenticate digital identities. Its capabilities may become increasingly important as new data sources emerge. Isn't afraid to innovate: Look into how the partner is testing and using the latest advancements, such as artificial intelligence, in its digital identity solutions. Protects your brand: Understand how the partner helps detect and prevent fraud while creating a seamless experience for your customers and protecting their data. The right partner can increase your bottom line, help you build trust and improve your brand's reputation. Learn more about Experian Identity, an integrated approach to digital identity that builds on Experian's decades of experience managing and securing identifying information. Learn more 1“2022 Global Identity and Fraud Report: Building digital consumer trust amidst rising fraud activity and concerns," Experian, June 2022 2“2021 Global Identity and Fraud Report: Protecting and enabling customer engagements in the new digital era," Experian, April 2021. https://www.experian.com/content/dam/marketing/na/global-da/pdfs/GIDFR_2022.pdf https://www.experian.co.th/wp-content/uploads/2021/04/Experian-Global-Identity-Fraud-Report-2021.pdf 3"Global Insights Report: April 2022," Experian, April 2022. https://www.experian.com/blogs/global-insights/wp-content/uploads/2022/04/WaveReportApril2022.pdf *This article includes content created by an AI language model and is intended to provide general information.

This article was updated on November 9, 2023. Fraud – it’s a word that comes up in conversations across every industry. While there’s a general awareness that fraud is on the rise and is constantly evolving, for many the full impact of fraud is misunderstood and underestimated. At the heart of this challenge is the tendency to lump different types of fraud together into one big problem, and then look for a single solution that addresses it. It’s as if we’re trying to figure out how to un-bake a terrible cake instead of thinking about the ingredients and the process needed to put them together in the first place. This is the first of a series of articles in which we’ll look at some of the key ingredients that create different types of fraud, including first party, third party, synthetic identity, and account takeover. We’ll talk about why they’re unique and why we need to approach each one differently. At the end of the series, we’ll get a result that’s easier to digest. I had second thoughts about the cake metaphor, but in truth it really works. Creating a good fraud risk management process is a lot like baking. We need to know the ingredients and some tried-and-true methods to get the best result. With that foundation in place, we can look for ways to improve the outcome every time. Let’s start with a look at the best known type of fraud, third party. What is third-party fraud? Third-party fraud – generally known as identity theft – occurs when a malicious actor uses another person’s identifying information to open new accounts without the knowledge of the individual whose information is being used. When you consider first-party vs third-party fraud, or synthetic identity fraud, third-party stands out because it involves an identifiable victim that’s willing to collaborate in the investigation and resolution, for the simple reason that they don’t want to be responsible for the obligation made under their name. Third-party fraud is often the only type of activity that’s classified as fraud by financial institutions. The presence of an identifiable victim creates a high level of certainty that fraud has indeed occurred. That certainty enables financial institutions to properly categorize the losses. Since there is a victim associated with it, third party fraud tends to have a shorter lifespan than other types. When victims become aware of what’s happening, they generally take steps to protect themselves and intervene where they know their identity has been potentially misused. As a result, the timeline for third-party fraud is shorter, with fraudsters acting quickly to maximize the funds they’re able to amass before busting out. How does third-party fraud impact me? As the digital transformation continues, more and more personally identifiable information (PII) is available on the dark web due to data breaches and phishing scams. Given that consumer spending is expected to increase1, we anticipate that the amount of PII readily available to criminals will only continue to grow. All of this will lead to identity theft and increase the risk of third-party fraud. More than $43 billion in total losses was reported due to identity theft and fraud in the U.S. in 2022.2 Solving the third-party fraud problem We’ve examined one part of the fraud problem, and it is a complex one. With Experian as your partner, solving for it isn’t. Continuing my cake metaphor, by following the right steps and including the right ingredients, businesses can detect and prevent fraud. Third-party fraud detection and prevention involves two distinct steps. Analytics: Driven by extensive data that captures the ways in which people present their identity—plus artificial intelligence and machine learning—good analytics can detect inconsistencies, and patterns of usage that are out of character for the person, or similar to past instances of known fraud. Verification: The advantage of dealing with third-party fraud is the availability of a victim that will confirm when fraud is happening. The verification step refers to the process of making contact with the identity owner to obtain that confirmation and may involve identity resolution. It does require some thought and discipline to make sure that the contact information used leads to the identity owner—and not to the fraudster. In a series of articles, we’ll be exploring first-party fraud, synthetic identity fraud, and account takeover fraud and how a layered fraud management solution can help keep your business and customers safe and manage third-party fraud detection, first-party fraud, synthetic identity fraud, and account takeover fraud prevention. Let us know if you’d like to learn more about how Experian is using our identity expertise, data, and analytics to create robust fraud prevention solutions. Contact us 1 Experian Ascend Sandbox 2 2023 U.S. Identity and Fraud Report, Experian.

This article was updated on November 9, 2023. Account takeover fraud is a huge, illicit business in the United States with real costs for consumers and the organizations that serve them. In fact, experts predict that by the end of 2023, account takeover losses will be over $635 billion. With consumers' data, your reputation, and your organization's financial picture on the line, now's the time to learn about account takeover fraud and how to prevent it.  What is account takeover fraud?  Account takeover fraud is a form of identity theft where bad actors gain unlawful access to a user's online accounts in order to commit financial crimes. This often involves the use of bots.  information that enables account access can be compromised in a variety of ways. It might be purchased and sold on the dark web, captured through spyware or malware or even given “voluntarily" by those falling for a phishing scam.  Account takeover fraud can do far more potential damage than previous forms of fraud because once criminals gain access to a user's online account, they can use those credentials to breach others of that user's accounts.  Common activities and tools associated with account takeover fraud include: Phishing: Phishing fraud relies on human error by impersonating legitimate businesses, usually in an email. For example, a scammer might send a phishing email disguising themselves as a user's bank and asking them to click on a link that will take them to a fraudulent site. If the user is fooled and clicks the link, it can give the hackers access to the account.  Credential stuffing/cracking: Fraudsters buy compromised data on the dark web and use bots to run automated scripts to try and access accounts. This strategy, called credential stuffing, can be very effective because many people reuse insecure passwords on multiple accounts, so numerous accounts might be breached when a bot has a hit. Credential cracking takes a less nuanced approach by simply trying different passwords on an account until one works.  Malware: Most people are aware of computer viruses and malware but they may not know that certain types of malware can track your keystrokes. If a user inadvertently downloads a “key logger", everything they type, including their passwords, is visible to hackers.  Trojans: As the name suggests, a trojan works by hiding inside a legitimate application. Often used with mobile banking apps, a trojan can overlay the app and capture credentials, intercept funds and redirect financial assets.  Cross-account takeover: One evolving type of fraud concern is cross-account takeover. This is where hackers take over a user's financial account alongside another account such as their mobile phone or email. With this kind of access, fraudsters can steal funds more easily and anti-fraud solutions are less able to identify them.  Intermediary new-account fraud: This type of fraud involves using a user's credentials to open new accounts in their name with the aim of draining their bank accounts.  This is only an overview of some of the most prevalent types of account takeover fraud. The rise of digital technologies, smartphones, and e-commerce has opened the door to thieves who can exploit the weaknesses in digital security for their own aims. The situation has only worsened with the rapid influx of new and inexperienced online users driven by the COVID-19 pandemic.  Why should you be concerned, now?  Now that digital commerce and smartphone use are the norm, information used to access accounts  is a security risk. If a hacker can get access to this information, they may be able to log in to multiple accounts.. The risk is no longer centralized; with every new technology, there's a new avenue to exploit.   To exacerbate the situation, the significant shift to online, particularly online banking, spurred by the COVID-19 pandemic, appears to have amplified account takeover fraud attempts. In 2019, prior to the pandemic, 1.5 billion records — or approximately five records per American — were exposed in data breaches. This can potentially increase as the number of digital banking users in the United States is expected to reach almost 217 million by 2025. Aite research reported that 64 percent of financial institutions were seeing higher rates of account takeover fraud than before COVID. Unfortunately, this trend shows no sign of slowing down. The increase in first-time online users propelled by COVID has amplified the critical security issues caused by a shift from transaction fraud to identity-centric account access. Organizations, especially those in the financial and big technology sectors, have every reason to be alarmed.  The impact of account takeover fraud on organizations  Account takeover can be costly, damage your reputation and require significant investments to identify and correct.  Protection of assets  When we think of the risks to organizations of account takeover fraud, the financial impact is usually the first hazard to come to mind. It's a significant worry: According to Experian's 2023 U.S. Identity and Fraud report, account takeover fraud was among the top most encountered fraud events reported by U.S. businesses. And even worse, the average net fraud loss per case for debit accounts has been steadily increasing since early 2021. The costs to businesses of these fraudulent activities aren't just from stolen funds. Those who offer credit products might have to cover the costs of disputing chargebacks, card processing fees or providing refunds. Plus, in the case of a data breach, there may be hefty fines levied against your organization for not properly safeguarding consumer information. Add to these the costs associated with the time of your PR department, sales and marketing teams, finance department and customer service units.  In short, the financial impact of account takeover fraud can permeate your entire organization and take significant time to recoup and repair.  Protection of information  Consumers rightfully expect organizations to have a solid cybersecurity plan and to protect their information but they also want ease and convenience. In many cases, it's the consumers themselves who engage in risky online behavior — reusing the same password on multiple sites or even using the same password on all sites. These lax security practices open users up to the possibility of multiple account takeovers. Making things worse for organizations, security strategies can annoy or frustrate consumers. If security measures are too strict, they risk alienating consumers or even generating false positives, where the security measure flags a legitimate user.  Organizations are in the difficult position of having to balance effective security measures with a comfortable user experience. Reputation  When there's a data breach, it does significant damage to your organization's reputation by demonstrating weaknesses in your security. Fraudulent account take-overs can affect the consumers who rely on you significantly and if you lose their trust, they're likely to sever their relationship with you. Large-scale data breaches can sully your organization's reputation with the general public, making consumers less likely to consider your services. How to build an account takeover fraud prevention strategy  There are numerous ways to build an account takeover fraud prevention strategy, but to work for your and individual consumers, it must pair robust risk management with a low friction user experience.  Here are some of the key elements to an account takeover fraud prevention strategy that hits the right notes.  Monitor interactions The risk of account takeover is constant so your monitoring should be as well. A layered, proactive and passive fraud prevention program can monitor your interactions, reduce false positives and keep track of consumers' digital identities. Use the right tools When it comes to fraud prevention, you've got plenty of choices but you'll want to make sure you use the tools that protect you, as well as consumer data, while always providing a positive experience. We use risk-based identity and device authentication and targeted step-up authentication to keep things running smoothly and only pull in staff for deeper investigations where necessary. Automate to reduce manual processes  Your organization's fraud prevention strategy likely includes manual processes, tasks that are completed by employees—but humans make mistakes that can be costly. Taking the wrong action, or even no action at all, can result in a security breach. Automated tasks like threat filtering and software and hardware updates can reduce the risk to your organization while improving response time and freeing up your team.  Choose a nimble platform  Technology changes quickly and so does fraud. You'll need access to a layered platform that lets you move as quickly as the bad actors do.  The bottom line  You can effectively mitigate against the risk of account takeover fraud and offer consumers a seamless experience. Learn more about account takeover fraud prevention and fraud management solutions.  Fraud management solutions

For companies that regularly engage in financial transactions, having a customer identification program (CIP) is mandatory to comply with the regulations around identity verification requirements across the customer lifecycle. In this blog post, we will delve into the essentials of a customer identification program, what it entails, and why it is important for businesses to implement one. What is a customer identification program? A CIP is a set of procedures implemented by financial institutions to verify the identity of their customers. The purpose of a CIP is to be a part of a financial institution’s fraud management solutions, with similar goals as to detect and prevent fraud like money laundering, identity theft, and other fraudulent activities. The program enables financial institutions to assess the risk level associated with a particular customer and determine whether their business dealings are legitimate. An effective CIP program should check the following boxes: Confidently verify customer identities Seamless authentication Understand and anticipate customer activities Where does Know Your Customer (KYC) fit in? KYC policies must include a robust CIP across the customer lifecycle from initial onboarding through portfolio management. KYC solutions encompass the financial institution’s customer identification program, customer due diligence and ongoing monitoring. What are the requirements for a CIP? Customer identification program requirements vary depending on the type of financial institution, the type of account opened, and other factors. However, the essential components of a CIP include verifying the customer's identity using government-issued identification, obtaining and verifying the customer's address, and checking the customer against a list of known criminals, terrorists, or suspicious individuals. These measures  help detect and prevent financial crimes. Why is a CIP important for businesses? CIP helps businesses mitigate risk by ensuring they have accurate and up-to-date information about their customers. This also helps financial institutions comply with laws and regulations that require them to monitor financial transactions for any suspicious activities. By having a robust CIP in place, businesses can establish trust and rapport with their customers. According to Experian’s 2024 U.S. Identity and Fraud Report, 63% of consumers say it's extremely or very important for businesses to recognize them online. Having an effective CIP in place is part of financial institutions showing their consumers that they have their best interests top of mind. Finding the right partner It’s important to find a partner you trust when working to establish processes and procedures for verifying customer identity, address, and other relevant information. Companies can also utilize specialized software that can help streamline the CIP process and ensure that it is being carried out accurately and consistently. Experian’s proprietary and partner data sources and flexible monitoring and segmentation tools allow you to resolve CIP discrepancies and fraud risk in a single step, all while keeping pace with emerging fraud threats with effective customer identification software. Putting consumers first is paramount. The security of their identity is priority one, but financial institutions must pay equal attention to their consumers’ preferences and experiences. It is not just enough to verify customer identities. Leading financial institutions will automate customer identification to reduce manual intervention and verify with a reasonable belief that the identity is valid and eligible to use the services you provide. Seamless experiences with the right amount of friction (I.e., multi-factor authentication) should also be pursued to preserve the quality of the customer experience. Putting it all together As cybersecurity threats are becoming more sophisticated, it is essential for financial institutions to protect their customerinformation and level up their fraud prevention solutions. Implementing a customer identification program is an essential component in achieving that objective. A robust CIP helps organizations detect, prevent, and deter fraudulent activities while ensuring compliance with regulatory requirements. While implementing a CIP can be complex, having a solid plan and establishing clear guidelines is the best way for companies to safeguard customer information and maintain their reputation. CIPs are an integral part of financial institutions security infrastructures and must be a business priority. By ensuring that they have accurate and up-to-date data on their customers, they can mitigate risk, establish trust, and comply with regulatory requirements. A sound CIP program can help financial institutions detect and prevent financial crimes and cyber threats while ensuring that legitimate business transactions are not disrupted, therefore safeguarding their customers' information and protecting their own reputation. Learn more

In a series of articles, we talk about different types of fraud and how to best solve for them. This article will explore first-party fraud and how it's similar to biting into a cookie you think is chocolate chip, only to find that it’s filled with raisins. The raisins in the cookie were hiding in plain sight, indistinguishable from chocolate chips without a closer look, much like first-party fraudsters. What is first-party fraud? First-party fraud refers to instances when an individual purposely misrepresents their identity in exchange for goods or services. In the financial services industry, it's often miscategorized as credit loss and written off as bad debt, which causes problems when organizations later try to determine how much they’ve lost to fraud versus credit risk. Common types of first-party fraud include: Chargeback fraud: Also known as "friendly fraud," chargeback fraud occurs when an individual knowingly makes a purchase with their credit card and then requests a chargeback from the issuer, claiming they didn't authorize the purchase. Application fraud: This takes place when an individual uses stolen or manipulated information to apply for a loan, credit card or job. In 2023, the employment sector accounted for 45% of all false document submissions — 70% of those who falsified their resumes still got hired. Fronting: Done to get cheaper rates, this form of insurance fraud happens when a young or inexperienced individual is deliberately listed as a named driver, when they're actually the main driver of the vehicle. Goods lost in transit fraud (GLIT): This occurs when an individual claims the goods they purchased online did not arrive. To put it simply, the individual is getting a refund for something they actually already received. A first-party fraudster can also recruit “money mules” — individuals who are persuaded to use their own information to obtain credit or merchandise on behalf of a larger fraud ring. This type of fraud has become especially prevalent as more consumers are active online. Money mules constitute up to 0.3% of accounts at U.S. financial institutions, or an estimated $3 billion in fraudulent transfers. How does it impact my organization? Firstly, there are often substantial losses associated with first-party fraud. An imperfect first-party fraud solution can also strain relationships with good customers and hinder growth. When lenders have to interpret actions and behavior to assess customers, there’s a lot of room for error and losses. Those same losses hinder growth when, as mentioned before, businesses anticipate credit losses that aren’t actually credit losses. This type of fraud isn’t a single-time event, and it doesn’t occur at just one point in the customer lifecycle. It occurs when good customers develop fraudulent intent, when new applicants who have positive history with other lenders have recently changed circumstances or when seemingly good applicants have manipulated their identities to mask previous defaults. Finally, first-party fraud impacts how your organization categorizes and manages risk – and that’s something that touches every department. Solving the first-party fraud problem First-party fraud detection requires a change in how we think about the fraud problem. It starts with the ability to separate first- and third-party fraud to treat them differently. Because first-party fraud doesn’t have a victim, you can’t work with the person whose information was stolen to confirm the fraud. Instead, you’ll have to implement a consistent monitoring system and make a determination internally when fraud is suspected. As we’ve already discussed, the fraud problem is complex. However with a partner like Experian, you can leverage the fraud risk management strategies required to perform a closer examination and the ability to differentiate between the types of fraud so you can determine the best course of action moving forward. Additionally, our robust fraud management solutions can be used for synthetic identity fraud and account takeover fraud prevention, which can help you minimize customer friction to improve and deepen your relationships while preventing fraud. Contact us if you’d like to learn more about how Experian is using our identity expertise, data and analytics to improve identity resolution and detect and prevent all types of fraud. Contact us

In today’s fast-paced world, the telecommunications industry is not just about connecting calls or sending messages. It’s about creating seamless digital experiences, especially when onboarding new customers. However, with the rise of digital services, the industry faces an increasing challenge: the need to mitigate fraud while streamlining the onboarding process.  The digital onboarding revolution Digital onboarding has transformed the way customers join telecommunications services. No longer are people required to visit a physical store or wait for lengthy paperwork. Instead, they can sign up for mobile, internet or TV services from the comfort of their homes, often within minutes. The convenience, however, has opened new doors for fraudsters. As the onboarding process happens online, the risk of identity theft, synthetic identity fraud and other fraudulent activities has surged. So, how can telecom companies provide fritctionless experiences while keeping fraud at bay? Mitigating fraud in telecommunications onboarding Know your customer (KYC) verification: Implement robust KYC solutions to verify the identity of new customers. This may include identity document checks, facial recognition or biometric authentication. Device and location data; and velocity: Analyze the device and location data of applicants. Does the device match the customer’s claimed location? Unusual patterns could signal potential fraud.  Behavioral analysis: Monitor user behavior during the onboarding process. Frequent changes in information or suspicious browsing activity may indicate fraudulent intent.   Machine learning (ML) and artificial intelligence (AI): Leverage AI/ML algorithms to detect patterns and anomalies humans might miss. These technologies can adapt and evolve to stay ahead of fraudsters.   Document verification: Use document verification services to ensure that documents provided by customers are genuine. This can include checks for altered or forged documents. Industry data sharing–consortia: Collaborate with industry databases and share fraud-related information to help identify applicants with a history of fraudulent activity or reveal patterns. The balancing act While it’s crucial to mitigate fraud, telecommunication companies must strike a balance between security and a seamless onboarding experience. Customers demand a hassle-free process, and overly stringent security measures can deter potential subscribers. By combining advanced technology, behavioral analysis and proactive fraud prevention strategies, telecom companies can create a secure digital onboarding journey that minimizes risk without compromising user experience. In doing so, they empower customers to embrace the convenience of digital services while staying one step ahead of fraudsters in today’s interconnected world.  Learn more about Experian and the telecom industry Learn more about our fraud and identity solutions

Authorized Push Payment fraud, also known as APP fraud or APP scams, involves a fraudster persuading a victim to willingly deposit funds to their account or to the account of a complicit third party, also known as a money mule. This type of fraud often includes social engineering of the victim using fake investment schemes, impersonation scams, purchase scams or other schemes. Social engineering clouds victims' judgments and encourages them to make payments willingly to one or more money mules, with funds eventually reaching fraudsters' accounts. This type of fraud has become more attractive to criminals since the advent of real-time payment systems, which are now a reality worldwide. Fraud fueled by real-time payments Authorized push payment fraud is becoming more prevalent, and it is imperative that you know how to detect and prevent it to safeguard your organization. Real-time payment systems, such as Faster Payments in the United Kingdom (UK), PIX in Brazil, the New Payments Platform in Australia, and FedNow in the USA, make real-time payment fraud a reality.  APP fraud is notoriously difficult for banks to prevent because the victim is sending the money themselves, and steps that banks take to authenticate customers are ineffective, as the customer will pass identity checks. The victims cannot reverse a payment once they realize they have been conned, as payments made using real-time payment schemes are irrevocable. APP fraud is particularly prevalent in countries where banks have an infrastructure that facilitates fast or immediate transfers, like the UK. Learn more about the new UK legislation around APP fraud Reimbursment is vital to victims Some common types of authorized push payment fraud include attacks on individuals like romance scams, family emergency swindles, targeting property transactions, and intercepting supplier payments. To protect against APP fraud, it is important to employ layered fraud protection across all products and channels used to manage real-time payments. But that alone is not enough. Reimbursement is vital in reversing the financial distress caused by APP scams, but it cannot reverse the emotional distress these scams cause. Prevention, detection, and awareness measures must be moved up on the agenda for banks, non-traditional lenders, PSPs (Payment Service Providers), and customers alike to ensure that the customer is protected at every stage of the payment journey.  Effective alerts are a key focus area for preventing customers from falling victim to APP scams. An effective warning is one that is dynamic and tailored to the customer’s payment journey. Recent research indicates that minor changes to notifications across banking apps can have the potential to drastically reduce the number of individuals that fall victim to APP fraud. The biggest effects were achieved when a combination of risk-based and Call to Action (CTA) warnings were implemented over a period of time. A collective effort across the banking industry and beyond is crucial to protect customers and tackle the fight against APP fraud. Banks, non-traditional lenders, and PSPs can raise awareness to educate their customers on the signs and risks of APP scams, and work with industry oversight bodies to commit to voluntary standards and codes to ensure good customer outcomes. Online forums, social media platforms, and influential voices also have a role to play in raising awareness of and preventing scams. Customers can also help by being vigilant and reading and acting upon warnings and information presented to them.  Authorized push payment fraud prevention To effectively combat authorized push payment fraud, financial institutions must implement a range of measures, including:  Direct communication with consumers.  Enhanced transaction monitoring.  Effective risk mitigation and management.  Improved employee education.  Public awareness campaigns.   In response to this growing threat, banks have introduced various checks and balances, such as the Confirmation of Payee (CoP) service in the UK, which cross-references bank details with the account holder's name when processing online payments.  Banks are also leveraging sophisticated fraud prevention software stacks, incorporating machine learning and contextual data to identify and flag suspicious transactions. By utilizing AI technologies, financial institutions can process  data points faster and enhance their fraud detection capabilities, mitigating identity risk and safeguarding customer accounts. Clear communication with customers is essential in the fight against APP fraud. Higher-risk companies now include warnings in their communications, advising customers not to act on messages that request payment into new bank accounts.  Financial institutions can also offer cool-off periods before payments are sent, increase due diligence around payment destinations, and monitor accounts that regularly receive high-value payments. Additionally, financial institutions can play a crucial role in educating their customers and promoting awareness around this increasingly common type of fraud. By combining these approaches with robust fraud prevention software, the public can fight against this type of fraudulent attack.  Taking the next steps with the right partner At Experian, we offer rich data sources, advanced analytics capabilities, and the consultancy services needed to rapidly adopt data analytics solutions that mitigate fraud risks. Our solutions are used by PSPs of all types and sizes – including some of the largest banks – to identify potentially fraudulent customers and transactions, and to ensure that action is taken in real time to prevent fraudulent payments being made.  Learn more about our fraud management solutions *This article leverages/includes content created by an AI language model and is intended to provide general information.

Model governance is growing increasingly important as more companies implement machine learning model deployment and AI analytics solutions into their decision-making processes. Models are used by institutions to influence business decisions and identify risks based on data analysis and forecasting. While models do increase business efficiency, they also bring their own set of unique risks. Robust model governance can help mitigate these concerns, while still maintaining efficiency and a competitive edge. What is model governance? Model governance refers to the framework your organization has in place for overseeing how you manage your development, model deployment, validation and usage.1 This can involve policies like who has access to your models, how they are tested, how new versions are rolled out or how they are monitored for accuracy and bias.2 Because models analyze data and hypotheses to make predictions, there's inherent uncertainty in their forecasts.3 This uncertainty can sometimes make them vulnerable to errors, which makes robust governance so important. Machine learning model governance in banks, for example, might include internal controls, audits, a thorough inventory of models, proper documentation, oversight and ensuring transparent policies and procedures. One significant part of model governance is ensuring your business complies with federal regulations. The Federal Reserve Board and the Office of the Comptroller of the Currency (OCC) have published guidance protocols for how models are developed, implemented and used. Financial institutions that utilize models must ensure their internal policies are consistent with these regulations. The OCC requirements for financial institutions include: Model validations at least once a year Critical review by an independent party Proper model documentation Risk assessment of models' conceptual soundness, intended performance and comparisons to actual outcomes Vigorous validation procedures that mitigate risk Why is model governance important — especially now? More and more organizations are implementing AI, machine learning and analytics into their models. This means that in order to keep up with the competition's efficiency and accuracy, your business may need complex models as well. But as these models become more sophisticated, so does the need for robust governance.3 Undetected model errors can lead to financial loss, reputation damage and a host of other serious issues. These errors can be introduced at any point from design to implementation or even after deployment via inappropriate usage of the model, drift or other issues. With model governance, your organization can understand the intricacies of all the variables that can affect your models' results, controlling production closely with even greater efficiency and accuracy. Some common issues that model governance monitors for include:2 Testing for drift to ensure that accuracy is maintained over time. Ensuring models maintain accuracy if deployed in new locations or new demographics. Providing systems to continuously audit models for speed and accuracy. Identifying biases that may unintentionally creep into the model as it analyzes and learns from data. Ensuring transparency that meets federal regulations, rather than operating within a black box. Good model governance includes documentation that explains data sources and how decisions are reached. Model governance use cases Below are just three examples of use cases for model governance that can aid in advanced analytics solutions. Credit scoring A credit risk score can be used to help banks determine the risks of loans (and whether certain loans are approved at all). Governance can catch biases early, such as unintentionally only accepting lower credit scores from certain demographics. Audits can also catch biases for the bank that might result in a qualified applicant not getting a loan they should. Interest rate risk Governance can catch if a model is making interest rate errors, such as determining that a high-risk account is actually low-risk or vice versa. Sometimes changing market conditions, like a pandemic or recession, can unintentionally introduce errors into interest rate data analysis that governance will catch. Security challenges One department in a company might be utilizing a model specifically for their demographic to increase revenue, but if another department used the same model, they might be violating regulatory compliance.4 Governance can monitor model security and usage, ensuring compliance is maintained. Why Experian? Experian® provides risk mitigation tools and objective and comprehensive model risk management expertise that can help your company implement custom models, achieve robust governance and comply with any relevant federal regulations. In addition, Experian can provide customized modeling services that provide unique analytical insights to ensure your models are tailored to your specific needs. Experian's model risk governance services utilize business consultants with tenured experience who can provide expert independent, third-party reviews of your model risk management practices. Key services include: Back-testing and benchmarking: Experian validates performance and accuracy, including utilizing statistical metrics that compare your model's performance to previous years and industry benchmarks. Sensitivity analysis: While all models have some degree of uncertainty, Experian helps ensure your models still fall within the expected ranges of stability. Stress testing: Experian's experts will perform a series of characteristic-level stress tests to determine sensitivity to small changes and extreme changes. Gap analysis and action plan: Experts will provide a comprehensive gap analysis report with best-practice recommendations, including identifying discrepancies with regulatory requirements. Traditionally, model governance can be time-consuming and challenging, with numerous internal hurdles to overcome. Utilizing Experian's business intelligence and analytics solutions, alongside its model risk management expertise, allows clients to seamlessly pass requirements and experience accelerated implementation and deployment. Experian can optimize your model governance Experian is committed to helping you optimize your model governance and risk management. Learn more here. References 1Model Governance," Open Risk Manual, accessed September 29, 2023. https://www.openriskmanual.org/wiki/Model_Governance2Lorica, Ben, Doddi, Harish, and Talby, David. "What Are Model Governance and Model Operations?" O'Reilly, June 19, 2019. https://www.oreilly.com/radar/what-are-model-governance-and-model-operations/3"Comptroller's Handbook: Model Risk Management," Office of the Comptroller of the Currency. August 2021. https://www.occ.treas.gov/publications-and-resources/publications/comptrollers-handbook/files/model-risk-management/pub-ch-model-risk.pdf4Doddi, Harish. "What is AI Model Governance?" Forbes. August 2, 2021. https://www.forbes.com/sites/forbestechcouncil/2021/08/02/what-is-ai-model-governance/?sh=5f85335f15cd

Have you heard about the mischievous ghosts haunting our educational institutions? No, I am not talking about Casper's misfit pals. These are the infamous ghost students! They are not here for a spooky study session, oh no! They are cunning fraudsters lurking in the shadows, pretending to be students who never attend classes. It is taking ghosting to a whole new level. Understanding ghost student fraud Ghost student fraud is a serious and alarming issue in the educational sector. The rise of online classes due to the pandemic has made it easier for fraudsters to exploit application systems and steal government aid meant for genuine students. Community colleges have become primary targets due to slower adoption of cybersecurity defenses. It is concerning to hear that a considerable number of applications, such as in California (where Social Security numbers are not required at enrollment), are fictitious, with potential losses in financial aid meant for students in need. The use of stolen or synthetic identities in creating bot-powered applications further exacerbates the problem. The consequences of enrollment fraud can have a profound impact on institutions and students. The recent indictment of individuals involved in enrollment fraud, where identities were stolen to receive federal student loans, highlights the severity of the issue. Unfortunately, the lack of awareness and inadequate identity document verification processes in many institutions make it difficult to fully grasp the extent of the problem. What is a ghost student? Scammers use different methods to commit ghost student loan fraud, including creating fake schools or enrolling in real colleges. Some fraudsters use deceitful tactics to obtain the real identities of students, and then they use it to fabricate loan applications. Types of ghost loan fraud, include: Fake loan offers: Fraudsters contact students via various channels, claiming to offer exclusive student loan opportunities with attractive terms and low interest rates. They often request personal and financial information including their SSN and bank account information and use it to create ghost loans. Identity theft: Threat actors will steal personal info through data breaches or phishing. They will then forge loan applications using the victim’s identity. Targeting vulnerable individuals: Ghost student loan fraud tends to prey on those already burdened by debt. Scammers may target borrowers with poor credit history, promising loan forgiveness or debt consolidation plans in exchange for a fee. Once the victim pays, the fraudsters disappear. Ultimately, addressing ghost student fraud requires a multi-faceted approach involving collaboration between educational institutions, government agencies, and law enforcement to safeguard the accessibility and integrity of education for all deserving students. Safeguarding the financial integrity of educational institutions One powerful weapon in the battle against ghost student fraudsters is the implementation of robust identity verification solutions. Financial institutions, online marketplaces, and government entities have long employed such tools to verify the authenticity of individuals, and their application in the educational domain can be highly effective. By leveraging these tools, institutions can swiftly and securely carry out synthetic fraud detection and confirm the identity of applicants by cross-referencing multiple credible sources of information. For instance, government-issued IDs can be verified against real-time selfies, email addresses can be screened against reliable databases, and personally identifiable information (PII) can be compared to third-party dark web data to detect compromised identities. Clinching evidence from various sources renders it nearly impossible for fraudsters to slip past the watchful eyes of enrollment officers. Moreover, implementation of identity verification measures can be facilitated through low-code implementation, ensuring seamless integration into existing enrollment workflows without requiring extensive technical expertise or incurring exorbitant development costs. To further fortify security measures, educational institutions may consider incorporating biometric enrollment and authentication solutions. By requiring face or voice biometrics for accessing school resources, institutions can create an additional layer of protection against fraudsters and their ethereal counterparts. The reluctance of fraudsters to enroll their own biometric data serves as a powerful deterrent against their intrusive activities. Taking action By adopting these robust measures, higher educational institutions can fortify their defenses against ghost student fraud and maintain the integrity of their finances. The use of online identity verification methods and biometric authentication systems not only strengthens the enrollment process but serves as a stringent reminder that there is no resting place for fraudsters within the hallowed halls of education. To learn more about how Experian can help you leverage fraud prevention solutions, visit us online or request a call. *The SSN Verification tool, better known as eCBSV is also a tool that can be utilized to verify SSN.  *This article leverages/includes content created by an AI language model and is intended to provide general information.

In financial crime, fraudsters are always looking for new avenues to exploit. The mortgage industry has traditionally been a primary target for fraudsters. But with the 30-year fixed-mortgage rate average above 7.19% for the month of September, it has caused an inherent slowdown in the volume of home purchases. As a result, criminals are turning to other lucrative opportunities in mortgage transactions. They have evolved their techniques to capitalize on unsuspecting homeowners and lenders by shifting their focus from home purchases to Home Equity Line of Credit (HELOC), as they see it as a more compelling option.  Understanding mortgage fraud  Mortgage fraud occurs when individuals or groups intentionally misrepresent information during the mortgage application process for personal gain. The most common forms of mortgage fraud include income misrepresentation, false identity, property flipping schemes, and inflated property appraisals. Over the years, financial institutions and regulatory bodies have implemented robust measures to combat such fraudulent activities.  As the mortgage industry adapts to counter established forms of fraud, perpetrators are constantly seeking new opportunities to circumvent detection. This has led to a shift in fraud trends, with fraudsters turning their focus to alternative aspects of the mortgage market. One area that has captured recent attention is HELOC fraud, also known as home equity loan fraud.  HELOC fraud: An attractive target for fraudsters  What is a HELOC?  HELOCs are financial products that allow homeowners to borrow against the equity in their homes, often providing flexible access to funds. While HELOCs can be a valuable financial tool for homeowners, they also present an attractive opportunity for fraudsters due to their unique characteristics.  HELOC fraud schemes  An example of a home equity loan fraud scheme is a fraudster misrepresenting himself to deceive a credit union call center employee into changing a member’s address and phone number. Three days later, the fraudster calls back to reset the member’s online banking password, allowing the fraudster to login to the member’s account. Once logged in, the fraudster orders share drafts to be delivered to the new address they now control. The fraudster then forges three share drafts totaling $309,000 and funds them through unauthorized advances against the member’s HELOC through online banking platforms.   Why HELOCs are becoming the next target for mortgage fraud  Rising popularity: HELOCs have gained significant popularity in recent years, enticing fraudsters seeking out opportunities with larger potential payouts.  Vulnerabilities in verification: The verification process for HELOCs might be less rigorous than traditional mortgages. Fraudsters could exploit these vulnerabilities to manipulate property valuations, income statements, or other critical information.  Lack of awareness: Unlike conventional mortgages, there may be a lack of awareness among homeowners and lenders regarding the specific risks associated with HELOCs. This knowledge gap can make it easier for fraudsters to perpetrate their schemes undetected.  Home equity loans do not have the same arduous process that traditional first mortgages do. These loans do not require title insurance, have less arduous underwriting processes, and do not always require the applicant to be physically present at a closing table to gain access to cash. The result is that those looking to defraud banks can apply for multiple HELOC loans simultaneously while escaping detection.  Prevention and safeguards  There are several preventive measures and fraud prevention solutions that can be established to help mitigate the risks associated with HELOCs. These include:  Education and awareness: Homeowners and lenders must stay informed about the evolving landscape of mortgage fraud, including the specific risks posed by HELOCs. Awareness campaigns and educational materials can play a significant role in spreading knowledge and promoting caution.   Enhanced verification protocols: Lenders should implement advanced verification processes and leverage data analytics and modeling thorough property appraisals, income verification, and rigorous background checks. Proper due diligence can significantly reduce the chances of falling victim to HELOC-related fraud.  Collaboration and information sharing: Collaboration between financial institutions, regulators, and law enforcement agencies is essential to combat mortgage fraud effectively. Sharing information, best practices, and intelligence can help identify emerging fraud trends and deploy appropriate countermeasures.  Acting with the right solution  Mortgage fraud is a constant threat that demands ongoing vigilance and adaptability. As fraudsters evolve their tactics, the mortgage industry must stay one step ahead to safeguard homeowners and lenders alike. With concerns over HELOC-related fraud rising, it is vital to raise awareness, strengthen preventive measures, and foster collaboration to protect the integrity of the mortgage market. By staying informed and implementing robust safeguards, we can collectively combat and prevent mortgage fraud from disrupting the financial security of individuals and the industry.  Experian mortgage is powering advanced capabilities across the mortgage lifecycle by gaining market intelligence, enhancing customer experience to remove friction and tapping into industry leading data sources to gain a complete view of borrower behavior.   To learn more about our HELOC fraud prevention solutions, visit us online or request a call.  *This article leverages/includes content created by an AI language model and is intended to provide general information.

In today's fast-paced financial landscape, financial institutions must stay ahead of the curve when it comes to account opening and onboarding. Digital account opening, empowering a prospective client to securely and efficiently open a new account, is key to how banks, credit unions and other financial institutions grow their business and expand their portfolio. Regardless of the time, money and other resources a financial institution invests in marketing to the right target prospect and tailoring an attractive offer, it’s worthless if that prospective customer can’t complete the process due to a poor account opening experience. Unhappy customers vote with their feet. A recent Experian study found that of the more 2,000 consumers surveyed who’d opened a new account in the last six months, 37% took their business elsewhere due to a negative account opening experience.   The choice of a reliable partner can make all the difference to your account opening and onboarding experience. The right partner must provide your financial institution with access to the freshest credit data; advanced analytics, scores and models to empower you to say yes to the right customers that meet your lending criteria; and industry-leading decision engines that make the best decisions and enable you to provide a seamless customer experience.  Moreover, the right partner will also help you in maintaining high levels of security without compromising user experience, all while adhering to regulatory compliance.  Recently, Liminal, a leading advisory and market intelligence firm specializing in the digital identity, cybersecurity, and fintech markets, released its highly anticipated Link™ Index Report for Account Opening in Financial Services, which evaluates solution providers in the financial sector, in the areas of compliance and fraud prevention for account opening. The report recognized Experian as a market leader for compliance and fraud prevention capabilities and market execution. Experian’s identity verification and fraud prevention solutions, including CrossCore® and Precise ID®, received the highest score out of the 32 companies highlighted in the report. It found that Experian was recognized by 94% of buyers and 89% identified Experian as a market leader.   “We’re thrilled to be named the top market leader in compliance and fraud prevention capabilities and execution by Liminal’s Link Index Report,” said Kathleen Peters, Chief Innovation Officer for Experian’s Decision Analytics business in North America. “We’re continually innovating to deliver the most effective identity verification and fraud prevention solutions to our clients so they can grow their business, mitigate risk and provide a seamless customer experience.”  You can access the full report here. To learn more about Experian’s award-winning fraud solutions, visit our identity fraud hub.  Download Liminal Link Index Report

Are you looking for ways to make your financial institution more secure without adding unnecessary friction to the customer experience? Automated identity verification is an essential part of this process, safeguarding sensitive consumer information and helping to prevent fraud. This blog post will serve as the ultimate guide to automated identity verification so that you can understand why it's important and how it works. We'll cover all the details, like what automated ID verification is, how authentication software works with identifying documents, why automated identification technology is preferred over manual processes, and tips on implementing automation identity verification solutions into your business practices.   What is automated identity verification?  Automated identity verification is a secure, efficient process for verifying the identity of individuals or entities. This process is integral in various industries, especially the financial sector, to curb identity theft and fraudulent activities. It operates by using advanced analytics and authentication software that cross-references the provided data with a set of stored information. This technology eliminates  manual ID verification, saving time and improving accuracy. ID verification automation uses artificial intelligence and machine learning to compare identifying credentials against various authenticating sources.   Automated identity verification also comes into play for employment and income verification. Experian VerifyTM enables businesses through precise, real-time employment and income verification, ultimately helping businesses reduce risk, accelerate conversion and remove friction.   For a more comprehensive understanding of automated identity verification, you can visit Experian's Identity Verification Solutions webpage, which provides a deep dive into the intricacies of identity verification, including insights on its importance in modern business operations and how it keeps your business secure.  Benefits of automated identity verification for businesses and consumers   Automated ID verification has revolutionized the way businesses conduct their operations and interact with customers. For businesses, AIV offers a range of benefits such as:  Improved efficiency – businesses can automate the time-consuming process of identity verification, freeing up resources (staff) to focus on other critical tasks.  Enhanced security – the technology ensures that customer data is secure and accurate, minimizing fraud risks and/or data breaches.  Reduced costs – with the process being faster and more secure, costs are reduced as a byproduct.  On the other hand, consumers enjoy a hassle-free experience as they can verify their identity within seconds, without  physical documentation. This is essential for today’s consumers who expect frictionless experiences that keep them and their information safe.   Data from Experian’s annual U.S. Identity and Fraud Report reflects these sentiments: 37% of consumers moved a new account opening process to another organization because of a poor experience; 95% of consumers say it's important to be repeatedly recognized online by businesses; and 60% of consumers are concerned about their online privacy. With automated identity verification, businesses can build trust, streamline their processes, and ultimately improve their bottom line.  Furthermore, automated identity verification is a necessary component for businesses to minimize fraud risks in our evolving digital landscape. Living in an era where cybercrime is rampant, AIV safeguards businesses from potential fraudulent attempts and data breaches that could cause significant financial and reputational damage.   From a compliance standpoint, automated identity verification ensures regulatory compliance, which is critical, considering the stringent regulations regarding customer data protection. Non-compliance can lead to severe legal repercussions and financial penalties. For financial institutions, Know Your Customer (KYC) policies must include Customer Identification Programs. Experian can help across the entire customer journey, from onboarding through portfolio management, while reducing risk of non-compliance and providing seamless authentication.  Common challenges of automated identity verification   As more companies turn to artificial intelligence and automation to deliver superior customer service experiences, the challenges businesses face have multiplied. One of the most common issues is ensuring identity proofing and accurate information protection within their networks. Although account takeover prevention has become more advanced, fraudsters still use increasingly sophisticated methods to circumvent it. As such, businesses must continuously develop new strategies to overcome these challenges, ensuring that their AI-powered solutions continue to provide reliable and secure user experiences.  Types of identity verification solutions   As the digital world continues to evolve, automated identity verification solutions have become a crucial part of online interactions. These solutions not only enhance security measures, but also provide faster and more efficient ways of identifying individuals.   For instance, facial recognition is one example. Experian’s CrossCore® Doc Capture enables confident identity verification via facial recognition, which scans a person's face and compares it to their identification documents. Another type is voice recognition, which uses speech patterns to verify an identity. Additionally, document verification scans and validates various identification documents, such as driver's licenses and passports. It's essential to choose the most suitable AIV solution for your organization to ensure robust and reliable security measures.  How to implement an automated ID verification solution   It’s not new news that identity theft and fraud continue to be major concerns, particularly in an increasingly digital-only world.  Implementing automated identity verification solutions to safeguard against such threats can seem daunting, particularly for businesses with limited IT resources. However, the benefits of automated ID verification, such as increased accuracy and efficiency, make it a worthwhile investment. When choosing a solution,  consider factors such as the level of security provided, ease of implementation and integration with existing systems, and the ability to customize rules and settings. With careful planning and the right solution, , organizations can take a significant step towards improving their security posture and protecting their customers.  Best Practices for automated identity verification  Automated identity verification presents one way that financial institutions can increase automation. In doing so, organizations can improve accuracy, speed, and security in the verification process. One technique that has proven effective is the use of biometric technology, such as facial recognition and fingerprint scanning, to verify a person's identity. Additionally, utilizing various data sources, such as credit bureaus like Experian and government agencies, can increase the accuracy of verification. Implementing these best practices can not only save time and resources but also enhance customer experience by providing a seamless and secure verification process.  In summary, automated identity verification is a vital tool for businesses and consumers to enhance their safety and security when engaging with customers. Automated identity verification streamlines customer processes across the lifecycle by eliminating manual checks and lengthy delays. As technology continues to evolve, it’s important for organizations to remain mindful that the methodologies used within automated identity verification will rapidly change as well. The key is to stay ahead. Automated identity verification solutions offer many advantages for businesses who want to maintain their trustworthiness while staying competitive in an ever-changing market.  To learn more about Experian’s automated identity verification solutions, visit our website.    Learn More *This article includes content created by an AI language model and is intended to provide general information. 

From science fiction-worthy image generators to automated underwriting, artificial intelligence (AI), big data sets and advances in computing power are transforming how we play and work. While the focus in the lending space has often been on improving the AI models that analyze data, the data that feeds into the models is just as important. Enter: data-centric AI. What is a data-centric AI? Dr. Andrew Ng, a leader in the AI field, advocates for data-centric AI and is often credited with coining the term. According to Dr. Ng, data-centric AI is, ‘the discipline of systematically engineering the data used to build an AI system.’1 To break down the definition, think of AI systems as a combination of code and data. The code is the model or algorithm that analyzes data to produce a result. The data is the information you use to train the model or later feed into the model to request a result. Traditional approaches to AI focus on the code — the models. Multiple organizations download and use the same data sets to create and improve models. But today, continued focus on model development may offer a limited return in certain industries and use cases. A data-centric AI approach focuses on developing tools and practices that improve the data. You may still need to pay attention to model development but no longer treat the data as constant. Instead, you try to improve a model's performance by increasing data quality. This can be achieved in different ways, such as using more consistent labeling, removing noisy data and collecting additional data.2 Data-centric AI isn't just about improving data quality when you build a model — it's also part of the ongoing iterative process. The data-focused approach should continue during post-deployment model monitoring and maintenance. Data-centric AI in lending Organizations in multiple industries are exploring how a data-centric approach can help them improve model performance, fairness and business outcomes. For example, lenders that take a data-centric approach to underwriting may be able to expand their lending universe, drive growth and fulfill financial inclusion goals without taking on additional risk. Conventional credit scoring models have been trained on consumer credit bureau data for decades. New versions of these models might offer increased performance because they incorporate changes in the economic landscape, consumer behavior and advances in analytics. And some new models are built with a more data-centric approach that considers additional data points from the existing data sets — such as trended data — to score consumers more accurately. However, they still solely rely on credit bureau data. Explainability and transparency are essential components of responsible AI and machine learning (a type of AI) in underwriting. Organizations need to be able to explain how their models come to decisions and ensure they are behaving as expected. Model developers and lenders that use AI to build credit risk models can incorporate new high-quality data to supplement existing data sets. Alternative credit data can include information from alternative financial services, public records, consumer-permissioned data, and buy now, pay later (BNPL) data that lenders can use in compliance with the Fair Credit Reporting Act (FCRA).* The resulting AI-driven models may more accurately predict credit risk — decreasing lenders' losses. The models can also use alternative credit data to score consumers that conventional models can't score. Infographic: From initial strategy to results — with stops at verification, decisioning and approval — see how customers travel across an Automated Loan Underwriting Journey. Business benefit of using data-centric AI models Financial services organizations can benefit from using a data-centric AI approach to create models across the customer lifecycle. That may be why about 70 percent of businesses frequently discuss using advanced analytics and AI within underwriting and collections.3 Many have gone a step further and implemented AI. Underwriting is one of the main applications for machine learning models today, and lenders are using machine learning to:4 More accurately assess credit risk models. Decrease model development, deployment and recalibration timelines. Incorporate more alternative credit data into credit decisioning. AI analytics solutions may also increase customer lifetime value by helping lenders manage credit lines, increase retention, cross-sell products and improve collection efforts. Additionally, data-centric AI can assist with fraud detection and prevention. Case study: Learn how Atlas Credit, a small-dollar lender, used a machine learning model and loan automation to nearly doubled its loan approval rates while decreasing its credit risk losses. How Experian helps clients leverage data-centric AI for better business outcomes During a presentation in 2021, Dr. Ng used the 80-20 rule and cooking as an analogy to explain why the shift to data-centric AI makes sense.5 You might be able to make an okay meal with old or low-quality ingredients. However, if you source and prepare high-quality ingredients, you're already 80% of the way toward making a great meal. Your data is the primary ingredient for your model — do you want to use old and low-quality data? Experian has provided organizations with high-quality consumer and business credit solutions for decades, and our industry-leading data sources, models and analytics allow you to build models and make confident decisions. If you need a sous-chef, Experian offers services and has data professionals who can help you create AI-powered predictive analytics models using bureau data, alternative data and your in-house data. Learn more about our AI analytics solutions and how you can get started today. 1DataCentricAI. (2023). Data-Centric AI.2Exchange.scale (2021). The Data-Centric AI Approach With Andrew Ng.3Experian (2021). Global Insights Report September/October 2021.4FinRegLab (2021). The Use of Machine Learning for Credit Underwriting: Market & Data Science Context. 5YouTube (2021). A Chat with Andrew on MLOps: From Model-Centric to Data-Centric AI *Disclaimer: When we refer to “Alternative Credit Data," this refers to the use of alternative data and its appropriate use in consumer credit lending decisions, as regulated by the Fair Credit Reporting Act. Hence, the term “Expanded FCRA Data" may also apply in this instance and both can be used interchangeably.

The Federal Reserve (Fed) took a big step towards revolutionizing the U.S. payment landscape with the official launch of FedNow, a new instant payment service, on July 20, 2023. While the new payment network offers advantages, there are concerns that fraudsters may be quick to exploit the new real-time technology with fraud schemes like automated push payment (APP) fraud. How is FedNow different from existing payment networks? To keep pace with regions across the globe and accelerate innovation, the U.S. created a alternative to the existing payment network known as The Clearing House (TCH) Real-Time Payment Network (RTP). Fraudsters can use the fact that real-time payments immediately settle to launder the stolen money through multiple channels quickly. The potential for this kind of fraud has led financial regulators to consider measures to better protect against it. While both FedNow and RTP charge a comparable fee of 4.5 cents per originated transaction, the key distinction lies in their governance. RTP is operated by a consortium of large banks, whereas FedNow falls under the jurisdiction of the Federal Reserve Bank. This distinction could give FedNow an edge in the market. One of the advantages of FedNow is its integration with the extensive Federal Reserve network, allowing smaller local banks across the country to access the service. RTP estimates accessibility to institutions holding approximately 90% of U.S. demand deposit accounts (DDAs), but currently only reaches 62% of DDAs due to limited participation from eligible institutions. What are real-time payments? Real-time payments refer to transactions between bank accounts that are initiated, cleared, and settled within seconds, regardless of the time or day. This immediacy enhances transparency and instills confidence in payments, which benefits consumers, banks and businesses.Image sourced from JaredFranklin.com Real-time payments have gained traction globally, with adoptions from over 70 countries on six continents. In 2022 alone, these transactions amounted to a staggering $195 billion, representing a remarkable year-over-year growth of 63%. India leads the pack with its Unified Payments Interface platform, processing a massive $89.5 billion in transaction volume. Other significant markets include Brazil, China, Thailand, and South Korea. The fact that real-time payments cannot be reversed promotes trust and ensures that contracts are upheld. This also encourages the development of new methods to make processes more efficient, like the ability to pay upon receiving the goods or services. These advancements are particularly crucial for small businesses, which disproportionately bear the burden of delayed payments, amounting to a staggering $3 trillion globally at any given time. The launch of FedNow marks a significant milestone in the U.S. financial landscape, propelling the country towards greater efficiency, transparency, and innovation in payments. However, it also brings a fair share of challenges, including the potential for increased fraud. Are real-time payments a catalyst for fraud? As the financial landscape evolves with the introduction of real-time payment systems, fraudsters are quick to exploit new technologies. One particular form of fraud that has gained prominence is authorized push payment (APP) fraud. APP fraud is a type of scam where fraudsters trick individuals or businesses into authorizing the transfer of funds from their bank accounts to accounts controlled by the fraudsters. The fraudster poses as a legitimate entity and deceives the victim into believing that there is an urgent need to transfer money. They gain the victim's trust and provide instructions for the transfer, typically through online or telephone banking channels. The victim willingly performs the payment, thinking it is legitimate, but realizes they have been scammed when communication halts. APP fraud is damaging as victims authorize the payments themselves, making it difficult for banks to recover the funds. To protect against APP fraud, it's important to be cautious, verify the legitimacy of requests independently, and report any suspicious activity promptly. Fraud detection and prevention with real-time payments Advances in fraud detection software, including machine learning and behavioral analytics, make unusual urgent requests and fake invoices easier to spot — in real time — but some governments are considering legislation to ensure more support for victims. For example, in the U.K., frameworks like Confirmation of Payee have rolled out instant account detail checks against the account holder’s name to help prevent cases of authorized push payment fraud. The U.K.’s real-time payments scheme Pay.UK also introduced the Mule Insights Tactical Solution (MITS), which tracks the flow of fraudulent transactions used in money laundering through bank and credit union accounts. It identifies these accounts and stops the proceeds of crimes from moving deeper into the system – and can help victims recover their funds. While fraud levels related to traditional payments have slowly come down, real-time payment-related fraud has recently skyrocketed. India, one of the primary innovators in the space, recorded a 23% rise in fraud related to its real-time payments system in 2022. The same ACI report stated that the U.S., making up only 1.2% of all real-time payment transactions in 2022, had, for now, avoided the effects. However, “there is no reason to assume that without action, the U.S. will not follow the path to crisis levels of APP scams as seen in other markets.” FedNow currently has no specific plans to bake fraud detection into their newly launched technology, meaning the response is left to financial institutions. Fight instant fraud with instant answers Artificial Intelligence (AI) holds tremendous potential in combating the ever-present threat of fraud. With AI technologies, financial institutions can process vast amounts of data points faster and enhance their fraud detection capabilities. This enables them to identify and flag suspicious transactions that deviate from the norm, mitigating identity risk and safeguarding customer accounts. The ability of AI-powered systems to ingest and analyze real-time information empowers institutions to stay one step ahead in the battle against account takeover fraud. This type of fraud, which poses a significant challenge to real-time payment systems, can be better addressed through AI-enabled tools. With ongoing monitoring of account behavior, such as the services provided by FraudNet, financial institutions gain a powerful weapon against APP fraud. In addition to behavioral analysis, location data has emerged as an asset in the fight against fraud. Incorporating location-based information into fraud detection algorithms has proven effective in pinpointing suspicious activities and reducing fraudulent incidents. As the financial industry continues to grapple with the constant evolution of fraud techniques, harnessing the potential of AI, coupled with comprehensive data analysis and innovative technologies, becomes crucial for securing the integrity of financial transactions. Taking your next step in the fight against fraud Ultimately, the effectiveness of fraud prevention measures depends on the implementation and continuous improvement of security protocols by financial institutions, regulators, and technology providers. By staying vigilant and employing appropriate safeguards, fraud risks in real-time payment systems, such as FedNow, can be minimized. To learn more about how Experian can help you leverage fraud prevention solutions, visit us online or request a call.  *This article leverages/includes content created by an AI language model and is intended to provide general information.

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