Fraud & Identity

To protect themselves against fraudulent applicants, apartment owners and operators need to leverage advanced screening tools and technologies.

Money mule fraud is a type of financial scam in which criminals exploit individuals, known as money mules, to transfer stolen money or the proceeds of illegal activities. Money mule accounts are becoming increasingly difficult to distinguish from legitimate customers, especially as criminals find new ways to develop hard-to-detect synthetic identities. How money mule fraud typically works: Recruitment: Fraudsters seek out potential money mules through various means, such as online job ads, social media, or email/messaging apps. They will often pose as legitimate employers offering job opportunities promising compensation or claiming to represent charitable organizations. Deception: Once a potential money mule is identified, the fraudsters use persuasive tactics to gain their trust. They may provide seemingly legitimate explanations like claiming the money is for investment purposes, charity donations or for facilitating business transactions. Money Transfer: The mule is instructed to receive funds to their bank or other financial account. The funds are typically transferred from other compromised bank accounts obtained through phishing or hacking. The mule is then instructed to transfer the money to another account, sometimes located overseas. Layering: To mask the origin of funds and make them difficult to trace, fraudsters will employ layering techniques. They may ask the mule to split funds into smaller amounts, make multiple transfers to different accounts, or use various financial platforms such as money services or crypto. Compensation: The money mule is often promised a percentage of transferred funds as payment.  However, the promised monies are lower than the dollars transferred, or sometimes the mule receives no payment at all. Legal consequences: Regardless whether mules know they are supporting a criminal enterprise or are unaware, they can face criminal charges. In addition, their personal information could be compromised leading to identity theft and financial loss. How can banks get ahead of the money mule curve: Know your beneficiaries Monitor inbound paymentsEngage identity verification solutionsCreate a “Mule Persona” behavior profileBeware that fraudsters will coach the mule, therefore confirmation of payee is no longer a detection solution Educate your customers to be wary of job offers that seem too good to be true and remain vigilant of requests to receive and transfer money, particularly from unknown individuals and organizations. How financial institutions can mitigate money mule fraud risk When new accounts are opened, a financial institution usually doesn’t have enough information to establish patterns of behavior with newly registered users and devices the way they can with existing users. However, an anti-fraud system should catch a known behavior profile that has been previously identified as malicious. In this situation, the best practice is to compare the new account holder’s behavior against a representative pool of customers, which will analyze things like: Spending behavior compared to the averagePayee profileSequence of actionsNavigation data related to machine-like or bot behaviorAbnormal or risky locationsThe account owner's relations to other users The risk engine needs to be able to collect and score data across all digital channels to allow the financial institution to detect all possible relationships to users, IP addresses and devices that have proven fraud behavior. This includes information about the user, account, location, device, session and payee, among others. If the system notices any unusual changes in the account holder’s personal information, the decision engine will flag it for review. It can then be actively monitored and investigated, if necessary. The benefits of machine learning This is a type of artificial intelligence (AI) that can analyze vast amounts of disparate data across digital channels in real time. Anti-fraud systems based on AI analytics and predictive analytics models have the ability to aggregate and analyze data on multiple levels. This allows a financial institution to instantly detect all possible relationships across users, devices, transactions and channels to more accurately identify fraudulent activity. When suspicious behavior is flagged via a high risk score, the risk engine can then drive a dynamic workflow change to step up security or drive a manual review process. It can then be actively monitored by the fraud prevention team and escalated for investigation. How Experian can help Experian’s fraud prevention solutions incorporate technology, identity-authentication tools and the combination of machine learning analytics with Experian’s proprietary and partner data to return optimal decisions to protect your customers and your business. To learn more about how Experian can help you leverage fraud prevention solutions, visit us online or request a call

The rapid acceleration of digital shopping and transactions highlights the need for marketplaces to refine their fraud and identity proofing strategies.

Identity document verification safeguards the integrity of financial systems and protects consumers and organizations from fraud, money laundering and more.

The ability to verify customer identities is essential for financial institutions for numerous reasons: regulatory requirements, for the protection of their consumers and their business, mitigating risk and more. Being able to detect high-risk customers and large transactions is a critical component of Know Your Customer (KYC) strategies. In addition to being good business practices, this type of risk mitigation is also outlined in industry regulations. In an increasingly complex regulatory environment, companies may be faced with meeting multiple KYC and Anti-Money Laundering (AML) requirements. Actions taken to validate customers such as enhanced due diligence in KYC compliance have impacts spanning far beyond just regulatory compliance. As with any business, bottom line and budget are primary drivers for many financial institutions. Enhanced due diligence (EDD) can positively impact a business's bottom line by contributing to the reduction of fraud rates. And with increased security to discover potential fraudsters, organizations can protect both customers and reputational value. Enhanced due diligence explained: Why KYC, CIP and AML are critical in financial services EDD takes Customer Due Diligence (CDD) to the next level. Financial institutions conduct CDD to protect their organizations from financial crime. CDD is also a critical component of KYC steps to comply with AML laws. AML legislation requires financial institutions to validate their customers to ensure they aren’t part of explicitly illegal financial activity or funding terrorism. EDD is, as it sounds, a more involved form of due diligence, which encompasses additional procedures. EDD involves determining a customer’s risk, often requiring additional information and evidence to determine their viability. While CDD is performed on all customers, EDD is reserved for high-risk potential customers. Because EDD is often more costly and involved in terms of time and resources, a risk-based approach is recommended to flag only the instances when this additional level of validity is required. KYC references the mandatory process of identifying and verifying a client’s identity at account opening and over the course of their relationship with a company to ensure they are the person they say they are. KYC consists of three parts: Customer identification program (CIP), CDD and EDD. CIP requires, at minimum, that financial institutions provide four pieces of identifying information including name, date of birth, address and identification number. CDD consists of classifying the identifying information that was collected. After identifying who the client is (via CIP), CDD assesses the information to determine risk. Enhanced due diligence in KYC In order to establish a competent EDD program, you must improve your CIP and KYC programs. Objective, automated and efficient identity verification capabilities help you acquire profitable, legitimate customers and monitor them effectively over time to meet regulatory compliance expectations. How can EDD benefit your business? Failing to comply with EDD regulations can result in countless risks for financial institutions like fines and reputational losses. While many customers pose little to no risk, high-risk individuals must be flagged quickly and efficiently. The primary benefit of EDD is to protect both financial institutions and their customers from financial crimes such as money laundering and terrorist financing, but there are other risks as well. By mitigating potential risks associated with higher-risk customers, EDD can prevent financial institutions from incurring regulatory fines, legal action, and damage to their reputation. In turn, this ensures that customers have more trust in their financial service providers. Financial institutions can then gain a competitive advantage by offering more secure financial products and services that investors, businesses and customer demand. Access EDD from Experian Experian leverages our advanced analytics, reliable data sources, and team of experts to conduct objective, full and comprehensive due diligence with confidence and certainty. Our solutions, including flexible monitoring and segmentation tools, allow you to resolve discrepancies and fraud risk in a single step, all while keeping pace with emerging fraud threats with effective customer identification software. Improving your Customer Identification Program (CIP) and KYC programs In conclusion, Enhanced Due Diligence in KYC, CIP, and AML are critical components of the financial services regulatory compliance framework. EDD goes beyond the standard KYC, CIP, and AML checks to mitigate risks associated with higher-risk customers. Implementing EDD can help financial institutions comply with regulatory requirements, protect against potential risks, and prevent financial crimes. Ultimately, this benefits not only the institutions but also their customers and the broader economy. It’s vital that financial institutions understand and appreciate the importance of EDD and take appropriate measures to implement it effectively. Experian offers objective, automated and efficient identity verification solutions to help you acquire profitable, legitimate customers and monitor them over time to meet regulatory compliance expectations. Discover the power of CIP and KYC solutions. Learn more

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

By leveraging an array of tools and technologies, businesses can tailor their fraud prevention strategies to suit the specific needs of their customers.

With an ever-present need for efficiency, security, and seamless citizen services, many agencies are looking at the benefits of a data-driven government. Last year, the federal government kicked off a unified effort to enable data-driven decision making. The goal at that level – and across all agencies – is to serve citizens more efficiently and effectively. By embracing the power of data and analytics, agencies of all sizes can set themselves up to better serve their citizens. What is a data-driven government? Agencies collect citizen data from a variety of service-based sources, including the Postal Service, Census Bureau, social welfare departments, and agencies that issue government IDs. When properly leveraged, this data holds many possibilities. However, many agencies face challenges when it comes to efficient collection, sharing, usage, integrity, and accessibility. Due to the amount of data collected and the potential lack of consistency in the collection and storage techniques, the data may not be usable. Without proper management and analysis, there’s little government agencies can do with their data to improve their processes. A data-driven government has well-managed data and uses that data to drive their decisions as they relate to citizen requests for benefits, tax collection, elections, and more. What are the benefits of data-driven decision making? Data management and government data analytics enable agencies to react quickly to citizen demands and concerns and proactively anticipate an issue before it becomes a crisis. With the right tools, agencies can gain a holistic view of their citizens, communicate effectively internally, provide digitally-driven services and improve overall efficiency through government-wide data integration and management. These changes have a wide range of benefits, including reduction of cost, fraud, waste and abuse, the automation of manual processes, and better service delivery. Why is a data-driven strategy required? In addition to the benefits listed above, a data-driven strategy also helps agencies align with published NIST guidelines and the need to monitor, evaluate, and maintain digital identity systems. Proper use of data-driven digital identity strategies will enhance equity and the usability of the solutions agencies provide to their citizens. Building an effective data-driven strategy The right strategy starts with ensuring that all departments about the need for proper data management and analytics and the guidelines that will govern it, such as maintaining up-to-date data, removing silos, and leveraging the right tools. The next step is finding the right partner. An effective partner can help agencies develop and maintain data management systems and implement the right tools and analytics – things like machine learning in government – to help each agency function efficiently and safeguard the data of its citizens. To learn how Experian can help your agency improve its use of data, visit us or request a call. Visit us

CrossCore named Overall Leader, Product Leader in Fraud Reduction Intelligence Platforms, Innovation Leader and Market Leader in Fraud Reduction..

Jennifer Schulz, CEO of Experian, North America kicked off Experian’s annual Vision conference Tuesday morning pointing to data, analytics, technology and collective curiosity as the drivers for change and a more impactful tomorrow to more than 700 attendees. Keynote speaker: Jennifer Bailey Jennifer Bailey, Vice President of Apple Pay and Apple Wallet, spoke about the customer experience “ethos.” She explained how Apple takes a long-term view and values the single most important performance metric as customer experience. She said creating a seamless customer experience comes down to making things simple and understandable, and asking, “Are we solving a customer problem?” and “How are we making it easier for customers to enjoy and liver their lives. Bailey, who said of all apps she uses the weather app the most, also talked about innovation, and that both intent and making mistakes are important parts of the process. Apple’s products are known for their user-friendliness, and design is part of that. She encouraged the audience to give design teams room to create without bottom line pressures and not to be afraid to take well-considered risks. Keynote Speaker: Gary Cohn Gary Cohn, Vice Chairman of IBM, talked about the current economic climate, and while it’s a natural viewpoint to look to the past for guidance, the current environment is unlike any before. Cohn discussed regulatory compliance in the banking industry and prioritizing safety and soundness. While AI is topical and in numerous headlines recently, Cohn reminded the conference goers that AI isn’t new. He said what is new and important is that you can now teach models to find the information needed rather than having to feed all the information yourself. He believes AI is not the end of employment, but rather helps boost productivity, efficiency, and job satisfaction and provides organizations more data. As for advice for the audience, Cohn shared opportunities are in the uncomfortable zones and you have to be willing to fail in order to succeed. Session highlights – Day 1 The conference hall was buzzing with conversations, discussions and thought leadership. Overall themes that were frequently part of the conversation included seamless customer experiences, agility in face of economic changes and leveraging AI/ML into strategies. Fraud automation and preventing commercial fraud More businesses are opening than ever before and lenders and service providers need a way to determine risk from businesses who are less than a year old. There is no one-size-fits-all approach to fraud. A layered solution assesses risk and applies the correct friction to resolve the risk and pass or refer the applicant. Identity Today’s consumer wants a personalized experience and is privacy conscious. Additionally, regulators are also pushing for greater privacy. Clean rooms allow you and a partner to add data to a safe space and learn more about consumers without exposing data. The right data improves acquisition rates, identity verification and allows you to anticipate customer needs. Advanced scoring Data, models and strategy are the levers institutions are using to leverage responsible analytics to meet their objectives like safely growing existing portfolios, managing the “right” level of risk, and providing a seamless digital experience. However, the total value of a decisioning system is almost always constrained by its most rudimentary component. The panel of experts discussed their uses and goals for leveraging models and customer experience was at the top of their priorities. Recession preparedness Delinquency is on the rise and lending offers made continue to drop. Changes in the economic climate require frequent monitoring of portfolio and decisions, benchmarking against peers, updating credit models and decision strategies, and stress testing portfolio and models. Trends in credit risk management While AI at the hands of everyone is topical today, it ranked lowest on the list of trends attendees believed were impacting their business. At the top of the list? The growing demand for simpler, faster and seamless experiences. More insights from Vision to come. Follow @ExperianVision and @ExperianInsights to see more of the action.

During their redeterminations process stats should look for efficiency and a risk-based approach to ensure compliance during the unwinding process.

As organizations look for ways to keep themselves and the consumers they serve safe in the digital era, many turn to fraud risk mitigation.

There’s an undeniable link between economic and fraud trends. During times of economic stress, fraudsters engage in activities specifically designed to target strained consumers and businesses. By layering risk management and fraud prevention tools, your organization can manage focus on growing safely. Download infographic Review your fraud strategy  

What Is Identity Proofing? Identity proofing, authentication and management are becoming increasingly complex and essential aspects of running a successful enterprise. Organizations need to get identity right if they want to comply with regulatory requirements and combat fraud. It's also becoming table stakes for making your customers feel safe and recognized. 63 percent of consumers expect businesses to recognize them online, and 48 percent say they're more trusting of businesses when they demonstrate signs of security. Identify proofing is the process organizations use to collect, validate and verify information about someone. There are two goals — to confirm that the identity is real (i.e., it's not a synthetic identity) and to confirm that the person presenting the identity is its true owner. The identity proofing process also relates to and may overlap with other aspects of identity management. Identity proofing vs identity authentication Identity proofing generally takes place during the acquisition or origination stages of the customer lifecycle — before someone creates an account or signs up for a service. Identity authentication is the ongoing process of re-checking someone's identity or verifying that they have the authorization to make a request, such as when they're logging into an account or trying to make a large transaction. How does identity proofing work? Identity proofing typically involves three steps: resolution, validation, and verification. Resolution: The goal of the first step is to accurately identify the single, unique individual that the identity represents. Resolution is relatively easy when detailed identity information is provided. In the real world, collecting detailed data conflicts with the need to provide a good customer experience. Resolution still has to occur, but organizations have to resolve identities with the minimum amount of information. Validation: The validation step involves verifying that the person's information and documentation are legitimate, accurate and up to date. It potentially involves requesting additional evidence based on the level of assurance you need. Verification: The final step confirms that the claimed identity actually belongs to the person submitting the information. It may involve comparing physical documents or biometric data and liveness tests, such as a comparison of the driver's license to a selfie that the person uploads. Different levels of identity proofing may require various combinations of these steps, with higher-risk scenarios calling for additional checks such as biometric or address verification. Service providers can implement a range of methods based on their specific needs, including document verification, database validation, or knowledge-based authentication. Building an effective identity proofing strategy By requiring identity proofing before account opening, organizations can help detect and deter identity fraud and other crimes. You can use different online identity verification methods to implement an effective digital identity proofing and management system. These may include: Document verification plus biometric data: The consumer uploads a copy of an identification document, such as a driver's license, and takes a selfie or records a live video of their face. Database validations: The proofing solution verifies the shared identifying information, such as a name, date of birth, address and Social Security number against trusted databases, including credit bureau and government agency data. Knowledge-based authentication (KBA): The consumer answers knowledge-based questions, such as account information, to confirm their identity. It can be a helpful additional step, but they offer a low level of assurance, partially because data breaches have exposed many people's personal information. In part, the processes you'll use may depend on business policies, associated risks and industry regulations, such as know your customer (KYC) and anti-money laundering (AML) requirements. But organizations also have to balance security and ease of use. Each additional check or requirement you add to the identity proofing flow can help detect and prevent fraud, but the added friction they bring to your onboarding process can also leave customers frustrated — and even lead to customers abandoning the process altogether. Finding the right amount of friction can require a layered, risk-based approach. And running different checks during identity proofing can help you gauge the risk involved. For example, comparing information about a device, such as its location and IP address, to the information on an application. Or sending a one-time password (OTP) to a mobile device and checking whether the phone number is registered to the applicant's name. With the proper systems in place, you can use high-risk signals to dynamically adjust the proofing flow and require additional identity documents and checks. At the same time, if you already have a high level of assurance about the person's identity, you can allow them to quickly move through a low-friction flow. Experian goes beyond identity proofing Experian builds on its decades of experience with identity management and access to multidimensional data sources to help organizations onboard, authenticate and manage customer identities. Our identity proofing solutions are compliant with National Institute of Standards and Technology (NIST) and enable agencies to confidently verify user identities prior to or during account opening, biometric enrollment or while signing up for services. Learn more   This article includes content created by an AI language model and is intended to provide general information.