Tag: Identity & Fraud

By leveraging insights from leading industry analysts, Experian's expertise, extensive market studies, and market sentiment, we identified four key themes shaping the financial services sector this year. Read now Four themes impacting financial services this year: 1. Fraud evolution driven by AI Tracking synthetic identities is a big challenge for FIs in 2025, exacerbated by fraudsters' use of Gen AI tools to scale activities. Investment in AI is a growing priority as banks seek to strengthen identity verification. Account takeover (ATO) and Authorised Push Payment Fraud (APP) are also growing problems very much linked to advanced AI methods employed by criminals. Collaboration across institutions and the adoption of advanced analytics will be critical in staying ahead of fraudsters. 2. Advanced AI will improve operational efficiencies in new ways GenAI and Agentic AI (an orchestration tool connecting multiple AI models) are unlocking new levels of efficiency and personalisation. The emphasis on adoption is twofold: first, automating steps to accelerate development and delivery, and second, ensuring transparency, compliance, and governance. Businesses need to take an incremental approach to GenAI adoption, with centralised governance and a focus on explainability. AI will improve mid-office processes where internal manual inefficiencies impact downstream customer interactions. 3. Emergence of RegTech to meet complexities of compliance Heightened regulatory scrutiny is driving the adoption of innovative compliance technologies. Adopting cloud-native, modular systems supports more agile compliance strategies and reduces the cost and complexity of updating solutions. Explainable AI is increasingly essential for demonstrating compliance and fostering regulator confidence in automated decision-making. 4. Convergence of risk management The integration of fraud prevention, credit risk assessment, and compliance is a growing trend among financial institutions. Digital identity frameworks and unified data analytics are becoming essential for holistic risk management. Banks need to embrace collaborative approaches and consortium-level partnerships to address interconnected challenges. Read the report

Experian's new global report is now available on how businesses can enhance efficiency, insights, and growth through integration to transform the future of risk strategy. Download report In the ever-evolving financial landscape, the convergence of credit risk, fraud risk, and compliance is becoming a game-changer. Financial institutions (FIs) increasingly recognise the need to integrate these functions to enhance efficiency, gain deeper insights, and drive growth. The 2024 global report on the convergence of credit, fraud, and compliance sheds light on this critical transformation, emphasising how a unified strategy can revolutionise risk management. The report highlights the importance of convergence in shaping the future of financial services. We surveyed 750 leaders in credit risk, fraud risk and compliance in financial services organisations across the world. Inside the report: The need for convergence As technology advances, financial institutions (FIs) face the dual challenge of managing complex systems while simplifying consumer processes. The report reveals that organisations use an average of eight tools across credit, fraud, and compliance, with some using more than ten. This fragmentation leads to inefficiencies and increased risks.In addition, 79% of respondents want to work with fewer vendors to manage credit risk, fraud, and compliance, underscoring the need for streamlined operations. Independent evolution of functions and associated challenges Credit risk, fraud risk, and compliance functions have evolved independently, creating operational silos and technology management challenges. This separation has led to increased fraud and credit losses. The report highlights that only 9% of organisations prioritise these functions equally, with most focusing on fraud. However, 87% of respondents acknowledge the overlap between these areas and are working towards closer collaboration. Regulatory pressures and advanced fraud techniques New regulations in the US, UK, and EU are compelling FIs to reimburse consumers for losses due to scams, increasing the liability for both sending and receiving banks. Penalties for failing to implement effective Anti-Money Laundering (AML) solutions have also intensified. These regulatory demands and advanced fraud techniques necessitate a more integrated approach to risk management. Early stages of convergence While the market is beginning to recognise the benefits of convergence, many FIs are still in the early stages of this journey. The convergence speed varies, but mature organisations have already started or plan to start the process soon. The report shows that 91% of respondents believe that forward-looking companies will centralise these functions within the next three years. However, only 15% prefer a 'point solution', 36% prefer a single integrated solution, and 49% prefer modular integration. The role of technology Technology plays a crucial role in integrating functions and managing risk. Next-generation platforms are essential for adapting to market needs, delivering innovative products, and meeting regulatory requirements. The report emphasises the importance of data aggregation, which combines diverse data for deeper insights, and the integration of credit decisioning and fraud detection solutions to balance risk and growth goals simultaneously. Improving risk management through alignment Correctly identifying consumers, managing fraud risk, making informed credit decisions, and ensuring compliance share common ground. The report shows that 57% of respondents believe aligning credit risk, fraud, and compliance functions leads to better overall risk management. Businesses with more centralised practices report improved risk management effectiveness, operational efficiencies, and data integrity. Benefits of convergence The convergence of credit risk, fraud, and compliance offers numerous benefits, including: Improved risk management effectiveness: Better alignment leads to more effective risk management strategies. Operational efficiencies: Streamlined processes and reduced duplication of efforts enhance operational efficiency. Increased data integrity: Centralised data management ensures consistency and accuracy. Cost reduction: Consolidation of functions and technology reduces costs. Enhanced customer experience: A unified approach improves customer recognition and service across all channels. Read the report to find out how to prove value through integration. Download report

Using business and consumer quantitative and qualitative research from the UK, US, Brazil, EMEA, and APAC between 2023 and 2024, we assess the current global impact of fraud. Download now As 2024 draws to a close, businesses face an increasingly hostile environment in the battle against fraud. Driven by rapid technological advancement and evolving regulatory landscapes, organisations seek new ways to prevent and detect highly sophisticated attacks. Experian’s 2024 Global Fraud Report offers a deep dive into the current state of fraud, revealing critical insights and strategies businesses must adopt to stay ahead of fraudsters. Read the report to discover: Why security and customer experience are still in conflict In today’s digital age, businesses face the daunting task of balancing robust fraud prevention with a seamless customer experience. The report highlights that while stringent security measures are essential, unnecessary friction can drive customers away. A multi-layered approach to fraud prevention, integrating advanced technologies with customer-friendly practices, is crucial. The power of data sharing Data sharing has emerged as a powerful tool in the fight against fraud. By collaborating and sharing data across industries, businesses can gain a comprehensive view of fraud patterns and enhance their detection capabilities. Regulatory frameworks in regions like Brazil and the UK increasingly support data-sharing initiatives, which are vital for effective fraud prevention. What the rise in Authorised Push Payment Fraud means for businesses APP fraud has seen a significant rise in some parts of the world due to newly accessible GenAI tools enabling fraudsters to create more convincing scams at scale. Financial institutions are under pressure to implement measures to protect consumers and comply with new regulations that mandate reimbursement for APP fraud victims. How to uncover synthetic identities Synthetic identity fraud is a growing concern. The report reveals that advancements in GenAI have enabled the creation of highly realistic fake identities, making detection more challenging. Businesses need to invest in advanced analytics and alternative data sources to uncover synthetic identities effectively. Why AI and machine learning are critical to fraud prevention AI and machine learning are pivotal in modern fraud prevention strategies. The report underscores the necessity of these technologies in detecting and preventing fraud. AI and machine learning can analyse vast amounts of data to identify patterns and anomalies that may indicate fraudulent activity. Download the report to discover the 5 key takeaways to combat evolving fraud The 2024 Global Fraud Report reinforces the need for businesses to leverage advanced analytics, alternative data insights, data sharing, and a multi-layered approach to combat evolving fraud threats globally. Download report now About the research The 2024 Global Identity and Fraud Report uses the latest research from the United States, the United Kingdom, Brazil, EMEA, and APAC between 2023 and 2024 to examine fraud worldwide. The research provides combined insights globally from over 1,000 businesses and fraud leaders, as well as 4,000 consumers, focusing on fraud management and digital experience. See the report appendix for full details of the research.

Download eBook How to deploy a multi-layered approach with a holistic view of the consumer to stay ahead of evolving fraud. Find out how to mitigate against GenAI-enhanced fraud by downloading the eBook GenAI's rise to the top has been rapid. It was only last year that GenAI fully emerged in the public domain as an accessible tool, with the technology's impact and expectations reverberating across businesses worldwide. This massive growth trajectory has led some critics to suggest that GenAI is nearing its hype peak. However, its potential is still unfolding as the technology continues to evolve and be applied to new use cases. Although its positive applications have enormous potential, the technology also poses many risks. In the fraud space, GenAI poses two main threats: The scaling and personalisation of attacks. Criminals today are generating synthetic content with a goal of decieving businesses and individuals. Fraudsters leverage GenAI to produce convincing synthetic identities and deepfakes that include audio, images, and videos that are increasingly sophisticated and practically impossible to differentiate from genuine content without the help of technology. Fraudsters also exploit the power of Large Language Models (LLMs) by creating eloquent chatbots and elaborate phishing emails to help them steal vital information or establish communication with their targets. Mitigation comes in many forms, depending on the business, but the fundamental differentiator in the fight against evolving and increasing fraud attempts is the ability to have a holistic view of the consumer. Businesses today deploy multiple solutions from various vendors to ensure fraud mitigation covers all touchpoints. Although full coverage may exist, businesses often don’t have a holistic offline and digital view of the consumer, meaning losses can accumulate before patterns emerge within these siloed views. Rapidly evolving, highly automated, and large-scale attacks demand an up-to-date cross-industry view of online and offline identity behavior, linkages, and interactions. The flexible solution must similarly leverage GenAI to spot and validate fraud signals, interpret intelligence from fraud analysts, and quickly operationalize new attributes and models to keep pace with attackers. This is where layered fraud and identity controls in real time and a comprehensive offline analytics platform work together Download the eBook to discover: The rise of GenAI GenAI impact by fraud type Deepfakes: The authenticity challenge The challenge of detecting synthetic identoties Scaling up: The emergence of bot-as-a-service Authorised Push Payment Fraud (APP Fraud) Understanding the role of intent and context in fraud prevention A holistic view of the consumer with Ascend Fraud Sandbox Key takeaways: Find out how to mitigate against GenAI-enhanced fraud Businesses that implement these recommendations will be best equipped to manage fraud spikes from GenAI while simultaneously protecting good customer experiences from being negatively impacted by unnecessary friction. Ascend Fraud Sandbox helps businesses to shine a light on the holistic view of consumer activity across the industry, moving far beyond the typical point-in-time, product-specific view of consumers.Mike Gross, Vice President, appled fraud research and analytics, experian Download eBook

Experian has been named a leader in Liminal’s Link Index for Account Takeover Prevention in Banking. Download Report Advances in technology have increased the scale and sophistication of fraud attacks for businesses around the globe with a significant increase in recent years in account takeover fraud (ATO). During the pandemic there was a rise in account opening attacks as the world moved in lockstep to digital channels, creating huge growth in online digital accounts. Now fraudsters are attempting to takeover those digital accounts and are leveraging AI tools to convince consumers to give away their login credentials, creating an enormous financial risk and loss for banks and other service providers. In a March 2024 survey of bank buyers across North America, Europe, Latin America, Asia Pacific, and the Middle East, Liminal found that ATO attacks now average $6,232 per incident, while fraud teams have reported a 66.8% increase in social engineering attacks in the past two years. However, Liminal also found that despite the growing exposure, only 44% of banks are leveraging mobile device signals. The opportunity for banks to implement more effective tools is the result of a combination of factors: 96% are worried about balancing ATO prevention with privacy laws. 82% say customization was necessary to comply with regional regulations. 96% have concerns about limitations on device signals stemming from data restrictions with consumer technologies. As a result, banks are faced with a three-pronged problem: simultaneously solving for authentication, identity and fraud prevention. Identity across the customer lifecycle Truly understanding a customer, especially in a digital-first environment where hundreds of billions of events occur each year, requires much more than ensuring a name matches a social security number and a physical address. The customer, their account information, the device they use, the network they are coming from, the geolocation of their device, and the behavior they exhibit are intertwined. Banks must now assess more information than ever before to try to distinguish between a legitimate customer and fraudsters. This challenge only gets harder when businesses require more complex passwords, which users promptly forget. Fraudsters, ever creative, exploit the password reset processes to impersonate the customer and convince businesses to give them the new reset password. In ATO attacks, often the only data presented to a business by the user at the time of login is a username and password. However, there are hundreds of other variables that may be passed back and forth between the device and the business in that digital moment, which can be useful for identifying potential threats or legitimate users. This exercise can be a monumental task that involves capturing vast data sets, knowing the difference between critical data and data that increases workload, analyzing that data and then marrying that back to what you know about the customer, all in a few milliseconds. And this is where one of the biggest hurdles exists. These vast data sets sit across a complex set of systems and technologies that have been implemented (but not fully integrated) over time. And consider within this context, the authentication team managing ATO that would otherwise benefit from a cohesive set of data isn’t usually aligned with the general fraud teams and is even further separated from the credit risk or compliance teams. These gaps in technologies and teams hinder ATO prevention and provide zero support for any interdependencies with other critical functions – and fraudsters are more than happy to exploit this weakness. On the other hand, managing a more complete view of the customer (which allows the business to streamline operational costs, data costs, and infrastructure costs) to prevent more ATO attacks and provide a more seamless experiences for the consumer has never been more possible. A fundamental shift in mindset is required to prevent fraudsters from exploiting gaps between business functions. Legitimate customers do not care about these internal divisions; they only see the inconsistency when one part of the business has no knowledge of them compared to another. This disconnect not only frustrates customers but also undermines trust and security. To effectively combat ATO attacks, financial institutions must leverage comprehensive data insights that cover various touchpoints. Integrating identity verification, device intelligence, and behavioral analytics is essential for distinguishing legitimate users from fraudsters. Breaking down traditional silos and enabling seamless data sharing ensures a holistic approach to fraud prevention, delivering a secure and frictionless customer experience. Liminal, a leading market intelligence firm specialising in digital identity, cybersecurity, and fintech markets, recently named Experian as a leader in its Link Index for ATO Prevention in Banking. Leading in ATO prevention The report highlights vendors that lead in authentication, fraud and identity and based on two primary criteria: product execution and strategic positioning. As a top-ranked vendor overall and in product execution, Experian’s performance underscores the effective integration of identity management in our solutions, positioning us as a leader in shaping strategies for account takeover prevention over the next five years. Download Liminal’s Link Index for ATO Prevention in Banking “When it comes to ATO prevention, banks are prioritizing highly accurate solutions that minimize fraud losses and limit financial loss, while reducing customer abandonment through a seamless user experience. Overall satisfaction is most strongly correlated with scalability. As a leader in this evaluation, Experian not only delivers these capabilities to banks, it also demonstrates an unparalleled ability to meet the market’s growing demand, which is projected to reach $1.5 billion by 2028.” Will Charnley, Chief Operating Officer, Liminal The report details the trends that are fundamentally reshaping the ATO threat landscape and today’s specific challenges, as well as those on the horizon, that banks must overcome, while also meeting an increasing expectation of customer satisfaction. Key statistics detail a prescriptive assessment of the market landscape and total addressable market, as well as findings from a March 2024 survey of banks conducted by Liminal, which includes: Specific key purchasing criteria (KPC). The scale and average cost (by volume and per incident) of ATO attacks. A descriptive methodology for calculating fraud loss opportunity costs. A priority-tiered description of ATO solution capabilities. As banks continue to operate in a competitive digital environment that favours excellent customer experience in parallel with fraud prevention, it is crucial to recognize that the front-end experience mirrors back-end operations; therefore, creating seamless integration on both sides is critical. Download Report CrossCoreR provides a fully-featured toolkit that leverages a wide range of capabilities for highly accurate and scalable ATO prevention.

New IDC MarketScape: Worldwide Enterprise Fraud Solutions 2024 Vendor assessment provides valuable resource as organizations face increased fraud. With fraud scam losses reported to have reached $10bn in 2023*, preventing fraud in today's digital landscape has become increasingly complex. As organizations continue to leverage advanced technologies, fraudsters have also evolved, employing ever more sophisticated techniques. Striking the balance between robust fraud prevention and delivering a seamless digital experience to customers has become a priority for organizations, with customer experience (CX) proving to be a competitive differentiator in a market with high digital expectations. Why real-time detection matters for CX As techniques employed by fraudsters get faster, so does the need for quick and effective fraud detection, making real-time solutions increasingly important during a period of rapid technological advancement. The development of real-time fraud solutions not only minimizes financial losses, but it has also paved the way for frictionless customer journeys, with identity and fraud checks no longer impeding customer experience. Using machine learning to leverage data and enable fraud detection To enable real-time detection, proactive fraud prevention also requires the analysis of vast amounts of data. Deploying static rules to identify anomalies in data does not allow for nuance because the thresholds within the rules are fixed, and therefore real-time patterns cannot be adjusted to within the model. Machine learning not only allows businesses to leverage data more effectively through analysis, allowing for flexibility within the parameters, but it also removes some manual processes, improving efficiency by updating models faster into production. Approving good customers is the number one priority for businesses, and a frictionless digital customer journey is the catalyst for this. To minimize financial losses while reducing the overall number of fraud incidents, organizations are looking to real-time fraud detection, enabled by machine learning. "As fraud risk losses continue to increase, the pursuit of fraud risk management solutions designed to identify, mitigate, and prevent fraud incidents and losses is a topic with increasing focus within financial services.” Sean O'Malley, research director, IDC Financial Insights: Worldwide Compliance, Fraud and Risk Analytics Strategies IDC, the premier global market intelligence firm, released its latest IDC MarketScape: Worldwide Enterprise Fraud Solutions, providing a valuable resource to buyers looking for new solutions in the market. Download excerpt of IDC MarketScape: Worldwide Enterprise Fraud Solutions 2024 Vendor Assessment The report highlights: Fraud solutions are increasingly moving toward real-time fraud detection and prevention. There are significant enhancements in technological capabilities, particularly with respect to cloud computing. Some newer fraud solutions take advantage of the increased computing power that is available to both expand the data sets being used to identify potential fraud incidents and enhance the models designed to detect, mitigate, and prevent fraud. Experian is recognized as a leader in this report. The IDC MarketScape notes, “In addition to evaluating the transactional data for potential fraud, Experian's CrossCore solution includes identity-authentication tools. The solution uses identity data, device intelligence, email and phone intelligence, alternative identity data, biometrics, behavioral biometrics, one-time passwords, and document verification to confirm identities and aid with identity protection, including synthetic identity protection. Experian utilizes multiple data partnerships in its fraud solution, which often can help provide a more comprehensive understanding of fraud risks and exposures.” To achieve a frictionless and secure customer experience, it is the integration of digital identity and fraud risk that is creating a gold standard for businesses. A siloed approach to fraud prevention not only leaves gaps for criminals to exploit, but it also presents consequences for customer experience too. The ability to layer multiple fraud capabilities together in a synchronized effort to achieve the best analytics-driven output possible can allow businesses to have the flexibility within their user journeys to optimize and control the order in which capabilities are called, removing friction, and ensuring good customers are successfully onboarded. Add in a final layer of machine learning to ensure the deployment of unified decisioning, and businesses are left with cohesive and explainable decisions. At Experian, we are working diligently to stay on the cutting edge of fraud and identity. In addition to our proprietary credit data on over 1.5 billion consumers and over 200 million businesses, Experian leverages a unique curated partner ecosystem to provide a more comprehensive understanding of fraud risks and exposures. Our powerful technology platform enables users to leverage a wide range of tools to combat their customized fraud challenges. Download Report Excerpt More on Crosscore® *IDC MarketScape: Worldwide Enterprise Fraud Solutions 2024 Vendor Assessment

We explore four fraud trends likely to be influenced the most by GEN AI technology in 2024, and what businesses can do to prevent them. 2023: The rise of Generative AI 2023 was marked by the rise of Generative Artificial Intelligence (GEN AI), with the technology’s impact (and potential impact) reverberating across businesses around the world. 2023 also witnessed the democratisation of GEN AI, with its usage made publicly available through multiple apps and tools such as Open AI's Chat GPT and DALL·E, Google's Bard, Midjourney, and many others. Chat GPT even held the world record for the fastest growing application in history (until it was surpassed by Threads) after reaching 100 million users in January 2023, just less than 2 months after its launch. The profound impact of GEN AI on everyday life is also reflected in the 2023 Word of the Year (WOTY) lists published by some of the biggest dictionaries in the world. Merriam-Webster’s WOTY for 2023 was 'authentic'— a term that people are thinking about, writing about, aspiring to, and judging more than ever. It's also not a surprise that one of the other words outlined by the dictionary was 'deepfake', referencing the importance of GEN AI-inspired technology over the past 12 months. Among other dictionaries that publish WOTY lists, both Cambridge Dictionary and Dictionary.com chose 'hallucinate' - with new definitions of the verb describing false information produced by AI tools being presented as truth or fact. A finalist in the Oxford list was the word 'prompt', referencing the instructions that are given to AI algorithms to influence the content it generates. Finally, Collins English Dictionary announced 'AI' as their WOTY to illustrate the significance of the technology throughout 2023. GEN AI has many potential positive applications from streamlining business processes, providing creative support for various industries such as architecture, design, or entertainment, to significantly impacting healthcare or education. However, as signalled out by some of the WOTY lists, it also poses many risks. One of the biggest threats is its adoption by criminals to generate synthetic content that has the potential to deceive businesses and individuals. Unfortunately, easy-to-use, and widely available GEN AI tools have also created a low entrance point for those willing to commit illegal activities. Threat actors leverage GEN AI to produce convincing deepfakes that include audio, images, and videos that are increasingly sophisticated and practically impossible to differentiate from genuine content without the help of technology. They are also exploiting the power of Large Language Models (LLMs) by creating eloquent chatbots and elaborate phishing emails to help them steal important information or establish initial communication with their targets. GEN AI fraud trends to watch out for in 2024 As the lines between authentic and synthetic blur more than ever before, here are four fraud trends likely to be influenced most by GEN AI technology in 2024. A staggering rise in bogus accounts: (impacted by: deepfakes, synthetic PII)Account opening channels will continue to be impacted heavily by the adoption of GEN AI. As criminals try to establish presence in social media and across business channels (e.g., LinkedIn) in an effort to build trust and credibility to carry out further fraudulent attempts, this threat will expand way beyond the financial services industry. GEN AI technology continues to evolve, and with the imminent emergence of highly convincing real-time audio and video deepfakes, it will give fraudsters even better tools to attempt to bypass document verification systems, biometric and liveness checks. Additionally, they could scale their registration attempts by generating synthetic PII data such as names, addresses, emails, or national identification numbers. Persistent account takeover attempts carried out through a variety of channels: (impacted by: deepfakes, GEN AI generated phishing emails)The advancements in deepfakes present a big challenge to institutions with inferior authentication defenses. Just like with the account opening channel, fraudsters will take advantage of new developments in deepfake technology to try to spoof authentication systems with voice, images, or video deepfakes, depending on the required input form to gain access to an account. Furthermore, criminals could also try to fool customer support teams to help them regain access they claim to have lost. Finally, it's likely that the biggest threat would be impersonation attempts (e.g., criminals pretending to be representatives of financial institutions or law enforcement) carried out against individuals to try to steal access details directly from them. This could also involve the use of sophisticated GEN AI generated emails that look like they are coming from authentic sources. An influx of increasingly sophisticated Authorised Push Payment fraud attempts: (impacted by: deepfakes, GEN AI chatbots, GEN AI generated phishing emails)Committing social engineering scams has never been easier. Recent advancements in GEN AI have given threat actors a handful of new ways to deceive their victims. They can now leverage deepfake voices, images, and videos to be used in crimes such as romance scams, impersonation scams, investment scams, CEO fraud, or pig butchering scams. Unfortunately, deepfake technology can be applied to multiple situations where a form of genuine human interaction might be needed to support the authenticity of the criminals' claims. Fraudsters can also bolster their cons with GEN AI enabled chatbots to engage potential victims and gain their trust. If that isn’t enough, phishing messages have been elevated to new heights with the help of LLM tools that have helped with translations, grammar, and punctuation, making these emails look more elaborate and trustworthy than ever before. A whole new world of GEN AI Synthetic Identity: (impacted by: deepfakes, synthetic PII)This is perhaps the biggest fraud threat that could impact financial institutions for years to come. GEN AI has made the creation of synthetic identities easier and more convincing than ever before. GEN AI tools give fraudsters the ability to generate fake PII data at scale with just a few prompts. Furthermore, criminals can leverage fabricated deepfake images of people that never existed to create synthetic identities from entirely bogus content. Unfortunately, since synthetic identities take time to be discovered and are often wrongly classified as defaults, the effect of GEN AI on this type of fraud will be felt for a long time. How to prevent GEN AI related fraud As GEN AI technology continues to evolve in 2024, its adoption by fraud perpetrators to carry out illegal activities will too. Institutions should be aware of the dangers they possess and equip themselves with the right tools and processes to tackle these risks. Here are a few suggestions on how this can be achieved: Fight GEN AI with GEN AI: One of the biggest advantages of GEN AI is that while it is being trained to create synthetic data, it can also be trained to spot it successfully. One such approach is supported by Generative Adversarial Networks (GANs) that employ two neural networks competing against each other — a generator and a discriminator. The generator creates synthetic data, while the discriminator evaluates the generated data and tries to distinguish between real and fake samples. Over time, both networks fine tune themselves, and the discriminator becomes increasingly successful in recognising synthetic content. Other algorithms used to create deepfakes, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Autoencoders, can also be trained to spot anomalies in audio, images, and video, such as inconsistencies in facial movements or features, inconsistencies in lighting or background, unnatural movements or flickering, and audio discrepancies. Finally, a hybrid approach that combines multiple algorithms often presents more robust results. Advanced analytics to monitor the whole customer journey and beyond: Institutions should deploy a fraud solution that leverages data from a variety of tools that can spot irregular activity across the whole customer journey. That could be a risky activity, such as a spike in suspicious registrations or authentication attempts, unusual consumer behaviour, irregular login locations, suspicious device or browser data, or abnormal transaction activity. A best-in-class solution would give institutions the ability to monitor and analyse trends that go beyond a single transaction or account. Ideally, that means monitoring for fraud signals happening both within a financial institution’s environment and across the industry. This should allow businesses to discover signals pointing out fraudulent activity previously not seen within their systems or data points that would otherwise be considered safe, thus allowing them to develop new fraud prevention models and more comprehensive strategies. Fraud data sharing: Sharing of fraud data across multiple organisations can help identify and spot new fraud trends from occurring within an instruction's premises and stop risky transactions early. Educate consumers: While institutions can deploy multiple tools to monitor GEN AI related fraud, regular consumers don't have the same advantage and are particularly susceptible to impersonation attempts, among other deepfake or GEN AI related cons. While they can't be equipped with the right tools to recognize synthetic content, educating consumers on how to react in certain situations related to giving out valuable personal or financial information is an important step in helping them to remain con free. Learn more with our latest fraud reports from across the globe: UK Fraud Report 2023 US Fraud Report 2023 EMEA + APAC Fraud Report 2023

Authorised Push Payment fraud is growing, and as regulators begin to take action around the world to try to tackle it, we look at what financial institutions need to focus on now. APP fraud and social engineering scams In recent years, there has been a significant surge in reported instances of Authorized Push Payment Fraud (APP). These crimes, also known as financial scams, wire fraud scams, or social engineering scams in different parts of the world, refer to a type of fraud where criminals trick victims into authorising a payment to an account controlled by the fraud perpetrator for what the victim believes to be genuine goods or services in return for their money. Because the transactions made by the victim are usually done using a real-time payment scheme, they are often irrevocable. Once the fraudster receives the funds, they are quickly transferred through a series of mule accounts and withdrawn, often abroad. Because APP fraud often involves social engineering, it employs some of the oldest tricks in the criminal's book. These scams include tactics such as applying pressure on victims to make quick decisions, or enticing them with too-good-to-be-true schemes and tempting opportunities to make a fortune. Unfortunately, these tricks are also some of the most successful ones, and criminals have used them to their advantage more than ever in recent times. On top of that, with the widespread adoption of real-time payments, victims have the ability to transfer funds quickly and easily, making it much easier for criminals to take advantage of the process. APP Fraud and social engineering scams - cases and losses across the globe: View map Impact of AI on APP fraud Recent advancements in generative artificial intelligence (Gen AI) have accelerated the process used by fraudsters in APP fraud. Criminals use apps like Chat GPT and Bard to create more persuasive messages, or bot functionality offered by Large Language Models (LLMs) to engage their victims into romance scams and the more sophisticated pig butchering scams. Other examples include the use of face swapping apps or audio and video deepfakes that help fraudsters impersonate someone known to their victims, or create a fictitious personality that they believe to be a real person. Additionally, deepfake videos of celebrities have also been commonly used to trick victims into making an authorised transaction and lose substantial amounts of money. Unfortunately, while some of these hoaxes were really difficult to pull off a few years ago, the widespread availability of easy-to-use Gen AI technology tools has resulted in an increased number of attacks. A lot of these scams can be traced back to social media, where the initial communication between the victim and criminal takes place. According to UK Finance, 78% of APP fraud started online during the second half of 2022, and this figure was similar for the first half of 2023 at 77%. Fraudsters also use social media to research their victims which makes these attacks highly personalised due to the availability of data about potential targets. Accessible information often includes facts related to family members, things of personal significance like hobbies or spending habits, information about favourite holiday destinations, political views, or random facts like favourite foods and drink. On top of that, criminals use social media to gather photos and videos of potential targets or their family members that can later be leveraged to generate convincing deepfake content that includes audio, video, or images. These things combined contribute to a new, highly personalised approach to scams than has never been seen before. What regulators are saying around the globe APP fraud mitigation is a complex task that requires collaboration by multiple entities. The UK is by far the most advanced jurisdiction in terms of measures taken to tackle these types of fraud to help protect consumers. Some of the most important legislative changes that the UK’s Payment Systems Regulator (PSR) has proposed or introduced so far include: Mandatory reimbursement of APP scams victims: A world first mandatory reimbursement model will be introduced in 2024 to replace the previous voluntary reimbursement code which has been operational since 2019. 50/50 liability split: All payment firms will be incentivised to take action, with both sending and receiving firms splitting the costs of reimbursement 50:50. Publication of APP scams performance data: The inaugural report was released in October, showing for the first time how well banks and other payment firms performed in tackling APP scams and how they treated those who fell victim. Enhanced information sharing: Improved intelligence-sharing between PSPs so they can improve scam prevention in real time is expected to be implemented in early 2024. Because many of the scams start on social media or in fake advertisements, banks in the UK have made calls for the large tech firms (for example, Google, Facebook) and telcos to be included in the scam reimbursement process. As a first step to offer more protection for customers, in December 2022, the UK Parliament introduced a new Online Safety Bill that intends to make social media companies more responsible for their users’ safety by removing illegal content from their platforms. In November 2023, a world-first agreement to tackle online fraud was reached between the UK government and some of the leading tech companies - Amazon, eBay, Facebook, Google, Instagram, LinkedIn, Match Group, Microsoft, Snapchat, TikTok, X (Twitter) and YouTube. The intended outcome is for people across the UK to be protected from online scams, fake adverts and romance fraud thanks to an increased security measures that include better verification procedures and removal of any fraudulent content from these platforms. Outside of the UK, approaches to protect customers from APP fraud and social engineering scams are present in a few other jurisdictions. In the Netherlands, banks reimburse victims of bank impersonation scams when these are reported to the police and the victim has not been ‘grossly negligent.’ In the US, some banks provide voluntary reimbursement in cases of bank impersonation scams. As of June 2023, payment app Zelle, owned by seven US banks, has started refunding victims of impersonation scams, thus addressing earlier calls for action related to reported scams on the platform. In the EU, with the newly proposed Payment Services Directive (PSD3), issuers will also be liable when a fraudster impersonates a bank’s employee to make the user authenticate the payment (subject to filling in a police report and the payer not acting with gross negligence). In October 2023, the Monetary Authority of Singapore (MAS) proposed a new Shared Responsibility Framework that assigns financial institutions and telcos relevant duties to mitigate phishing scams and calls for payouts to be made to affected scam victims where these duties are breached. While this new proposal only includes unauthorised payments, it is unique because it is the first such official proposal that includes telcos in the reimbursement process. Earlier this year, the National Anti-Scam Centre in Australia, announced the start of an investment scam fusion cell to combat investment scams. The fusion cell includes representatives from banks, telcos, and digital platforms in a coordinated effort to identify methods for disrupting investment scams to minimise scam losses. To add to that, in November 2023, Australian banks announced the introduction of confirmation-of-payee system that is expected to help reduce scams by ensuring customers can confirm they are transferring money to the person they intend to, similarly to what has been done in the UK a few years ago. Finally, over the past few months, more jurisdictions such as Australia, Brazil, the EU and Hong Kong, have announced either proposals or the roll out of fraud data sharing schemes between banks and financial institutions. While not all of these schemes are directly tied to social engineering scams, they could be seen as a first step to tackle scams together with other types of fraud. While many jurisdictions beyond the UK are still in the early stages of the legislative process to protect consumers from scams, there is an expectation that regulatory changes that prove to be successful in the UK could be adopted elsewhere. This should help introduce better tracking of the problem, to stimulate collaboration between financial insitutions, and add visibility of financial instituitions efforts to prevent these types of fraud. As more countries introduce new regulations and more financial institutions start monitoring their systems for scams occurrences, the industry should be able to achieve greater success in protecting consumers and mitigating APP fraud and social engineering scams. How financial institutions can prevent APP fraud Changing regulations have initiated the first liability shifts towards financial institutions when it comes to APP fraud, making fraud prevention measures a greater area of concern for many leaders in the industry. Now the responsibility is spreading across both the sending and receiving payment provider, they also need to improve monitoring for incoming payments. What’s more, as these types of fraud are a global phenomenon, financial institutions from multiple jurisdictions might consider taking greater fraud prevention steps early on (before regulators impose any mandatory rules) to keep their customers safe and their reputation high. Here are five ways businesses can keep customers safe, while retaining brand reputation: Advanced analytics – advanced data analytics capabilities to create a 360° of individuals and their behaviour across all connected current accounts. This supports more sophisticated and effective fraud risk analysis that goes beyond a single transaction. Combining it with a view of fraudulent behaviours beyond the payment institution's premises by adding the ability to ingest data from multiple sources and develop models at scale allows businesses to monitor new fraud patterns and evolving threats. Behavioural biometrics – used to provide insights on indicators such as active mobile phone calls, session length, segmented typing, hesitation, and displacement to detect if the sender is receiving instructions over the phone or if they show unusual behaviour during the time of the transaction. Transaction monitoring and anomaly detection – required to monitor sudden spikes in transaction activity that are unusual for the sender of the funds as well as mule account activity on the receiving bank’s end. Fraud data sharing capabilities – sharing of fraud data across multiple organisations can help identify and stop risky transactions early, in addition to mitigation of mule activity and fraudulent new accounts opening. Monitoring of newly opened accounts – used to detect fake accounts or newly opened mule accounts. By leveraging a combination of these capabilities, financial institutions will be better prepared to cope with new regulations and support their customers in APP fraud. Identity & Fraud Report 2023 US Identity & Fraud Report 2023 UK Defeating Fraud Report 2023 EMEA & APAC

What are lenders prioritising when it comes to Gen AI? We take a look at five transformative use cases in lending, and organisational priorities for integrating Gen AI into customer lifecycle processes. Although Generative Artificial Intelligence (Gen AI) only launched publicly in the form of Chat GPT last November, adoption has been widespread and rapid. Even in typically risk-adverse industries like financial services, our research shows that there is widespread recognition that Gen AI could deliver a range of benefits across business functions. We identified five areas of focus for lenders based on our research. In a study conducted by Forrester Consulting on behalf of Experian, we surveyed 660 and interviewed 60 decision makers for technology purchases that support the credit lifecycle at their financial services organisation. The study included businesses across North America, UK and Ireland, and Brazil. The qualitative research showed that lenders are already using a type of Gen AI, Large Language Models (LLMs), in their operations, with a focus on testing across areas such as customer service and internal processes before deploying to credit operations. We look at the potential use cases, and how businesses are using Gen AI now. 1. Personalised customer experience Customers today expect a personalised lending experience that is tailored to their unique needs and preferences. GenAI can leverage customer data to generate personalised loan offers, recommendations, and repayment plans. This helps lenders improve customer satisfaction and loyalty, leading to increased customer retention and revenue growth. This is an area that is front of mind for the companies in our research – nearly half of businesses surveyed are planning to implement or expand technology capabilities to either upsell or retain customers in the next 12 months. Furthermore, 50% of companies believe that offering more tailored underwriting and pricing is a top priority in their credit operations, followed by 44% who also aim to increase personalisation in marketing, products, and services to their customers. According to the research, some organisations have formed alliances with technology providers like OpenAI and Microsoft to investigate and further explore the use of LLMs. These partnerships involve analysing customer data to identify opportunities for cross-selling. 2. Enhancing models with new data sources With new data sources emerging all the time, Gen AI is one of the technologies that will most likely accelerate the opportunity for businesses to incorporate them into models. Lenders could include sources such as social network data into their models by using LLMs. This unstructured data, including customer emotions and behaviours on social networks, would be treated as an additional variable in the models. According to the research social media data and psychometric data is already used across financial services, to varying degrees. It showed that 35% of retail companies use social media data, while 29% of FinTechs use psychometric data. Auto finance companies sit at lower end of the adoption scale, with only 12% using social media data and 15% psychometric data. 3. Operational efficiencies Gen AI can help bring operational efficiencies to customerjourneys across the entire lifecycle, offering lenders theability to automate and streamline various processes,resulting in improved productivity, cost savings, andenhanced customer experiences. One of the top challenges for businesses surveyed isimproving customer journeys during onboarding, and thiswas particularly significant for credit unions / buildingsocieties (53%). 4. Detecting and preventing fraud Gen AI can play a crucial role in fraud detection by analysing patterns and anomalies in vast datasets. By leveraging machine learning techniques, Gen AI models can proactively identify potentially fraudulent activities and mitigate risks. The ability to detect fraud in real-time improves the overall security of lending operations and helps protect lenders and borrowers from financial losses. Detecting and preventing fraud is a constant challenge for lenders. 51% of retailers and 47% of credit unions/ building societies surveyed said that reducing fraud losses is a key challenge for them. 5. Customer service Driven by advances in the machine learning and AI space, the world of customer service has benefited hugely from the adoption of virtual assistants and chatbots in recent years. This looks to continue, with businesses saying that LLMs are being tested for customer service purposes, allowing lenders to identify customer issues and automate actions. What's next for lenders? The research found that lenders are utilising various machine learning techniques like regression, decision trees, neural networks, and random forest, along with LLMs. Businesses are in the early stages of exploring how they can use LLMs in credit risk models, but it will undoubtedly involve a blend of existing and new capabilities. As with any emerging technology, it’s important to look at potential risk. The research indicated that organisations see challenges and concerns when it comes to the use of LLMs in their models. It is crucial to ensure the models are trusted, validated, and properly understood to avoid reliance on outsourced solutions and maintain control and visibility over the models’ functions. The ability to explain decisions in Gen AI to avoid bias can be difficult, and businesses will be watching the regulators to understand how best to proceed. There is no doubt, however, that Gen AI will optimise the credit customer lifecycle, creating vast opportunities for lenders. Download PDF More on Gen AI

In a study conducted by Forrester Consulting on behalf of Experian, we surveyed 660 and interviewed 60 decision makers for technology purchases that support the credit lifecycle at their financial services organisation. The study included businesses across North America, UK and Ireland, and Brazil. More on Gen AI

Fraud prevention is a critical concern for businesses today. To help combat this ever-present threat, the consortium approach has emerged as a powerful tool in the fight against fraud. By pooling resources, expertise, and creating visibility, consortium members can be more effective in detecting and preventing fraudulent activities. con-sor-tium noun: A group of people, countries, companies, etc., who are working together on a particular project. What is a consortium? Within business, consortiums are a global concept and can operate under multiple categories, including finance, marketing, and tech. A well-known, successful example is Star Alliance. They are a group of airlines, whose agreement enables their members to share and benefit from flights, airport lounges, and frequent flyer programs. All Star Alliance members are working towards the same goal, which is to offer their customers a seamless travel experience. Key benefits of the consortium approach Resource sharing: Pooling resources like funding, expertise, and infrastructure can lead to cost savings and efficient resource utilisation. Risk mitigation: Shared risks make it easier for organisations to tackle ambitious projects or ventures with reduced individual exposure. Access to expertise: Members can tap into the collective knowledge and skills of the consortium, enhancing their capabilities. Market influence: Consortiums often have more influence in negotiations, regulations, and standards-setting, benefiting all members. Innovation: Collaboration can foster innovation through cross-pollination of ideas and technologies among members. Economies of scale: Consortiums can negotiate better deals on purchases or services due to their combined purchasing power. Reduced competition: In some cases, members can reduce direct competition among themselves by coordinating efforts. Market entry: Consortiums can facilitate market entry, especially in foreign markets, by leveraging each other's networks and knowledge. Shared infrastructure: Access to shared facilities or infrastructure can save costs and accelerate projects. Brand recognition: Being part of a reputable consortium can enhance an organisation's credibility and market presence. However, consortiums also come with challenges such as coordination issues, conflicts of interest, and shared decision-making. Successful consortiums require effective governance structures and clear agreements among members. Consortiums in fraud detection and prevention The success of a consortium relies on the collective commitment of its members to a shared goal. In the context of fraud prevention, this means maintaining consistent and high-quality insights across all members. To achieve this, consortium members adhere to an agreement that covers elements such as data quality and data frequency. These agreements ensure that all participants contribute their best insights and information. By fostering a culture of cooperation and sharing, consortiums create an environment where valuable insights can be harnessed to combat fraud effectively. However, it's crucial to emphasise that the success of consortiums ultimately depends on the active participation and contribution of all its members. Consortiums can only thrive when every member is dedicated to making their quality insights accessible to the group. Read more about how consortiums can revolutionise fraud detection and prevention by sharing data on fraudsters across different product types and industry sectors with Hunter.

With heightened consumer demand for an improved customer experience online, and the increasing threat of fraud, how can organizations ensure secure and efficient customer onboarding in today's digital landscape? Onboarding the highest number of customers while maintaining compliance and security Digital account opening is in demand. Businesses are competing to create the most effective onboarding experience, while managing the need to draw on multiple sources during account opening. The onboarding stage of the customer lifecycle plays a pivotal role in establishing trust between the customer and the business. Friction during the digital account opening process can lead to customer dropouts, resulting in lower growth for organizations. Moreover, the ever-present threat of fraud necessitates organizations to be vigilant and enhance customer journey with an added layer of verification and protection. Liminal, a leading market intelligence firm specializing in digital identity, cybersecurity, and fintech markets, recently recognized Experian as a market leader for compliance and fraud prevention capabilities and execution in its Liminal Link Index on Account Opening in Financial Services. Download report The report highlights that solution providers in financial services are focused on delivering high levels of assurance while maintaining regulatory compliance and minimizing user friction. Access to real-time verification data, risk analytics and decision-making strategies make it possible for clients to verify identities, detect and prevent fraud, and ensure regulatory compliance. Experian’s identity verification and fraud prevention solutions, including CrossCore® and Precise ID®, received the highest Link 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. 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.”Kathleen Peters, Chief Innovation Officer for Experian’s Decision Analytics business in North America The report offers valuable insights into the market overview, demands, challenges, purchasing criteria, vendor landscape, landscape analysis, and buyer opportunities. Access full report