Feedzai - Experts & Thought Leaders

AI is the most effective method for improving anti-money laundering (AML) processes and efficiencies according to AML professionals, research from Feedzai, a pioneering provider of financial crime and risk management solutions. AML ecosystem Feedzai’s The State of Global Anti Money Laundering Compliance Report 2023 surveyed compliance professionals to discover what the biggest threats and opportunities are in the AML ecosystem. It found that 46% of AML professionals are concerned about increasingly sophisticated money laundering techniques, including generative AI. The threat from generative AI and linked technology is now the top challenge for AML professionals, overtaking regulation, cryptocurrency and blockchain, the top threats cited in 2022. Despite no longer occupying the top spot, crypto still remains front of mind for AML professionals. Over half (53%) of those surveyed said that the money laundering activities within their scope are predominantly linked to cryptocurrency transactions. Cryptocurrencies' anonymous and decentralised nature is being exploited to conceal the origins of illicit funds, exacerbating the challenges in detection and monitoring. Result of AI integration AML experts say AI and machine learning are the most useful plans for handling money laundering As criminals utilise increasingly sophisticated technology, so too do those seeking to protect consumers. A third (33%) of AML professionals say that AI and machine learning are the most effective methods for preventing money laundering. Of those already adopting AI, 60% said that the technology has already been effective in driving efficiencies in their organisation’s AML processes.  Looking ahead, over half (51%) of respondents believe that increased use of AI and machine learning is the future of AML and KYC (Know Your Customer) programmes. With the potential to instantly analyse huge data sets, AI is already helping investigators identify bad actors and diffuse threats. As a result of AI integration, see improved KYC processes, reduced false positives, and also a reduced cost burden on compliance professionals. Author's quote Nick Parfitt, Principal AML SME at Feedzai said, “Fraudsters are capitalising on fast-developing technologies to trick existing AML programmes, in many cases using generative AI to their advantage. Our latest report reiterates the demand from AML professionals for their organisations to adopt AI in combination with human insight as a defensive weapon to improve their compliance process and efficiencies."  “Banks and financial institutions are sitting on a wealth of data that they can use to better protect their customers and business. By taking a RiskOps approach, they can put this data to good use by creating a 360-degree view of customer risk that addresses the entire lifecycle of financial crime and compliance, – helping to stop criminals in their tracks before they can do any damage.”

Feedzai, a pioneering provider of financial crime and risk management solutions, announced significant enhancements to its RiskOps Platform, enabling banks to better protect their customers from a wide variety of financial scams. These new Feedzai ScamPrevent™ capabilities deliver industry-pioneering detection, classification, and interception of the widest variety of payment scams and financial fraud typologies. Financial scams are an epidemic growing in both dollar volume and human impact. The FTC recently reported that between 2021 and 2023, losses from scams increased by 30% in the US. These losses are only the tip of the iceberg as globally only 7% of scam losses are reported, according to data from the Global Anti-Scam Alliance (GASA). As scammers now have access to generative AI using large language models (LLMs) to fashion increasingly sophisticated and realistic scams, these losses can only be expected to increase. Legacy point solutions Most financial institutions employ multiple legacy point solutions that use rules-based approaches to identify different types of fraud, but fail to specifically target scams. These traditional approaches have three critical limitations:  They are siloed by channel, so they are susceptible to fraud typologies that operate across multiple banking products or payment platforms. They identify fraud by either focussing on behavioural activity (such as biometrics, app and device usage patterns, malware incidence, and network activity), or financial activity (transactional data across one or more banking channels and platforms), but they don’t natively look at both together, which significantly limits the ability to rapidly diagnose a scam in progress. They don’t quickly evolve to protect against new types of fraud as scammers continuously change their tactics. Feedzai’s RiskOps platform Feedzai’s RiskOps platform is the only solution in the industry that employs a unified AI model Feedzai’s RiskOps platform is the only solution in the industry that employs a unified AI model to build a 360-degree view of customer risk, monitoring a customer’s behaviour and financial activity across the widest span of banking channels. Feedzai’s new ScamProtect™ capabilities build on this unique RiskOps approach to enhance the platform’s ability to identify and intercept scammers before their crimes impact customers, with: Improved AI-based detection. Significant improvements to Feedzai’s AI engine, based on learnings across multiple geographies and financial institutions, enable improved scam detection with reduced false positives. Custom scam rules. New capability to add bank-specific scam detection rules and thresholds on top of out-of-the-box AI detection delivers a rapid and customised response to new scam attacks; Early intervention. Digital signals, including behavioural biometrics and other non-transactional patterns, may suggest a customer could be a scam victim prior to them actually making a payment. New Feedzai features empower banks to identify these signals and create intervention and education opportunities earlier in the risk lifecycle. Inbound payments. To benefit from a scam, a scammer has to send money to an account they can control. New features enable monitoring of inbound payments as well as outbound to give banks multiple opportunities to stop a scam.  Extended scam reporting. Customisable scam classification, performance metrics, and reporting. Author's quote The human impact of scams is particularly high as scammers tend to target vulnerable groups" “Consumer losses from scams are expected to surge as countries introduce or expand instant payment channels – like the US will do this year with the introduction of FedNow,” said Pedro Cunha Barata, Chief Product Officer of Feedzai. He adds, “The human impact of scams is particularly high as scammers tend to target vulnerable groups – the elderly, the economically disadvantaged, immigrant communities, and youth. As it becomes faster and easier to make payments, there is a growing need for new solutions that enable scams to be detected and intercepted before any money moves. With our new ScamProtect™ features, Feedzai delivers the industry’s most comprehensive approach to scam prevention.”  Difference in Net Promoter Score Recent data from McKinsey shows that when a customer is impacted by a scam, it is a make-or-break moment for their banking relationship. Their research shows that the difference in Net Promoter Score (NPS) of customers that had a “good” experience versus a “bad” experience when impacted by fraud was a massive 132 points.  This data strongly suggests that banks that succeed in protecting their customers from scams will increase customer satisfaction and retention, while those that fail will see increased churn.  Recent independent survey Legislators in other countries are considering similar measures Increasingly, consumers hold banks responsible for personal losses stemming from scams. A recent independent survey conducted by Censuswide on behalf of Feedzai found that in the US, 76% of respondents were very likely or somewhat likely to leave their bank if they were not refunded for losses they suffered in a financial scam.  In the UK, existing rules making banks directly accountable for reimbursement of affected consumers are likely to be tightened later this year. Legislators in other countries are considering similar measures. Webinar about scams “In this environment of faster payments and more sophisticated scams, banks should look at proactive strategies to protect their customers from financial crime,” said Nuno Sebastiao, CEO of Feedzai. “We believe that banks which embrace a comprehensive RiskOps approach will outperform in customer satisfaction and retention, while minimising losses from financial crime.”  On June 14, Feedzai will host a webinar about the impact of scams on both banks and their customers, featuring financial crime thought pioneers from GASA, Forrester, Which? and more.

Pedro Bizarro, Chief Science Officer,  Feedzai said, “The UK is at a critical inflection point in the AI space. The CMA’s timely review of the market comes as anti-fraud and anti-money laundering leaders are being pushed to embrace AI responsibly and effectively." Collaborative approach "A one size fits all approach to AI regulation simply won’t work in the UK, and so while a collaborative approach across regulators is sensible, the challenge will be ensuring those regulators are joined up." "There’s a delicate balance to be struck here to ensure that innovation isn’t stifled, but also that consumers are effectively protected." Need for a proactive approach “The financial services industry is no stranger to AI; in fact, it's at the forefront of its adoption. To ensure consumers using these services are being protected, banks must continue to harness the power of AI to combat financial crime while fostering trust, transparency, and fairness in the process." "While we wait for the CMA’s review to conclude, fraud and AML leaders should review their current AI practices and adopt a proactive approach that improves fraud detection and AML processes.”