The rise of financial scams is becoming increasingly alarming, with losses reaching a staggering $8.8 billion in 2022 alone. According to the United States Federal Trade Commission, there has been a 30% increase in losses from financial fraud between 2021 and 2023. This paints a troubling picture of the dark side of technological advancement, as scammers now employ generative artificial intelligence (AI) to create sophisticated and realistic scams.
Numerous reports indicate that scammers are capable of developing chatbots that mimic human conversation, request personal financial information, create malware, craft sophisticated phishing emails, and even replicate human voices. The convenience of instant payments through digital banking also provides fraudsters with an opportunity to deceive users into transferring money instantly, leaving victims with little hope of recovering their funds.
In the fight against financial crime, risk management platforms like Feedzai play a crucial role. Powered by machine learning and big data, platforms like Feedzai offer advanced technology and high-level security to combat sophisticated financial scams.
So, what exactly is Feedzai and how does it work? Feedzai is a risk operations (RiskOps) platform that utilizes machine learning technology and AI to provide fraud prevention solutions for retailers, banks, and payment providers. With a global reach, Feedzai aims to protect individuals from the risks associated with e-commerce and banking.
Originally founded in Portugal in 2011, Feedzai is now headquartered in California and offers its services in 190 countries. As a market leader in its field, the company was initially developed by its founders, Nuno Sebastião, Paulo Marques, and Pedro Bizarro, to provide operational intelligence and fraud detection solutions.
Today, Feedzai has evolved into a suite of AI-based solutions specifically designed to detect fraud and prevent financial crime. Its main clients consist of established banks and financial institutions such as Citibank, Standard Chartered, and Lloyds Banking Group.
Feedzai is a RiskOps platform that utilizes machine learning to combat financial fraud. It operates on the concept of RiskOps, which operationalizes risk through fair and customer-centric approaches. By empowering financial institutions to detect suspicious behaviors, identify scammers, and combat fraud, RiskOps helps these institutions manage identity, data, and foster collaboration across various systems more efficiently. This, in turn, enables institutions to provide their customers with superior and reliable services.
Technically, what RiskOps platforms like Feedzai do is provide financial institutions with a framework for more effective financial risk management. By standardizing the risk management and fraud prevention approach, these platforms make it easier to assess abstract and difficult-to-define concepts like risk. As a result, institutions can confidently measure and analyze risk and make smarter decisions based on these findings.
Feedzai’s platform utilizes machine learning to process events and transactions rapidly while providing easily understandable results through a human-readable semantic layer. Its learning model processes and transforms multiple data streams and insights from various sources to create highly detailed customer profiles, making it easier to identify fraudulent activities and potential victims.
To minimize the risk of fraud and money laundering for financial institutions, Feedzai collects data from various sources, including cross-channel, cross-product, and third-party data. This helps distinguish between authentic and fraudulent transactions while providing a comprehensive view of each individual’s interaction with the bank. These profiles also make it easier to identify customers who are more likely to fall victim to scams, even before they become targets.
The platform is capable of quickly detecting fraud in real-time for different payment types, such as cards, instant transfers, digital wallets, withdrawals, and deposits. Additionally, Feedzai offers production-ready application programming interfaces (APIs) for various payments, providing real-time transaction recommendations, such as whether to approve or decline them.
Feedzai serves several purposes in addressing various threats and weaknesses. Firstly, it addresses the shortcomings of legacy solutions commonly used by financial institutions. These outdated point solutions rely on rules-based approaches to detect fraud but do not specifically focus on scams. They are limited to individual channels, making them vulnerable to fraud schemes that span across multiple banking products or payment platforms. Additionally, they fail to consider both behavioral and financial activity together, hindering the quick identification of ongoing scams. Machine learning fills this gap by assimilating new data and providing real-time insights into customer behavior.
Feedzai also specializes in analyzing network transactions to detect hidden fraudulent payment networks. This is particularly crucial in combating the creation of fake accounts that exploit the rewards system of digital transactions. Fraudsters take advantage of cashless transactions and increased gamification by creating fake accounts and moving funds in circles to collect rewards. Feedzai’s analysis of network transactions can identify fraudulent patterns that may not be immediately obvious.
Another threat that Feedzai helps combat is SIM swapping. SIM swapping involves a fraudster posing as the owner of a phone number and convincing a call center or branch employee to swap out the associated SIM card. By analyzing transactional data, Feedzai can detect SIM swaps when multiple transactions are attempted from different devices in quick succession.
Feedzai has recently introduced new ScamProtect features to enhance its ability to detect and prevent scams before they harm customers. Some key features of the platform include a comprehensive RiskOps architecture that operates in real time, early intervention and education capabilities, a human-centered AI approach that prioritizes customers, inbound payment monitoring, and triage behavior alerts. The platform also offers customization options, allowing institutions to incorporate specific clauses related to scams and adapt to changes in fraudulent schemes.
Looking ahead, AI-powered risk operations are expected to undergo significant growth. Cutting-edge machine learning algorithms and predictive analytics will revolutionize risk assessment, detection, and mitigation across sectors. Rapid analysis of large datasets by AI will uncover complex patterns and anomalies, enabling proactive risk management. Real-time monitoring and adaptive algorithms will improve response agility and reduce vulnerabilities. Additionally, sentiment analysis and natural language processing will enhance understanding of risk, including social and reputational factors. Collaborative AI-human workflows will optimize decision-making, and AI’s self-learning capabilities will allow it to continuously adapt to evolving risks. Ultimately, AI-powered risk operations will usher in an era of precision, efficiency, and resilience, mitigating threats and creating safer and more secure environments.