Form3, the cloud-native account-to-account platform, has launched a new authorised push payment fraud (APP fraud) prevention solution, powered by Feedzai, the anti-fraud and financial crime software provider.

The new product from Form3 and Feedzai is built using fully supervised machine learning, leveraging collaborative intelligence to understand the behaviour of both the payment sender and recipient, to determine the risk of the payment being made in real-time.

Form3’s new APP Fraud solution combines its account-to-account payment processing with Feedzai’s fraud and financial crime analytics, to create a model that identifies risk in both the individual sending the money and the person receiving the money. Understanding who is receiving the money is key to preventing fraud, as APP fraud involves impersonation that manipulates the victim into sending the money.

This new solution closes the gaps in intelligence that the fraudsters utilise to be able to use faster payments to target UK consumers and businesses. The solution’s model is then able to detect 95 per cent of fraud at market-standard false positive rates.

Mike Walters, CEO of Form3, commented: “The best way to tackle the rise of APP fraud is the use of collaborative intelligence and cutting-edge technologies that allow the real-time identification of scams within the payment message.

“By bringing together Form3’s payment processing expertise, and Feedzai’s fraud and financial crime solutions, we can tackle APP fraud so that UK banks can make faster payments safer. Feedzai is the solution provider of choice for two of the top four financial institutions in the UK, so we are partnering with a market leader to combat APP fraud.”

A £500million problem

Recognising that APP fraud losses account for nearly £500million per year, Form3 developed this new solution on the back of new regulation from the Payment Systems Regulator. This sees APP fraud victims given refunds by their bank from October 2024, with reimbursement now the responsibility of both the sending and the receiving institutions.

Pedro Barata, CPO at Feedzai, also added: “There is increasing regulation in this space, and rightly so – we’ve got to do everything in our power to protect the end consumer from APP fraud. With reimbursement becoming mandatory from October this year, it’s also in the interests of all banks to collectively ensure they prevent fraud and save huge payouts.

“By combining the expertise of Feedzai and Form3, we can drastically reduce the level of vulnerability in the payment process and give our customers the real-time intelligence that they need to stop fraudsters in their tracks.”

The partnership underscores Form3’s commitment to ‘doing well by doing good’, by employing technology to tackle the pervasive issue of fraud, which has profoundly impacted countless individuals worldwide.

The service will go live in April, with a full rollout in the UK market expected in the summer of 2024 – ahead of the implementation of the new rules in October 2024.

Feedzai, the financial crime and risk management solution, and global payments technology company Mastercard are combining technologies to increase crypto fraud protection for hundreds of millions of consumers.

An estimated 40 per cent of scam transactions exit directly from a bank account to a crypto exchange. According to Feedzai’s recent report, The State of Global Anti-Money Laundering (AML) Compliance Report 2023, the monitoring of cryptocurrency effectively is still one of the biggest challenges for financial institutions.

In an attempt to address these challenges, Feedzai and Mastercard plan to integrate Mastercard’s crypto intelligence solution, ‘Ciphertrace Armada’, into Feedzai’s RiskOps platform.

RiskOps analyses transaction data totalling over $1.7trillion annually and offers a comprehensive suite of AI-based solutions designed to stop fraud and financial crime at the source – alerting banks in nanoseconds when a transaction appears fraudulent.

Ciphertrace Armada also enables banks, crypto exchanges, wallets, crypto ATMS and other Virtual Asset Service Providers (VASPs) to better assess the fraud risk in digital asset transactions. In pairing these technologies together, Feedzai’s customers, who collectively protect over 900 million consumers globally,
will now be able to identify and prevent transactions involving fraudulent crypto exchanges before they occur.

Empowering banks ‘to protect their customers’

Nuno Sebastião, CEO of Feedzai, explained the significance of the partnership: “Mastercard’s commitment to protecting its global customer base from fraud aligns perfectly with Feedzai’s mission.

“Criminals use crypto as part of their scam strategies, with the scam proceeds often ending up being funnelled to an unauthorised or otherwise risky crypto exchange.

“It also continues to remain a challenge for AML professionals as criminals become ever more sophisticated and money laundering techniques advance.  This global partnership will further empower banks to protect their customers against the risks associated with crypto and instil further trust in the ecosystem.”

The partnership comes just months after Mastercard announced its new solution that helps banks identify scams in account-to-account payments. Using AI, Mastercard Consumer Fraud Risk enables banks to intervene in real-time and to stop payment before funds leave a victim’s account.

Ajay Bhalla, president of cyber and intelligence at Mastercard, also added: “This is an exciting step in our journey to secure the digital ecosystem. We’re providing financial institutions with the insights they need to be able to prevent transactions involving fraudulent crypto exchanges. We are delighted that, through this new partnership, we can go further, by helping to stop fraud and payments to scams before they take place, giving customers more choice, security and, most importantly, reinforcing trust.”

The combined intelligence of Feedzai and Mastercard means that financial institutions can stop transactions involving high-risk and potentially fraudulent crypto exchanges in real-time, alerting the customer to the risk before the money leaves their account.

Financial scams are rising, with losses amounting to $8.8 billion in 2022 alone. According to the United States Federal Trade Commission, losses from financial fraud have increased by 30% from 2021 to 2023. This paints a dire portrait of the dark underbelly of digital advancement, with scammers now leveraging generative artificial intelligence (AI) to craft increasingly complex and realistic scams.

Multiple reports suggest scammers can create chatbots that mimic human conversation, ask for personal financial details, create malware, write sophisticated phishing emails and even mimic human voices. The immediacy of instant payments via digital banking also presents an opportunity for fraudsters to deceive users into transferring money instantly, leaving defrauded users with little to no hope of getting their money back.

Risk management platforms like Feedzai are part of the ongoing fight against financial crime. Powered by machine learning and big data, platforms like these boast advanced technology and high-level security to combat sophisticated financial scams.

What is Feedzai, and how does it work?

Feedzai is a risk operations (RiskOps) platform that leverages machine learning technology and AI to provide retailers, banks and payment providers with fraud prevention solutions. The platform has a global reach and aims to protect people from the risks associated with e-commerce and banking.

Initially founded in Portugal in 2011, Feedzai is now based in California and offers services in 190 countries. Considered a market leader in its field, the company was originally developed by its founders, Nuno Sebastião, Paulo Marques and Pedro Bizarro, to offer operational intelligence and fraud detection solutions.

Today, Feedzai has evolved into a suite of AI-based solutions specifically targeted at detecting fraud and preventing financial crime. Feedzai’s main clients are established banks and financial institutions like Citibank, Standard Chartered and Lloyds Banking Group.

Feedzai, a RiskOps platform that uses machine learning

Feedzai is based on the concept of RiskOps, a practice that operationalizes risk through fair and customer-centric approaches. RiskOps also empowers financial institutions to detect suspicious behaviors, identify scammers and combat fraud.

RiskOps helps financial institutions manage identity, data and foster collaboration across various systems more efficiently — allowing 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. Standardizing the risk management and fraud prevention approach makes it easier to assess abstract and difficult-to-define concepts like risk. As such, these institutions can confidently measure and analyze risk and make smarter decisions based on these findings.

Feedzai’s platform uses machine learning to process events and transactions quickly while providing easily understandable results through an added 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 identifying fraudulent activities and potential victims easier.

Feedzai minimizes the risk of fraud and money laundering for financial institutions by collecting data from various sources, such as cross-channel, cross-product and third-party data.

This helps to distinguish between authentic and fraudulent transactions, and it provides a comprehensive view of how each individual interacts with the bank. These profiles also make it easier to identify customers more likely to fall victim to scams — even before a scam targets them.

The platform detects fraud quickly and in real time for different payment types, such as cards, instant transfers, digital wallets, withdrawals and deposits. The solution also offers production-ready application programming interfaces (APIs) for various payments to give real-time transaction recommendations, such as whether to approve or decline them.

What is Feedzai used for?

There are several threats and weaknesses that Feedzai helps address:

Addressing the shortcomings of legacy solutions

Financial institutions often use several outdated point solutions that use rules-based approaches to detect fraud but do not specifically focus on scams. Traditional approaches have three main limitations. First, they are restricted to siloed channels, making them vulnerable to fraud schemes that spread across various banking products or payment platforms.

Second, legacy solutions detect fraud by analyzing either behavioral activity (like app and device usage patterns, malware incidence, biometrics and network activity) or financial activity (transactional data across banking platforms). However, their analysis does not consider both types of activity together, reducing the ability to quickly identify an ongoing scam.

Lastly, these fraud protection measures do not adapt quickly enough to counter new tactics used by scammers. Machine learning fills this gap by assimilating new data and providing real-time insights into customer behavior. Feedzai’s platform is designed to quickly detect financial fraud, money laundering and other illicit activities with AI-driven approaches tailored to different payment mechanisms’ nuances.

Combatting the creation of fake accounts to compound rewards

The rise of digital transactions, particularly for small but frequent purchases, has increased rewards for merchants and consumers. However, this growth also presents an opportunity for fraudsters to take advantage of the rewards system.

Fraudsters are taking advantage of the shift toward cashless transactions and increased gamification by creating fake accounts and moving the funds in circles to collect rewards.

Feedzai specializes in analyzing network transactions made by account holders to identify hidden fraudulent payment networks. This means they can detect fraudulent patterns that may not be immediately obvious.

Detecting SIM swaps

SIM swapping is a type of fraud where a perpetrator poses as the owner of a phone number and convinces a call center or branch employee to swap out the associated SIM card. This is done by providing the victim’s personal data to the carrier.

Fraudsters acquire data through hacks and data breaches, or they exploit information that users have publicly shared on social media. They use this information to deceive carriers into permitting them to replace the SIM card linked to a phone number with a SIM card they possess. By doing this, all incoming calls and text messages are re-directed to the fraudster.

Feedzai helps combat this by analyzing transactional data, which can be used to detect a SIM swap. For instance, when multiple transactions are attempted from different devices in quick succession, Feedzai’s algorithms will flag it as suspicious behavior and alert the financial institution of a potential scam.

What are the key features of Feedzai?

Feedzai has added new ScamProtect features to its RiskOps approach, which aims to help improve the platform’s ability to detect and prevent scams before they harm customers. Among the platform’s key features for fraud prevention are:

Comprehensive RiskOps architecture

Feedzai operates in real time and offers a singular centralized location for data ingestion and interpretation. Its comprehensive architecture provides institutions with a centralized hub to detect emerging fraud threats, identify new business requirements, and analytics on user experience and operational performance. By using Feedzai, banks can anticipate where their focus should be ahead of trends.

Early intervention and education

Feedzai’s early detection capabilities enable banks to identify digital signals such as behavior biometrics and other non-transactional patterns that may indicate a potential scam victim. This can help the banks intervene and educate customers earlier in the risk lifecycle before they make a payment.

To navigate the complexity of scam fraud, alerts can record detailed explanations and specific indicators. This information can then guide agents to have more effective conversations with customers.

Human-centered AI

Technology sometimes leads to added roadblocks for customers as they are viewed as data points. This can result in unfair classification into groups and unnecessary difficulties for bank customers (canceled transactions, incessant calls to verify purchases they make, etc.).

Feedzai uses multidimensional data that prioritizes customers through AI to address this issue. By creating hyper-accurate risk profiles based on individual behaviors, banks can identify changes and prevent financial crime with greater ease — while keeping customers satisfied.

Inbound payment monitoring

To successfully scam someone, a scammer needs to send the money to an account they control. However, with Feedzai, banks can now monitor both incoming and outgoing payments, giving them more chances to prevent a scam from taking place.

Triage behavior alerts

The platform’s constant surveillance of each customer builds intelligence to identify fraudulent behavior quickly. Feedzai Case Manager then allows key persons to instantly take action on alerts, automate processes and organize team workloads.

The platform can direct specific alerts to agent groups based on their training through role and queue management. Additionally, the platform includes dashboards and reporting that categorize fraud types, allowing for easier tracking of detection and alert management.

Customization

Feedzai can customize and categorize rules to incorporate particular clauses related to scams, which can be modified in response to changes in fraudulent schemes. Additionally, the platform can adopt a regional approach by using parameters such as bank codes, states or product types, allowing institutions to develop tailored strategies when necessary.

The future of AI-powered risk operations

Risk operations enabled by AI are expected to experience transformational growth in the future. Risk assessment, detection and mitigation across sectors will be revolutionized by cutting-edge machine learning algorithms and predictive analytics.

Rapid analysis of large data sets by AI will reveal complex patterns and anomalies, enabling proactive risk management. Response agility will be improved, reducing vulnerabilities, using real-time monitoring and adaptive algorithms. Sentiment analysis and natural language processing will improve knowledge of risk, including social and reputational factors.

Furthermore, collaborative AI-human workflows will optimize decision-making, and AI’s self-learning skills will enable 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 fostering safer, more secure environments.