Oscilar’s new solution identifies and prevents fraudulent transactions with increased speed and accuracy by leveraging advanced machine learning algorithms, generative AI techniques, and real-time data analysis and explainability.
The launch comes at critical time, when the ACH Network – the backbone of the modern financial ecosystem – experiences unprecedented growth, with 8.2 billion payments handled in the first quarter of 2024 alone, including a 47% increase in Same-Day ACH volume. This payment method facilitates critical transactions such as payroll, bill payments, internet purchases, person-to-person transfers, and business-to-business settlements.
ACH credit fraud increased by 6% between 2021 and 2023, and more than half of organisations with revenue less than USD 1 billion were unable to recover funds lost from fraud attacks.
As the ACH Network experiences rapid growth and faster payments, the threat of ACH fraud has become more pressing than ever, with organised groups, data breaches, and sophisticated techniques exploiting vulnerabilities in the system.
Fraudsters employ a wide range of tactics which are tackled by Oscilar, including first-party fraud, account takeovers, stolen account details, scams, Business Email Compromise (BEC), vendor and payroll impersonation, money mules, and check kiting, which are increasingly complex and difficult to detect using traditional fraud prevention methods. The FBI reported that BEC scams remain highly prevalent, resulting in USD 2.9 billion in losses in 2023, making it the second-costliest type of cybercrime.
Traditional fraud detection solutions have struggled to keep pace with the ever-evolving threat landscape. They rely on outdated rules engines or static machine learning models and manual processes that are slow, inefficient, and prone to errors. This has exposed financial institutions and businesses to significant financial losses and reputational damage.
Oscilar's holistic approach to ACH fraud detection includes real-time orchestration capabilities, advanced feature engineering for behavioural profiles, hybrid machine learning models, and AI co-pilots for risk teams. These capabilities not only detect new attack vectors fast, but also help risk operations teams scale their investigations and reviews. This approach is well-suited for detecting and staying ahead of the ever-evolving nature of ACH fraud. It enables financial institutions to effectively combat fraudulent activities and protect the entire customer journey before money moves out.
Officials from Oscilar said they founded their company to make the internet safer and protect online transactions. Cracking down on ACH fraud is one of the biggest challenges for their fintech and financial institution customers, and ACH fraud costs companies and consumers billions each year. Their new ACH Fraud Detection product allows customers to prevent fraud in real-time while also helping them navigate the regulatory landscape with ease and confidence.
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