Resistant AI, a Czech Republic-based company founded in 2019, employs machine learning techniques to safeguard financial services from fraud, manipulation and attack.
Katherine Gormley, the AML product manager at Resistant AI, sheds light on how the company employs anomaly detection to proactively identify emerging threats and safeguard customers in the digital landscape.
Anomaly Detection: Strengthening Digital Interactions
Resistant AI utilizes anomaly detection, a core framework of machine learning, to identify unknown and emerging threats faced by businesses and their customers. By applying this technology, the company can detect forged documents in the onboarding process and monitor consumer behavior to combat fraud and money laundering effectively. Gormley emphasizes that Resistant AI’s focus lies at the intersection of physical and digital worlds, making digital interactions safer from financial crime attacks.
Addressing Pain Points and Unique Selling Proposition
The primary objective of Resistant AI is to assist its clients in building trust, enhancing reputation, and establishing lasting relationships with their customers by preventing and disrupting financial crime. Gormley emphasizes the need to protect systems and customers from illicit actors, as criminals exploit the digital channels and digital interactions between clients and their customers. Resistant AI’s distinct approach lies in enhancing existing platforms and systems instead of seeking wholesale replacements. By incorporating AI into established processes and systems, the company improves outcomes, drawing from its cybersecurity domain experience.
The Role of AI in Anti-Money Laundering (AML)AI has long been recognized as a valuable mechanism for preventing, detecting, and disrupting financial crime. Gormley highlights AI’s ability to rapidly process vast amounts of information, making it a perfect fit for the anti-money laundering space. Transaction monitoring, for instance, benefits from AI’s analytical capabilities to identify unusual or anomalous activities. Resistant AI emphasizes the value of layering AI on top of existing systems to offer superior protection and outcomes for clients.
Challenges in Implementing AI for AML
Implementing AI for AML involves overcoming various challenges, which can vary depending on the organization, particularly traditional financial services firms versus neobanks. Legacy systems pose a significant challenge for traditional firms, requiring extensive change programs to optimize and enhance them. Resistant AI addresses this challenge by advocating for overlaying AI onto existing systems rather than replacing them entirely.
Additionally, uncertainty around the regulatory viewpoint on AI adoption in AML pose obstacles for organizations. While AI can efficiently support regulatory obligations, there needs to be clear guidance from regulators. Resistant AI anticipates further regulatory encouragement of AI adoption in the future.
Funding and Future Plans
Resistant AI recently extended its Series A round to $27.6 million and will use the funding to expand its product, team, and geographical presence. This funding enables the company to meet the surging demand from financial institutions seeking protection against malicious attacks. Gormley emphasizes the company’s commitment to strengthen defenses against growing threats like authorized push payment fraud.
Key Trends: Rise of ‘Crime-as-a-Service’
In the ever-evolving financial crime space, Resistant AI highlights the trend of criminal organizations offering “crime-as-a-service” or fraud as a service. Criminals now operate as organized groups, exploiting financial services firms with stolen information and synthetic identities. Gormley points out that the availability of new tools, including advanced technologies like ChatGPT, enables criminals to commit fraud more efficiently. It is crucial for firms to stay ahead of the increasing pace of criminal activity.
Resistant AI stands at the forefront of anomaly detection, leveraging its expertise in machine learning and cybersecurity to protect financial services from emerging threats. By enhancing existing systems with AI technologies, Resistant AI enables its clients to achieve better protection, build trust, and strengthen customer relationships. With its ongoing focus on innovation, funding, and addressing evolving trends, Resistant AI is well-positioned to meet the growing demand for enhanced financial security in the digital era.
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