Resistant AI Secures $25 Million Series B to Fortify Financial Institutions Against Evolving Fraud Threats
Resistant AI, a frontrunner in providing native artificial intelligence models for financial crime and fraud prevention, has successfully secured $25 million in its Series B funding round. The investment, led by DTCP, saw robust participation from existing investors such as Experian, GV (formerly Google Ventures), and Notion Capital, who are reinforcing their commitment to the company's growth trajectory. This significant capital injection is earmarked to propel Resistant AI's expansion into new territories, enhance its document fraud detection and transaction monitoring services, and fortify its threat intelligence capabilities, all while aiming to solidify its position as a profitable European AI leader.
The Evolving Landscape of Financial Crime and AI
The financial technology and regulatory technology (RegTech) sectors are currently navigating a period of profound transformation, largely driven by the emergence of agentic AI solutions. These advanced systems are designed to replace traditional, static workflows with more dynamic, intelligent, and cost-effective adaptive processes. However, the widespread adoption of large language model (LLM)-based agents has brought to light critical limitations. These models often struggle with the rigorous quantitative risk analysis essential for combating sophisticated financial crime. Furthermore, they are prone to significant "hallucination rates," estimated between 10% and 30%, and present considerable security challenges due to their susceptibility to adversarial manipulation. This complex environment creates a pressing need for robust solutions that can both leverage AI advancements and mitigate their inherent risks.
Resistant AI's Differentiated Approach
Resistant AI is strategically positioned to address these challenges by developing solutions that protect and empower both AI agents and the human fraud, risk, and compliance teams that manage them. The company's core technology relies on proprietary machine learning models that are adept at detecting fraud across a spectrum of data points, including documents, transactions, and user behaviors. A key differentiator is its ability to integrate and leverage signals from a client's entire existing risk technology stack, creating a more comprehensive and context-aware fraud detection system. This unique approach is engineered to deliver unparalleled improvements in detection recall, precision, and contextual decision-making. It enables financial institutions to more effectively identify and prevent a wide array of sophisticated financial crimes, including Real-Time Payment (APP) fraud, synthetic corporate identity fraud, money muling, generative AI-driven document fraud, and intricate money laundering schemes.
Addressing the Surge in AI-Powered Fraud
The financial crime landscape is undergoing an unprecedented AI-driven transformation. Reports indicate that a substantial 35% of businesses have already experienced fraud directly linked to generative AI technologies. Resistant AI's own Threat Intelligence research highlights the rapid maturation of the "Fraud-as-a-Service" economy. This burgeoning market features easily accessible online platforms offering over 160,000 pre-verified accounts sourced from more than 3,000 financial institutions, which are then used to perpetrate Authorized Push Payment (APP) scams. These scams alone have already inflicted an estimated trillion dollars in economic losses globally. With regulatory bodies worldwide, such as the UK Payment Systems Regulator, implementing mandatory APP fraud reimbursement rules, the urgency for advanced, AI-powered detection capabilities has never been more critical.
Demonstrated Growth and Future Outlook
Since its Series A funding round, Resistant AI has experienced remarkable growth. The company reports a tenfold increase in its Annual Recurring Revenue (ARR) and a fourfold expansion of its customer base. Its document fraud detection service has established itself as an uncontested leader, having successfully verified over 150 million documents. Concurrently, the volume of transactions analyzed for fraud and Anti-Money Laundering (AML) purposes has surged by a factor of 100, reflecting the escalating demand for sophisticated fraud prevention solutions across the financial services industry.
Leadership Vision and Investor Confidence
Martin Rehak, CEO and Founder of Resistant AI, commented on the evolving threat landscape: "The financial crime landscape has fundamentally changed with the deployment of LLMs and AI agents in risk prevention settings, and the weaponization of generative AI by fraudsters. Our fraud and fincrime models offer any institution the tools to empower both their human and agentic co-pilots to combat these AI-powered threats at scale. This funding, combined with our near-term path to profitability, allows us to accelerate our mission of protecting the global financial system from increasingly sophisticated criminal networks."
Michael Rager, Partner at DTCP Growth, expressed strong confidence in the company's direction: "Resistant AI represents the future of financial crime prevention, with their in-house built multi-model approach to fraud detection marking a paradigm shift in how financial institutions can protect themselves and their customers. We look forward to partnering with Martin and the Resistant AI team to support the business in its next stage of growth."
Expanding Reach and Capabilities
Resistant AI continues to serve a growing portfolio of global financial institutions, fintech companies, and enterprises. Its established customer base includes prominent names such as Dun & Bradstreet, Payoneer, Close Brothers, PennyMac, AXA, Anna Money, Finom, and Bank of Valletta. With over 100 employees spread across offices in Prague, London, and New York, Resistant AI is well-positioned to leverage this new funding to scale its operations, deepen its technological capabilities, and expand its market presence in the ongoing fight against financial crime.
Resistant AI's offerings, including its document fraud detection and transaction monitoring models, are designed to enhance the resilience of fintech AI and automation systems against manipulation and attacks, without necessitating the replacement of existing technology infrastructures. The company's solutions, such as Resistant Documents, provide rapid fraud and authenticity checks on any document, while Resistant Transactions enhances traditional rule-based systems with over 80 models specifically targeting advanced financial crime typologies. By analyzing a broad range of data, from submitted documents to ongoing customer behaviors, Resistant AI effectively uncovers and prevents various forms of fraud, including document forgery, large-scale serial fraud, synthetic identities, account takeovers, money muling, money laundering, APP fraud, and emerging financial threats.
Companies leveraging Resistant AI services have reported significant improvements, including a threefold increase in document fraud prevention, a fivefold reduction in review times, achievement of 90% automation rates, and a fivefold boost in the productivity of second-line analysts.
AI Summary
Resistant AI, a prominent provider of native artificial intelligence models for financial crime and fraud prevention, has announced a significant $25 million Series B funding round. The investment was spearheaded by DTCP, with substantial contributions from existing investors including Experian, GV (formerly Google Ventures), and Notion Capital, underscoring their continued confidence in the company's vision and technology. This funding infusion comes at a critical juncture for the anti-fraud and regtech market, which is currently undergoing a seismic shift with the advent of agentic AI solutions. While these new AI agents promise more adaptive and cost-effective workflows, they also present inherent challenges, such as a lack of quantitative risk analysis capabilities, significant hallucination rates (10-30%), and vulnerabilities to adversarial manipulation. Resistant AI positions its technology as a crucial protective layer for these AI agents and the human teams tasked with combating financial crime. The company's proprietary machine learning models are designed to detect sophisticated fraud across documents, transactions, and user behaviors, leveraging signals from a client's existing risk technology stack. This multi-faceted approach aims to deliver substantial improvements in detection accuracy, precision, and contextual decision-making. The funds will be strategically deployed to expand Resistant AI's document fraud detection and transaction monitoring offerings into new geographical territories and forge new partnerships. A key focus will also be on bolstering the company's threat intelligence capabilities, further solidifying its role as a profitable EU AI champion. The company has demonstrated impressive growth since its Series A, with a tenfold increase in Annual Recurring Revenue (ARR) and a quadrupled customer base. It has successfully verified over 150 million documents and seen a hundredfold increase in transaction analysis for fraud and anti-money laundering (AML) purposes. This growth trajectory highlights the increasing demand for advanced fraud detection solutions in the financial services sector. Martin Rehak, CEO and Founder of Resistant AI, emphasized the transformed financial crime landscape, driven by LLMs and generative AI used by fraudsters. He stated that Resistant AI's models empower both human analysts and AI co-pilots to combat these evolving threats at scale, with the new funding accelerating their mission to safeguard the global financial system. Michael Rager, Partner at DTCP Growth, expressed confidence in Resistant AI's multi-model approach as a paradigm shift in fraud prevention, anticipating a strong partnership to support the company's expansion. Resistant AI currently serves a diverse clientele, including major financial institutions and fintechs, and employs over 100 professionals across its Prague, London, and New York offices.