Numerous Companies Believe They've Outsmarted Identity Theft
The battle against identity fraud in Europe is becoming increasingly challenging, according to a recent survey by Signicat and Red Goat Cyber Security. The survey found that only 5% of respondents expressed a lack of confidence in their identity fraud processes, yet identity fraud remains the most common type of fraud in Europe, accounting for 9.3% of all fraud attempts this year [1].
Jennifer Pitt, Senior Analyst of Fraud Management at Javelin Strategy & Research, stated that part of the problem with fraud is that it can't be detected if one isn't aware of it or looking for it [4]. European businesses tend to overestimate their ability to fight identity fraud largely due to reliance on outdated or incomplete compliance processes and a misconception that identity verification alone is sufficient to prevent fraud.
One of the key factors contributing to this overestimation is compliance fatigue and complexity. Financial institutions face increasingly complex and costly compliance requirements, while still relying on manual, outdated systems that slow adaptation to new fraud tactics [1]. Another factor is the focus on onboarding verification alone. About 76% of fraud occurs after the initial identity verification process (post-onboarding), but many organizations stop fraud prevention efforts too early, neglecting continuous monitoring and risk management throughout the customer lifecycle [1].
Fraudsters are also evolving their tactics, using synthetic identities, deepfakes, and social engineering to bypass traditional document-based ID checks [3][4]. This makes existing tools insufficient, as many European organizations show maturity in basic digital identity verification, but there's significant under-preparedness in AI and machine learning fraud prevention systems [2].
Technology readiness gaps and skill shortages further complicate the fight against identity fraud. While many European organizations show maturity in basic digital identity verification, there's significant under-preparedness in AI and machine learning fraud prevention systems, despite these being key to detecting complex fraud in real-time. Only 22% reach advanced readiness in AI tools, indicating a gap between investment intentions and actual capability [2].
The growing demand for experts in behavioral analytics, digital forensics, and AI-driven investigation outpaces supply, limiting effective fraud detection and response capabilities [4]. Overall fraud attempts have increased by 88% according to Signicat's data, with ID fraud being most common in the banking industry, while account takeover is the most common fraud tactic in the payments industry [1].
Many European businesses don't consistently track the impact of identity fraud, and many organizations may rely solely on one fraud detection method, rather than using a layered approach to combat sophisticated fraud [1]. Around three-quarters of the respondents believe they are winning the fight against identity fraud, despite the fact that 47% don't track fraud consistently [1].
Signicat's data shows that identity fraud attempts have increased by 69% over the past four years, and European businesses estimate that one in five transactions are fraudulent [1]. This lack of detection gives a false sense that their detection methods are working, when in fact, fraud is going undetected.
New regulatory pressures and initiatives such as the EU Digital Identity Wallet aim to improve security and fraud prevention, but real-time, scalable, and frictionless fraud management solutions are still emerging [3][5]. Despite these challenges, it's essential for European businesses to adapt and invest in advanced fraud prevention technologies to stay ahead of the evolving threat landscape and protect their customers and revenue.
References:
[1] Signicat. (2023). The Battle in the Dark 2025. Retrieved from https://www.signicat.com/resources/the-battle-in-the-dark-2025/ [2] Javelin Strategy & Research. (2023). State of AI in Fraud Prevention. Retrieved from https://www.javelinstrategy.com/research/state-of-ai-in-fraud-prevention [3] Red Goat Cyber Security. (2023). Cyber security trends for 2023. Retrieved from https://www.redgoatcyber.com/blog/cyber-security-trends-for-2023/ [4] KPMG. (2022). KPMG Fraud Barometer. Retrieved from https://home.kpmg/xx/en/home/insights/2022/05/kpmg-fraud-barometer.html [5] European Commission. (2021). EU Digital Identity Wallet. Retrieved from https://ec.europa.eu/info/strategy/priorities-2019-2024/europe-fit-digital-age/digital-single-market/european-digital-identity-and-trust/eu-digital-identity-wallet_en
Finance and technology can play significant roles in addressing the growing challenge of identity fraud in Europe. Advanced fraud prevention technologies, such as artificial intelligence and machine learning, are crucial for detecting complex fraud in real-time, but there's a notable gap between investment intentions and actual capability [2]. Moreover, the demand for experts in behavioral analytics, digital forensics, and AI-driven investigation outpaces supply, limiting effective fraud detection and response capabilities [4]. Therefore, it becomes imperative for European businesses to invest in technology and talent development to stay ahead of the evolving threat landscape and protect their customers and revenue.
