How AI is Redefining Fraud Prevention in 2025
The year 2024 has shown us that artificial intelligence is here to change the world of fraud—both for fraud fighters and cybercriminals.
As we look ahead, what challenges and opportunities will 2025 bring?
Deepfakes of Elon Musk encouraging people to invest in fraudulent schemes. An Arup employee duped by a deepfaked meeting into transferring more than $25 million. The world’s largest advertising group targeted by a voice cloning scheme. And more recently, a Brad Pitt deepfake that convinced a victim to hand over $850,000 in an elaborate scam. These are just a few headlines that have made waves in past months. It’s no surprise that some are calling 2024 the “Year of the Deepfake.”
Artificial intelligence (AI) is, however, not just about deepfakes. AI aids fraudsters in many areas—from generating convincing phishing messages and researching potential targets to crafting malware. Equally, AI plays a crucial role in detecting increasingly sophisticated scams. One thing is certain: in the age of AI-powered fraud, AI-enhanced fraud prevention is not an option but a necessity.
The increasing prevalence of AI-powered fraud
As with so many industries, artificial intelligence is becoming a powerful force in the fraud landscape. Deloitte predicts that, in the United States alone, GenAI driven fraud losses could exceed $40 billion by 2027.
In 2024, it was specifically the dreaded deepfake that added challenges for fraud fighters, organizations, and consumers: According to Deloitte data, more than 1 in 4 executives (25.9%) reported that their organization had experienced one or more deepfake incidents targeting financial and accounting data.
A 2024 Medius survey also revealed that over half of finance professionals in the US and UK had been targeted by deepfake-powered financial scams, with 43% reporting they had fallen victim to such attacks. The financial sector is particularly vulnerable, with deepfake incidents surging by 700% in 2023 compared to the previous year.
Fraudsters also increasingly turn their attention to the lucrative cryptocurrency sector, which experienced a staggering 654% rise in deepfake-related incidents between 2023 and 2024.
What to expect: Three AI fraud trends for 2025
The integration of artificial intelligence into fraud schemes is steadily becoming a global standard. So, what can we expect from AI banking fraud in 2025?
AI-powered impersonation
Scammers will continue to exploit AI for popular impersonation tactics—not only through convincing AI-generated phishing messages, emails, and websites but also with advanced deepfakes and voice cloning. Detecting these scams will become increasingly difficult for consumers as the sophistication of these methods evolves.
Synthetic identities
Artificial intelligence will increasingly fuel synthetic fraud—schemes where fraudsters create synthetic identities by blending real and fabricated, AI-generated information to form new, fictitious personas. These identities are then used to open accounts, take out loans, and commit other fraudulent activities. Deloitte estimates that synthetic identity fraud could result in at least $23 billion in losses by 2030.
Advanced financial malware
AI will play an increasing role in enabling fraudsters to develop highly advanced financial malware. Unlike traditional malware, which relies on fixed, pre-written code, AI-powered malware can dynamically adapt, learn from its environment, identify weaknesses in fraud defenses, and refine its attacks in real time. Experts warn that generative AI can also be used to create polymorphic malware—malicious software capable of constantly altering its code to bypass detection by antivirus programs and cybersecurity tools that rely on recognizing known malware signatures.
Explore more AI fraud insights
AI vs. fraud: Leveraging AI’s potential in banking
To safeguard customers from the fraud enabled by AI, financial organizations have no choice but to fight fire with fire. Only AI itself has the capability to detect and counter even the most sophisticated scams, using advanced tools to stay one step ahead of fraudsters.
Behavioral profiling
AI can create detailed profiles based on how users interact with digital platforms—a process known as behavioral profiling. This includes factors like typing speed, mouse movements, session patterns, device usage, and more. Behavioral profiling is highly effective against AI-driven fraud because it focuses on the dynamic, unique patterns of individual interactions, rather than static identifiers like passwords or personal data.
By analyzing these patterns, behavioral profiling can detect inconsistencies that reveal deepfakes, uncover unnatural behaviors indicating synthetic identities, identify unauthorized account access, and flag anomalies in high-risk transactions.
Anomaly detection
AI is also exceptionally suited to detecting deviations from the norm—not just in behavioral patterns but also in transactions, network traffic, IP addresses, and other critical data points. Its ability to analyze massive datasets in real time makes AI ideal for identifying anomalies and uncovering fraud in large-scale operations, such as those in financial networks or e-commerce platforms.
Predictive tools
Last but not least, AI stands out for its predictive capabilities, using advanced analytics, machine learning, and historical data to anticipate and prevent fraudulent activities. Unlike reactive measures, these tools enable organizations to stay ahead by identifying vulnerabilities and addressing threats before they materialize.
For instance, AI-powered systems can analyze historical fraud patterns, detect unusual behaviors, and adapt dynamically to new data. This approach uncovers emerging fraud schemes, predicts potential risks, and enables organizations to take preventive action effectively.
What lies ahead for AI and fraud?
In 2025, AI-powered fraud is expected to become increasingly widespread, impacting consumers, organizations across industries, and financial institutions alike. This makes it more critical than ever to not only educate ourselves about these evolving threats but also to implement robust measures that mitigate their risk.
Regulators are likely to play a growing role in addressing AI-powered fraud, placing greater emphasis on both the protection of vulnerable stakeholders and the ethical use of AI systems. Evolving regulatory frameworks are beginning to recognize—and in some cases encourage—the adoption of advanced technologies like AI to effectively combat financial crimes.
After all, artificial intelligence is not just a challenge; it is also a transformative opportunity to make the fight against fraud more effective, accessible, and impactful.