AI and Machine Learning Fraud
The increased use of Artificial Intelligence (AI) and Machine Learning (ML) is one of the most significant trends predicted for 2025 in both perpetrating and combating fraud. AI and ML algorithms can analyze vast amounts of data at unprecedented speeds, making them powerful tools for detecting fraud patterns and anomalies. However, fraudsters are also leveraging these technologies to create more sophisticated schemes. As technology continues to evolve, cyber fraud is expected to grow in complexity and frequency. The increasing reliance on digital platforms for financial transactions, communication and data storage creates new vulnerabilities for cybercriminals to exploit your members. Credential stuffing, a cyber-attack where stolen usernames and passwords are used to gain unauthorized access to accounts, is expected to rise. Despite the increasing shift towards digital transactions, check fraud persists as a significant challenge and is set to evolve alongside technological advancements. In 2025, fraudsters will likely exploit sophisticated printing technologies and AI to produce counterfeit checks that are nearly indistinguishable from genuine ones. These counterfeit checks may replicate the design and security features of legitimate checks, making them more deceptive to both recipients and financial institutions. Learning about common phishing attack indicators (Avoiding Social Engineering and Phishing Attacks | CISA) and being wary of what information you share online can reduce your chances of becoming a victim. Collaboration and information sharing among financial institutions can also aid in detecting and preventing synthetic identity fraud. Moreover, it will be crucial to enhance the education of our members about the dangers of check fraud and the importance of protecting checkbooks and personal information. Promoting the use of electronic payments and providing guidelines on recognizing and reporting suspicious checks will play a key role in diminishing the incidence of check fraud.
