The increasing use of AI in biometrics and deepfakes damages sports betting companies' business models and security, raising concerns for businesses and individuals.
Fremont, CA: Artificial intelligence has revolutionized various aspects of our lives, including smart assistants, self-driving cars, and wearable health devices. However, it has also increased AI-driven fraud, where bad actors create fake identities and spread false information. As fraud-prevention jobs become more prevalent, companies must tackle these threats head-on.
How AI Is Being Used For Fraud
Artificial intelligence (AI) is used in fraudulent activities like synthetic identities, phishing campaigns, and arbitrage betting. Fraudsters combine fake and real data to create fictitious identities, forge documents, bypass security, and conduct fraudulent transactions. The increasing use of AI in biometrics and deepfakes damages sports betting companies' business models and security, raising concerns for businesses and individuals.
How to Fight Back Against AI-Driven Fraud
Businesses are countering the rising threat of AI in multiple ways. Awareness training for staff and customers is key to this. As AI-driven fraud becomes more prevalent, staff and customers must be vigilant and aware of scams. Banks can help by providing regular information on these topics, using email and SMS alerts, pop-ups when accessing apps and online accounts, and mid-transaction pop-ups for users transferring funds using their apps.
Modern businesses should conduct frequent staff awareness sessions to combat fraud, including training them on fraud techniques like phishing and the latest methods like voice cloning software. Staff should also be prepared to detect transactions or information-sharing attempts bypassing normal business processes.
Transaction monitoring, a technology-driven solution, aids companies in detecting and preventing fraud by automating screening processes for purchases, money transfers, and other business interactions. This tool, essential for instant payment systems, can flag suspicious individuals and transactions, enhancing security.
AI can prevent fraud in several contexts, such as account takeovers, the creation of fictitious accounts, card fraud, credential stuffing, and the employment of betting bots. Machine learning algorithms offer risk criteria based on transaction and fraud data, allowing fraud-fighting strategies to be tailored to unique needs. These models increase the accuracy of fraud detection over time.
