What is fraud detection? Common methods & emerging threats

As technology advances, so do the tactics of cybercriminals. One of the most notable emerging security threats today is deepfake fraud, which not only highlights the dangers of the technology but also the need for effective global fraud detection.

This rising challenge of deepfake fraud is currently targeting organizations across various industries, threatening the privacy and security of businesses, customers, and employees worldwide.

This blog post seeks to address the common methods criminals use to perpetuate fraud, emerging challenges organizations face in detecting and preventing it, and possible solutions to curb the rising issue of deepfake fraud.

Fraud detection serves to protect individuals and organizations from deceptive activity that threatens their financial stability, reputation, and overall integrity.

It involves the use of specialized software and tools to detect and prevent fraudulent activities by analyzing data, looking for patterns, and confirming anomalies.

The process also involves investigating and verifying suspicious activities to ensure that organizations can detect and prevent fraudulent activities in real-time.

Criminals continue to develop newer and more sophisticated ways to defraud individuals and organizations.

A common method criminals use to perpetrate fraud in organizations today is social engineering, and accounts for nearly 98% of data breaches that occur-which typically involves deceiving individuals into sharing confidential information.

Criminals use this method to acquire information for identity theft, initiate fraudulent transactions, and ultimately gain unauthorized access to secure systems.

Deepfake fraud has become an extension of social engineering, using generative AI to create fake personas and fake audio and video recordings of key individuals, which scammers use to try and extract personal data from unsuspecting victims.

Alongside using spoof numbers, and ultimately pursuing data theft.

Deepfake fraud is a rising challenge for organizations globally, with social engineering and fraud using generative AI increasing by 135% in 2023.

Criminals predominantly use deepfake audio, images, and video to deceive people, thereby posing a significant threat to businesses and individuals.

As challenging as it is to detect deepfake fraud, it’s particularly dangerous when these fake audios, videos, and images of people in positions of authority circulate widely.

The consequences of this can range from merely tarnishing someone’s reputation to sparking an international crisis. It is, therefore, critical to prioritize deepfake fraud detection.

As general fraud and the increasing popularity of using deepfakes becomes increasingly rampant, several solutions have arisen.

One possible solution is utilizing specialized AI models that will differentiate between real and fake audios and videos. Besides, organizations should invest in state-of-the-art tools and software for fraud detection and prevention.

DeepAlana, for instance, is a fraud detection system that protects organizations against various malicious phone call attempts, such as spoof numbers, scam callers, and social engineering tactics alongside malicious deepfakes.

It acts as an intelligent layer on top of every call and segments callers based on specific analytics and threat detection. Once a detection is made, the system provides an automated forensic report to the organization for every security incident.

The rising challenge of deepfake fraud targeting organizations worldwide requires immediate attention, and the urgency cannot be overemphasized.

The use of deepfake technology has increasingly become popular in perpetrating fraud, thereby threatening the security and privacy of businesses, customers, and employees worldwide.

Organizations must invest in the right tools and software, utilize specialized AI models, and seek the help of specialists like DeepAlana, who protect and detect fraudulent activities in real-time with a 99.9% accuracy rate.

While it might not be possible to eliminate fraud entirely, there is hope that with the right approach and technology, organizations can minimize its impacts and increase their chances of detection and prevention.