A recent research report by Experian, a leader in data and technology, has revealed interesting insights from senior fraud leaders on how Generative AI (GenAI) is transforming the fraud landscape.
Conducted by Forrester Consulting, the report reveals an increase in fraud losses, driven by identity theft, and highlights the importance of robust Machine Learning (ML)-based security measures in the fight against fraud. The research surveyed 449 senior fraud leaders and decision makers across eight countries, including South Africa, India, Norway, Denmark, Spain, Italy, the Netherlands and Germany.
The Impact of GenAI on Fraud
The report identifies a significant shift from individual fraudsters to highly organised fraud syndicates, a trend exacerbated by the advent of GenAI. Eighty-two percent (82%) of South African respondents agree that GenAI has permanently altered the fraud landscape, making it more complex and sophisticated. GenAI has also enabled the “industrialisation of fraud”, where fraudsters create and deploy synthetic identities, deepfakes, and other fraud tactics at scale and with ease.
As a result, 47% of businesses in South Africa struggle to identify the use of GenAI in a fraud attack and to quantify its impact on losses. Businesses must take a more proactive approach to fraud prevention through the adoption of advanced, AI-driven solutions and integrations of multiple tools via orchestration platforms – allowing them to more accurately call fraud checks based on risk threats, enhance detection accuracy, and reduce costs.
The Growing Need for Collaboration and Advanced Technologies
With the increasing complexity of fraud threats, collaboration and advanced technologies are more crucial than ever. Close to four out of five fraud decision-makers recognise this, with 83% in SA agreeing that collaboration with external partners is crucial for effective fraud prevention. For example, 67% agree that sharing fraud data through a consortium is an effective way to identify new and emerging fraud trends. 60% of businesses in the research from SA have seen positive return on investment (ROI) from their participation, highlighting the benefits of consortia. This highlights the importance of overcoming data-sharing challenges to enhance fraud detection and prevention efforts.
Machine Learning as the Backbone of Fraud Prevention
Given the increasing fraud threat and the critical role of ML in fraud prevention, the introduction of ML-based models was recognised as a top priority by leaders. Nearly half (43%) of businesses in SA currently struggle with implementation, citing insufficient training data and 50% lacking quality data. Developing effective ML models in-house is challenging compared to using verified, pre-trained models. By using customisable off-the-shelf ML models, businesses can accelerate deployment and value realisation.
Experian is at the forefront of the fight against fraud, using cutting-edge technology and data analytics to stay ahead of emerging threats. We are committed to developing and refining our Machine Learning (ML)-based tools, which are essential in identifying and mitigating fraudulent activities. By encouraging the use of these advanced tools, we empower businesses to navigate the complex landscape of fraud prevention with confidence. Our goal is to ensure that personal and financial information remains secure, providing peace of mind in an increasingly digital world.