About 76% of respondents in Spain agree that the generative AI has complicated and sophisticated the fraud panorama. This technology allows the “industrialization of fraud”, facilitating the creation and deployment of synthetic identities, Deepfakes and other large -scale fraudulent tactics.
This is experienced in their latest report, made by Forrester Consulting, where they highlight that as a result, 48% of Spanish companies have difficulty identifying the use of IAGEN in fraud attacks, which complicates the quantification of their impact on losses.
To face these challenges, companies must adopt a more proactive approach to fraud prevention, using advanced solutions based on AI and orchestration platforms that integrate multiple tools, thus allowing a more precise detection and a cost reduction.
“We are committed to the development and improvement of our tools based on Machine Learning (ML), which are essential to identify and mitigate fraudulent activities. By promoting the use of these advanced tools, we train companies to browse with confidence for the complex panorama of fraud prevention. Our goal is to ensure that personal and financial information remains safe, providing tranquility in an increasingly digital world, ”says Loreto de Lucas, Chief Product Officer of Experian Spain.
Generative and fraud
The growing complexity of fraud threats has made collaboration and the use of advanced technologies more crucial than ever. 80% of Spanish managers recognize the importance of collaborating with external partners for effective fraud prevention. 63% of respondents agree that sharing fraud data through a consortium is an effective way of identifying emerging trends.
In fact, 82% of the Spanish companies that participated in the report have seen a positive return on investment (ROI) thanks to their participation in these consortiums, which highlights the benefits of overcoming the challenges of data exchange to improve the fraud detection and prevention.
Automatic learning (ML) has become the backbone of fraud prevention. Given the growing threat, managers consider the implementation of ML -based models as one of their main priorities. However, 42% of Spanish companies face difficulties in implementing these models, citing data failure to train them and the lack of quality data in 45% of cases.
The generative AI has significantly altered the fraud panorama, making fraudulent tactics more sophisticated and difficult to detect. To combat these threats, companies must adopt a proactive and collaborative approach, using advanced technologies and sharing data through consortiums.
The implementation of automatic learning models is essential to improve accuracy in fraud detection and reduce associated costs. As threats evolve, it is crucial that companies adapt and strengthen their fraud prevention strategies to protect themselves effectively against increasingly sophisticated attacks.
