Rising AI-Fueled Fraud Poses a Growing Threat to Asia’s Profitable Finance Sector
Asia’s finance industry is booming, attracting cybercriminals who are taking advantage of the lucrative opportunities it offers. A recent report revealed that the finance sector is the most targeted vertical in Asia, with cyberattacks becoming increasingly sophisticated. Singapore, in particular, witnessed a surge in scams, primarily perpetrated through e-commerce and online channels, with a 64.5 percent increase in the first half of 2023.
To make matters worse, fraud is becoming more complex. Scammers are now employing deepfake technology to create convincing videos that manipulate both images and voices. For instance, they recently released a deepfake video advertisement featuring a Singaporean newscaster interviewing Elon Musk, encouraging viewers to invest in a dubious project. Experts from Deloitte have warned that fraudsters will increasingly leverage generative artificial intelligence (AI) to enhance their attacks.
The rapid digital transformation in Asia has opened up a multitude of online services, granting greater convenience to consumers. However, this interconnectedness also offers cybercriminals numerous entry points to exploit. Gaining access to just one service can expose a wealth of personal data. Additionally, the availability of easily accessible generative AI tools makes social engineering attacks, such as phishing, even more convincing.
While the public sector is working swiftly to combat fraud through shared responsibility frameworks and regulations, private sector entities are facing resource-intensive challenges in fighting AI-driven fraud. Investigators now spend more time sifting through vast amounts of data and behavioral indicators to identify fraudulent activities. Moreover, fraud trends are constantly evolving, requiring organizations to continually adapt their defense strategies.
Fortunately, artificial intelligence (AI) and machine learning (ML) can be harnessed for the greater good. These tools enable organizations to detect signs and patterns of fraud in real time and automate behavioral analysis and decision-making, ultimately reducing costs and improving productivity. Implementing these technologies across the organization can significantly enhance predictive fraud defenses.
However, for AI and ML to effectively combat fraud, organizations must ensure they have access to trusted, real-time data to train the models. Training datasets need to be comprehensive and relevant, integrating data that provides valuable behavioral insights, such as banking records and credit scores. Nonetheless, preparing and unifying such vast amounts of data for training purposes requires substantial computing power and a robust infrastructure.
To address these challenges, numerous financial institutions are investing in advanced data management technologies, like hybrid data platforms. These technologies facilitate the integration, governance, and real-time analysis of data securely and in compliance with regulations. UOB, a prominent bank in Singapore, successfully reduced false positives in suspected money laundering transactions by 40 percent through the implementation of machine learning models on their data platform.
Axis Bank, the third-largest private-sector bank in India, has also embraced AI and ML to combat fraud. By utilizing an organization-wide data management platform, Axis Bank can analyze vast amounts of data from various sources for credit and marketing analytics, as well as fraud detection.
To effectively combat fraud, organizations must prioritize comprehensive strategies and policies that empower staff to utilize AI and ML tools effectively. This includes organizing data into a single reliable source, enhancing data governance practices, enabling real-time data analysis, and utilizing data management platforms to streamline operations and facilitate compliance.
As fraud tactics continue to evolve, financial institutions must arm themselves with predictive, real-time data, AI, and ML to stay one step ahead. By leveraging these technologies, organizations can proactively detect and prevent fraudulent activities, safeguarding their customers and the lucrative finance industry in Asia.
