Company specializing in identity verification, location intelligence, and fraud prevention, GBG released a new report titled “Building Trust in Digital Channels: A Study of Banking and Finance in Asia.” Produced in partnership with Chartis Research, the study explores the hurdles and a progress in fraud detection and prevention in light of the region’s unprecedented digital adoption levels.
One of the major findings indicates that 8 in 10 Asian financial institutions and banks are encountering challenges with digital fraud detection. However, they are actively contributing in the technology and improving user experience to reduce these risks and maintain customer confidence.
The company has also highlighted a warning tendency of the growing complexity and frequency of fraud occurrences. Nearly 90% of participants identified evolving tactics and sophistication as the greatest challenges in fraud identification. Importantly, scams and phishing attacks have seen the most notable increases, with 59% and 57% of respondents reporting a rise in these two types of fraud, respectively.
When it comes to balancing security and customer experience, 97% of respondents acknowledged the challenge. This echoes the fast digital adoption across Asia, where real-time payments are now commonplace, enhancing the risk of fraud for financial institutions and their clients. Consequently, it is crucial for these organizations to implement strong security measures while ensuring a positive customer experience to maintain trust.
GBG Finds That Proactive Technological Investments Represent A Priority
Among other findings, the report emphasizes that accurately detecting newer, more complex fraud types will necessitate a multi-layered approach that combines traditional anomaly detection techniques with advanced methods such as neural networks. However, the presence of legacy systems and technology complicates the integration of additional data into existing fraud practices, with 64% of respondents citing this as a primary reason for high false positive rates. This issue is further compounded by the prevalence of poor data quality, a concern shared by 52% of the respondents.
Additionally, the study found that while banks and financial institutions in Asia have traditionally relied on recruiting staff to address gaps in fraud detection, these organizations plan to increase their investments in machine learning (ML) and artificial intelligence (AI) over the coming years. Investment in these technologies is expected to rise from 16% in 2023-24 to 68% in 2025-26. This indicates a shift away from traditional anomaly detection methods towards automated solutions capable of managing more complex tasks. This transition aims to reduce the burden on staff and organizational costs while enhancing fraud detection efficiency.
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