AI Assessed to Strengthen Digital Fraud Prevention

The rise of digital financial transactions in Indonesia has been accompanied by an increased risk of fraud, pushing the banking and financial technology (fintech) industries to strengthen risk management systems by utilising artificial intelligence (AI) to detect potential crimes earlier. The development of digital financial services has enabled transactions to occur more quickly, across multiple channels, and in real time. Meanwhile, criminals are continuously developing new methods by exploiting gaps in digital processes, user behaviour, devices, and security systems. The types of fraud have become increasingly diverse, extending beyond unauthorised transactions. Methods such as social engineering, account takeover, scams, identity theft, application misuse, payment fraud, internal access abuse, and cybercrime pose threats that can lead to financial losses, operational disruptions, reputational damage, and a decline in public trust in financial institutions. The urgency to strengthen security systems is underscored by the rapid growth of the digital economy. Data from the Indonesian Internet Service Providers Association (APJII) shows that the number of internet users in Indonesia has reached 221.56 million, with a penetration rate of 79.5%. Meanwhile, Bank Indonesia recorded that the volume of digital payment transactions in April 2026 reached 5.15 billion, an increase of 42.86% compared to the same period the previous year. Transactions via mobile banking, internet banking, and QRIS also recorded significant growth. Amid this increase in digital activity, the number of financial transaction fraud cases continues to rise. According to data from the Indonesia Anti-Scam Centre (IASC) under the Financial Services Authority (OJK), the centre received 579,459 reports of financial transaction fraud from its inception on 22 November 2024 until 31 May 2026. During the same period, 998,558 accounts were reported, 515,553 accounts were blocked, and victim funds totalling IDR 638.9 billion were secured. This situation has rendered manual checks or post-incident actions inadequate. The financial industry requires a system capable of reading risk signals early, connecting various data sources, and assisting in swift and accurate decision-making. This issue was discussed at a forum titled ‘From Compliance to Intelligence in the Era of Digital Banking Risk’, which brought together practitioners in risk management, compliance, IT security, digital banking, operations, and technology transformation. The forum highlighted the importance of shifting from a reactive anti-fraud approach to a proactive system supported by data analytics and AI technology. Financial services and regulation practitioner Aribowo assessed that fraud can no longer be viewed solely as an operational issue, as its impact touches on governance and public trust. ‘Amid the growth of digital transactions, fraud is no longer just an operational risk. It is closely linked to public trust, consumer protection, governance, and institutional resilience. Therefore, banks and fintech companies must ensure their anti-fraud strategies not only meet compliance requirements but also include clear processes for detection, escalation, investigation, and follow-up,’ he stated. Banking risk technology practitioner Bayu Hasdianto added that fraud patterns are becoming more complex because transactions now occur very quickly and across various digital channels. ‘Banks face evolving fraud patterns, from social engineering and account takeover to misuse of digital channels. Therefore, a fraud management system must be able to read risks from various sources, including transactions, customer behaviour, devices, and channels used. The sooner a risk signal can be detected, the greater the opportunity for banks to prevent losses and keep the customer experience safe,’ he explained. Strengthening anti-fraud systems is also in line with the latest regulations in the financial services sector. The OJK, through POJK Number 12 of 2024, requires financial service institutions to implement an anti-fraud strategy that includes prevention, detection, investigation, reporting, sanctioning, monitoring, evaluation, and follow-up. Thus, fraud management becomes an integral part of risk governance, not merely a support function. The forum also introduced an AI-based fraud management system that integrates transaction monitoring, user behaviour analysis, device identification, risk level assessment, investigation management, and workflow automation. This approach is considered capable of helping financial institutions accelerate responses to potential crimes, reduce losses, strengthen audit processes, and maintain customer trust. Deputy Vice President of Business Development, Product, and Partnerships at M2P Fintech, Madhusudhan Ramakrishnan, stated that AI technology not only generates alerts but also helps understand the context of risk so that decisions can be made more accurately. ‘Banks and fintech companies need a system that not only generates alerts but also helps teams understand the context behind each risk. AI can strengthen this process, from anomaly detection and risk assessment to response prioritisation and learning from previous cases. With an integrated system, fraud management can become more proactive, accurate, and relevant to business needs,’ he said.