Artificial Intelligence Plays a Crucial Role in Financial Crime Prevention in Oman
In the wake of the COVID-19 pandemic, Oman’s financial services industry has witnessed rapid growth. However, this digital transformation has also created new risks for financial institutions (FIs) to navigate. To combat these risks, regulatory bodies have been encouraging market participants to integrate technology into their financial crime control frameworks.
Regulatory Guidelines
The Central Bank of Oman has issued guidelines urging FIs to utilize digital identity verification systems to perform customer due diligence. The bank has also mandated FIs to define and implement a strategy for sourcing and developing counter-fraud systems and technology to manage fraud risks.
Integrating Anti-Financial Crime Technologies
In this article, we will examine how FIs can integrate suitable anti-financial crime technologies in two key processes: identity verification and transaction monitoring.
Identity Verification
Impersonation Fraud Risks
Impersonation fraud remains a significant risk for FIs when onboarding new customers through digital channels. While traditional controls such as multi-factor authentication provide some protection, financial criminals have found ways to defeat these measures. Artificial intelligence (AI) now offers more sophisticated solutions that can complement or replace existing identity verification controls.
AI-Driven Solutions
Two AI-driven solutions include:
- Identification document verification systems: scans live identification documents uploaded by customers to verify their validity and authenticity.
- Biometric validation solutions: uses facial recognition, liveness detection, age detection, gender detection, blinking analysis, mood analysis, and behavior analysis to validate customer identities.
These AI-driven solutions can significantly mitigate identity manipulation risks in digital account opening processes, optimize financial crime compliance resources, and provide cost benefits.
Transaction Monitoring
Optimizing Transaction Monitoring Frameworks
As digital payment volumes surge in Oman, FIs are looking for ways to optimize their transaction monitoring (TM) frameworks. The Central Bank of Oman has enabled FIs to explore dynamic intelligence-led TM models that can identify wider networks in which customers operate.
AI-Driven Solutions
Two AI-driven solutions that can augment incumbent TM frameworks include:
- Transaction analysis solutions: assesses multiple data points linked to a transaction to uncover complex patterns.
- Specialized trade-based TM solutions: automates large parts of the due diligence process for trade-based money laundering detection.
The inclusion of AI in the TM process can be a game-changer, enabling FIs to automate manual tasks such as alert investigations and providing time and cost efficiencies without compromising financial crime risk management.
Conclusion
The use cases for AI-driven solutions are numerous, and their benefits are apparent. In line with regulatory strategy across the Middle East, FIs should review their financial crime risk management strategies and consider making technology a focal component to realize the true benefits that AI can deliver for business and compliance.