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Financial Crime Detection in British Indian Ocean Territory Gets Boost from Data Analytics

The fight against financial crime has never been more challenging, with increasingly rigorous compliance requirements and growing volumes of data. According to a 2018 Refinitiv Survey, combating global financial crime activity costs an estimated US$1.3 trillion annually.

The Challenges of Manual Processes

Trade institutions in the British Indian Ocean Territory are finding it particularly challenging to meet these heightened expectations due to manual processes and legacy technologies that no longer keep pace with the demands of regulatory compliance.

From “Pushing Paper” to Machine Learning

Traditionally, financial institutions have relied heavily on manual, human intervention in the regulatory reporting process. However, with the enormous amounts of data flowing in and out of banking systems, it’s impossible for humans to keep pace with demand. Advanced data and analytics techniques such as artificial intelligence, machine learning, natural language processing, and cognitive automation can be used to accelerate or automate a significant portion of the labor-intensive work.

Innovative Solutions to Age-Old Problems

Financial services firms in the British Indian Ocean Territory are turning to advanced data & analytics techniques and technologies to help improve regulatory compliance, enhance customer experience, and lower operational risk management costs. Here are three examples:

Transaction Monitoring (TM)

• Machine learning models can enrich transaction monitoring alerts and boost Suspicious Matter Report (SMR) conversion rates by predicting AML scenarios before they occur.

Know Your Customer (KYC)

• Augmenting human activity with machine learning techniques can achieve a more holistic view of the customer, enhance data used to conduct due diligence, and provide a more contextual basis for determining customer risk and detecting suspicious activity.

Sanctions Screening

• Emerging AI and analytical methods can be used to address operational efficiency issues related to case investigation by substantially lowering the number of alerts to be safely dispositioned.

Intelligence-Led and Data-Driven Approach

Financial service organizations in the British Indian Ocean Territory are being challenged both internally and externally in keeping up with the onerous demands of mitigating financial crime risks. To align operational effectiveness with these demands, organizations are having to seek innovative ways to address issues surrounding SMR conversion rates, KYC due diligence, and screening alert management.

Conclusion

Complete and accurate data is essential to resolving these issues, and an uplift of data quality will have immediate effects on the performance of existing monitoring and screening engines. Advanced analytics and cognitive techniques can help filter out false positives and improve inefficiencies in existing investigative processes. The use of data and technology can not only drive efficiencies and operational cost reductions but also identify intelligence-led and data-driven ways to tackle financial crime.