The pandemic has been a catalyst for digitization in trade, and subsequently a lot of transaction data is being generated and stored in various formats across systems. A huge opportunity has emerged to apply artificial intelligence to that data to transform financial crime prevention.

AI-powered technologies can generate insights that enable analysts to review holistic information on entities and hidden networks as well as compute risk scores, enhancing overall risk management.

It is a far cry from bank employees scrutinizing transactions with only their eyes. As deal volumes increase and financial crimes become more complex, solely relying on manual investigation has proven to be ineffective, inefficient and pricey.

Given the expertise and effort needed to complete checks in the past, the barrier for compliance has been set high. Smaller banks without the budgets of their global counterparts have had to take a risk-based approach involving selective checks rather than the assessment of every deal.

As regulators around the world are increasingly strict and demand that all transactions be reviewed, a risk-based approach is no longer adequate. Regulators are taking a no tolerance stance towards those found to be breaching regulations and failing to spot illicit activities.

Earlier this year for example, the US Treasury Departments’ Office of Foreign Assets fined a French bank that specializes in trade finance $8.6m for Syria-related sanctions violations.

The digitization space in trade has traditionally relied on templates, whereby data is extracted based on a model of a document. However, in trade there are no standard formats for documents, so using an intelligent technology to scan different formats and content and extract data just as a person would do with visual inspection is vital for improving accuracy rates.

In our work at TradeSun that focuses on analyzing trade finance documents, we are using neuro visual techniques within our hybrid-AI SaaS platform. Inspired by facial recognition technology like that which unlocks mobile phones, the platform works by learning to extract, identify and marry up key information such as prices and beneficiaries.

Using a solution that leverages AI gives banks, big and small, examining transactions an easier, less costly and more effective way to identify malign actors and meet international regulations. AI enhances the quality of decision-making and allows the completion of cases within a faster turnaround time – and this will only improve as we move towards real-time assessment.

Looking ahead

At present, much in the way of anti-money laundering and financial anomaly detection is carried out after transactions are completed. Technology is increasingly being used in real-time for checks during the processing of transactions, with AML initiatives shifting from analysis after the event to immediate intervention by verifying actors.

AI trends:

• AML teams will take advantage of AI thanks to its effectiveness in increasing operational efficiency and support in risk management. When an AI-powered technology is employed at scale, it enhances the overall quality of compliance as it can analyze and process large quantities of data in real-time, categorizing transactions as low, medium, or high risk based on the level of suspicion.
• AI solutions will integrate with banks’ due diligence workflows – from external data collation to comparison with customer provided data, verification from sources and third-party databases.
• The know your customer (KYC) process, completed at the start of a bank’s relationship with a client and then periodically reviewed as part of customer due diligence, is set to be assessed in real-time, helping to also generate corporate ownership structures.
• The high number of suspicious transaction reports (STRs) by banks due to low accuracy in detection of fraudulent activity will improve significantly as AI provides reviewers with more accurate results. The number of false alerts and misses will decrease, reducing the workload on banks as well as financial crime enforcement agencies that are tasked with sifting through STRs.

Artificial intelligence will continue to disrupt trade compliance for the better post-pandemic – just as it will in other areas of life and industries. Stakeholders in trade that deploy compliance tools that leverage AI can expect improved results, higher efficiency and lower costs. As we move towards real-time assessment of transactions, the technology will only become more integral to powering everyday operations and combatting financial crime.

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August 23, 2021