The 5 tech improvements banks and other financial institutions will need to maintain AML compliance

anti money laundering

Banks have been focused on identifying and preventing money laundering and terrorist financing for about two decades, using both manpower and technology.

While banks have worked to combat perpetrators’ increasingly sophisticated tactics, regulators have identified needed improvements in overall process management and end reporting.

The major technology improvements required by banks and financial institutions to better comply with requirements for Anti-Money Laundering/Combating the Financing of Terrorism (AML/CFT) include the following:

  1. Improve data quality. Banks face difficulties in getting complete, standardized and non-conflicting data from multiple transaction systems. Better data quality takes on more significance today when data – driven advanced analytics are used to detect financial crimes.
  2. Reduce false positives. Several factors — including increased transaction volumes, poor data quality, an increased number of rules and lack of sufficient technology adoption — have converged to result in more overall alerts and larger rates of false-positives, making it more difficult to detect actual cases. All of this subsequently requires significant remediation efforts, usually in the form of increased labor deployments, leading to delays in decision-making and reporting.
  3. Deploy advanced analytical tools. Banks are adopting artificial intelligence, machine learning, and unstructured data analytics, including social media and text analytics, to enhance due diligence and AML processes. Behavioral trend analytics using cognitive computing can help detect unusual behavior of a single actor or a group of bad actors. Analyzing similarities between existing and past financial crimes through link analysis can help build stronger cases while trusted pair identification through link analysis can help reduce false positives.
  4. Increase efficiency of resolutions and reporting. Today it takes nearly three hours, on average, to complete an alert investigation. Banks can more quickly resolve alerts and generate suspicious activity reports (SARs) by using technology to reduce manual intervention and improve process flow.
  5. Adopt an enterprise level risk-based approach. Banks need to supplement traditional, standalone, rules-based AML approaches with risk-based platforms capable of detecting both fraud and money-laundering activities across channels. They also need to put in place comprehensive risk-scoring mechanisms that consider customer profile and transaction scoring, among other factors. To gain individualized knowledge of a customer, including his or her social context, increased usage of semi-structured and unstructured data will be required.

While banks and other financial institutions are trying to enhance internal capabilities towards better compliance, there’s also a need to use third-party utilities for Know Your Customer (KYC) and due diligence data. Institutions are building common databases — of customers, of transactions, of alerts — that help detect cross-financial, cross-organizational crimes while ensuring data confidentiality norms.

Governments and regulators are promoting councils to create shared databases at an industry level, which they can leverage to both prevent financial crime and cultivate business statistics that offer better direction to the industry about products and pricing. These AML initiatives must be seen not as a standalone compliance requirement. Banks need to leverage them to improve business results.

Ashok Jhunjhunwala leads risk management and compliance initiatives for the banking industry for DXC Technology. He has been engaged with the industry in the solution and delivery of multiple programs on Anti-Money Laundering, Financial Risk Management, Enterprise Data Warehouse and Regulatory Reporting. He worked about 13 years in the banking industry, followed by 12 years of related consulting for technology companies.

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