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Smarter financial crime compliance

Conduct and consequences Print

The cost of meeting know-your-consumer (KYC) and anti-money laundering (AML) requirements with human resources is spiralling out of control. New digital technologies offer banks a lifeline, with the potential to realise sizeable cost savings quickly without the need for significant investment.

Stricter KYC and AML requirements

In response to ever more digitally sophisticated financial crime threats, regulators around the world are raising the bar on banks’ KYC and AML requirements – and handing down record fines for lapses.

An extraordinary level of human effort is required to meet these demands. In addition to the KYC platform requirements, transaction monitoring can generate more than 1,000 alerts every day for a large bank. If each one of these alerts takes an hour to investigate, a bank will need 133 employees working full-time to cover this aspect of compliance alone.

The cost is staggering.

In 2016, global expenditures on financial crime compliance by top-tier banking and capital markets firms reached a record breaking US$32b – a figure currently projected to rise to US$36.8b by 2018."

This is not just expensive — it’s incredibly inefficient. Of the alerts reviewed each day, around 80% are typically quickly found to be benign. The remaining 20% go to the next level of investigation, which takes more time. Of these, another 15–19% are not suspicious.

Data analytics and robotics offer clear opportunities to get costs under control

The two most common solutions our banking clients are working on for improving AML cost efficiencyare:

  • Data analytics. Compliance teams can use advanced data analytics to automatically monitor watchlists, transactional activity and adverse media screening, enabling firms to proactively identify risks and opportunities. Analytical tools and visualization software give stakeholders fast insight into what’s really going on with a particular account.
  • Robotics process automation (RPA). RPA can pull information from multiple bank systems, automating the vast majority of tasks required for initial investigations of transaction monitoring alerts. In addition, RPA is based on a step-by-step process flow that obtains internal and publicly available documentation to complete a KYC file, thereby reducing onboarding and periodic review times while enhancing customer experience.

RPA can be easily applied to automate repetitive, clerical processes within a screening function based on the decision rules defined by business and operation. Banks can also robotically preprocess negative news searches and collect customer information from external systems to screen individuals and organizations. The software then creates dockets in a standardized format for analysts to review easily and quickly. RPA can significantly reduce the time it takes to complete a KYC review, while improving cost- effectiveness. Banks need to harness data analytics and RPA in numerous processes within the financial crime control framework, including:

  • KYC due diligence and client on-/off-boarding
  • AML transaction-monitoring alert investigations
  • Name screening for sanctions and PEP investigations
  • Adverse press investigations
  • Payment screening for sanctions investigations
  • Source of wealth reviews
  • Linking accounts across the institution, inclusive of all markets and segments, to create a one-client view

The only question is whether banks should start with small incremental steps or large-scale initiatives, or a blend of both. Either way, the days of trying to manage AML and KYC compliance efforts with purely human resources are over.