The hidden costs of the COVID-19 pandemic: part 2

Johannesburg, 30 Jul 2020
Read time 3min 40sec
Lizette Sander, product manager, Bateleur Software
Lizette Sander, product manager, Bateleur Software

Terrorists and money-launderers everywhere are taking advantage of the COVID-19 pandemic to increase their nefarious activities.

Rohit Sharma, president and managing director of the Association of Certified Anti-Money Laundering Specialists (ACAMS), the largest international membership-based organisation of financial crime detection and prevention professionals, says the global anti-financial crime (AFC) community has been deeply impacted by the pandemic.

ACAMS members have reported shifts in both customer and criminal behaviour, including a surge in cash withdrawals, online banking and crypto-currency related activity.

“Now more than ever we need the latest resources and knowledge to help navigate this new operating landscape,” Sharma warns.

However, Lizette Sander, product manager at Johannesburg-based Bateleur Software, points out that crime compliance has become a significant cost burden for most banks and financial institutions.

The fines and related costs associated with non-compliance, such as defending allegations, legal expenses and remediating deficiencies raised by the regulators – let alone repairing the reputational damage caused by reports of non-compliance – represent only part of these costs.

“The operational costs are far more onerous, with approximately two-thirds of these AML compliance costs related to personnel costs, with only about 20% spent on technology,” Sander adds.

A 2019 study involving 140 financial institutions in the US and Canada revealed they spend more than $31.5 billion annually on AML compliance processes such as customer onboarding, identity verification, investigations, watchlist screening and transaction monitoring.

“The trend in recent years to continuously augment staff to cope with these increased workloads and regulatory demands is neither sustainable nor cost-effective in the long run,” says Claudia Huesmann, Senior Partner at Analytics software company FICO.

She also says the current approach to traditional rules-based transaction monitoring systems has resulted in excessive false positive alerts “which lead to unmanageable workloads”.

Sander agrees, pointing out that false positives account for 75%-90% of all alerts. “Huge amounts of time and money are wasted on false positives. Not only are they costly, frustrating and boring, they also result in precious resources being diverted away from managing real AML risks,” she says.

The goal, Sander continues, must be to reduce false positives as much as possible. The best way to do this is through leveraging the power of technology, particularly artificial intelligence (AI) and robotic process automation (RPA).

RPA allows financial institutions to streamline and automate the process of investigation and alert handing in KYC and AML by empowering compliance managers to configure software to capture, interpret and manipulate data for triggering responses and reducing manual steps.

Much of current AML and KYC alert handling involves manual tasks that tend to be:

  • Repeatable;
  • High-volume;
  • Data intensive;
  • Time-consuming;
  • Prone to error; and
  • Based on clearly defined rules and criteria.

“A machine – a robot – can do these tasks much better than a human,” Sander says.

“Clearly defined alert rules and case rules, which can be set up to operate autonomously around the clock using time-based rules, and which are specific to the needs and situation of the individual financial institution, will take away certain repeatable manual tasks from human investigators. This will free them to focus on more complex tasks.”

In addition to delivering lower operational costs due to reduced investigation time and increased productivity, estimated at between 25%-60%, analytics-driven alert prioritisation and RPA has the potential to deliver better accuracy – lower false positives despite a 20% increase in suspicious activity reports; and rapid return on investment.

However, Sander emphasises that to be truly effective, robotics and AI should be integrated into an enterprise-wide alert and case management solution that is based around customer-centricity, thus helping to reduce the risk of duplicate alerts. It should also provide a holistic view across all financial crimes and offer configurable workflow that can be adapted to the organisation’s specific needs and processes.

“Using a scalable IT environment to fulfil requirements for detecting fraud and AML at the same time, would not only provide an economy of scale, but would also allow institutions to take a far broader and integrated approach to detecting illicit activities,” she concludes.

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