VP Bank Group uses Fuzzy Payment Screening with ACTICO Machine Learning and cuts workload in half

Through artificial intelligence, VP Bank Group improves its hit quality thereby cutting its workload in half when screening payments against sanctions lists.

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About VP Bank Group

VP Bank Group is an internationally active private bank and one of the largest banks in Liechtenstein. It has offices in Vaduz, Zurich, Luxembourg, Singapore, Hong Kong and Tortola in the British Virgin Islands. VP Bank is listed on the SIX Swiss Exchange and the group’s financial strength is confirmed by its A rating from Standard & Poor’s.

Modern payment screening in private banking

VP Bank Group opts for new payment screening system based on ACTICO Machine Learning

The mounting pressure on financial institutions to meet ever-stricter compliance rules has led VP Bank Group to update its sanctions list screening. A review of the payment screening system used at VP Bank Group revealed that it no longer met the current requirements for fuzzy matching.

To ensure an accurate identification of potential risks without increasing the work and costs involved, the Liechtenstein-based bank decided to install a new payment screening system. It is based on ACTICO Machine Learning and is able to improve the quality of fuzzy matching significantly. At the same time, artificial intelligence has helped to halve the workload of compliance and payments staff at VP Bank.

Effectiveness and Efficiency in Fuzzy Screening

An intelligent monitoring system optimizes cost and risk at the same time

Fuzzy matching means that it should still be possible to identify risky transactions even if the name in the transaction does not exactly match the name on the sanctions list. A fuzzy search always produces more hits than an exact search. Non-risky false positives increase the workload in payment and compliance teams and lead to a trade-off between effectiveness and efficiency in payment screening.

  • Effectiveness = As many risky transactions as possible can be found
  • Efficiency = The least possible transactions that, on closer inspection, turn out to be innocuous can be found

By using ACTICO’s intelligent monitoring system, VP Bank Group managed to overcome this conflict of goals. Since the system was implemented, it was able to continuously reduce the hit volume and increase the hit quality.

The above average efficiency of the ACTICO Machine Learning model was confirmed during a benchmarking exercise.

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