What is it about?

Using a broader dataset on clients' characteristics and products in the bank can improve the client risk classification, and the precision in anti-money laundering models can be increased. Without considering the credit risk of business clients, changes in the credit risk, and the client's use of the bank, the bank is at risk of not detecting money laundering and using unnecessary resources to investigate flagged transactions that are not suspicious.

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Why is it important?

Banks use considerable resources to investigate flagged transactions to determine whether they are suspicious. By improving client risk classification, banks can improve their precision in detecting suspicious transactions.


Improving client risk classification by employing external and internal information about a client's bank use should be the starting point when improving anti-money laundering and anti-fraud models in banks and financial institutions.

Endre Jo Reite
Norwegian University of Science and Technology

Read the Original

This page is a summary of: Changes in credit score, transaction volume, customer characteristics, and the probability of detecting suspicious transactions, Journal of Money Laundering Control, April 2023, Emerald, DOI: 10.1108/jmlc-06-2022-0087.
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