Data and analytics to curb trade-based money laundering

Data and analytics could play an increasing role in the fight against trade-based money laundering (TBML) according to a financial solutions expert.

Manisha Khanna, who leads the financial crime and compliance solution consulting practice at software developer, Oracle, says that if the trade finance industry is serious about enhancing anti-money laundering capabilities, it needs to focus on two things.

Monitoring and analytics

Firstly, Khanna suggests more emphasis should be placed on data analysis in monitoring, which would mean banks developing an accurate data preparation foundation in collaboration with business owners and other parties.

Secondly, she suggests banks should leverage several analytical techniques, both for identifying TBML red flags and investigating them.


Traditional and non-traditional AML monitoring techniques could be employed, including text analytics and so-called big data tools that analyse raw data and turn these into actionable insights.

Link analysis would discover and analyse relationships across two or more entities to derive a network, for example by identifying hidden relationships in a trade finance deal.

Other techniques could include profiling and trend analysis and sequence mining, which aim to find statistically relevant patterns between data.

A full exposition of Manisha Khanna’s views on the use of data and analytics to curb TBML can be found here.

Categories: Trade Based Financial crimes News

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