SRL NPL for Sanctions Compliance

Here’s a simple question:

Why don’t watchlist screening vendors deploy semantic role labeling (SRL) methodologies when screening free-text fields?

The value proposition is obvious — analysts would save hours of work each week by not having to clear false-positive alerts like the match of the word “shipped” to “XHAFERI, Shefit” (SDN).

But seriously, this is a huge problem. If a large portion of a financial institution’s business activity is in Letters of Credit or similar transactions that involve sending large free-text messages blocks between banks, then these garbage matches can easily balloon to more than 50% of generated alert activity and hamper cost-center efficiency.

As mentioned in a previous post (here), two criteria must be satisfied for quality matches to be generated:

  1. The internal company data and sanctions record data must be comparable.
  2. The method of comparison must be appropriate for the type of records being compared.

Failing to implement SRL methodologies across free-text fields flies in the face of the second criteria.

Essentially, SRL breaks down a sentence into it’s principle components (think subject, object, action, etc.), like “Mary shipped little lamb” to:

  • Subject: “MARY”
  • Action: “SHIPPED”
  • Object: “LITTLE LAMB”

Under this processing methodology, it wouldn’t make any sense to compare “shipped” to sanctions list or watchlist records – but, that’s what we do now with our current carpet-bomb string matching approach.

So again, why don’t watchlist screening vendors deploy SRL methodologies when screening free-text fields?

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