Quantexa: A Better Way to Nail a Money Launderer?
July 29, 2020
We noted the Techcrunch article “Quantexa Raises $64.7M to Bring Big Data Intelligence to Risk Analysis and Investigations.” There were a number of interesting statements or factoids in the write up; for example:
Altogether, Quantexa has “thousands of users” across 70+ countries, it said, with additional large enterprises, including Standard Chartered, OFX and Dunn & Bradstreet.
We also circled in true blue marker this passage:
As an example, typically, an investigation needs to do significantly more than just track the activity of one individual or one shell company, and you need to seek out the most unlikely connections between a number of actions in order to build up an accurate picture. When you think about it, trying to identify, track, shut down and catch a large money launderer (a typical use case for Quantexa’s software) is a classic big data problem.
And lastly:
Marria [the founder] says that it has a few key differentiators from these. First is how its software works at scale: “It comes back to entity resolution that [calculations] can be done in real time and at batch,” he said. “And this is a platform, software that is easily deployed and configured at a much lower total cost of ownership. It is tech and that’s quite important in the current climate.”
Some “real time” systems require time consuming and often elaborate configuration to produce useful outputs. The buzzwords take precedence over the nuts and bolts of installing, herding data, and tuning the outputs of this type of system.
Worth monitoring how the company’s approach moves forward.
Stephen E Arnold, July 29, 2020
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