Thought Leaders in Artificial Intelligence: Charlie Delingpole, CEO of ComplyAdvantage (Part 4)

Sramana Mitra: I’m thinking about what you said about these lists of people who have been sanctioned that you can access easily. What are the spheres of influence of these people? There are corruption rings all over the world. There are terrorist rings, drug cartel rings, and all other questionable groups. How do you map those out?

Charlie Delingpole: There are government policies around sanctions. You have different factions programmed. You have North Korea, Venezuela, and South Sudan, for example. Part of it is geopolitical to the extent that there is wide UN or US disdain for a particular group. That then merits the nuclear option of sanctions. 

Thought Leaders in Artificial Intelligence: Charlie Delingpole, CEO of ComplyAdvantage (Part 3)

Sramana Mitra: How easy is it to access the sanctioned list in the structured category?

Charlie Delingpole: That is easy because the US Treasury makes it publicly available. The real challenge is name matching. In Latin alphabets, it’s easy to name match because you can do simple heuristics.

Thought Leaders in Artificial Intelligence: David Talby, CTO of John Snow Labs (Part 6)

Sramana Mitra: How do you go to market? Is this a professional services go-to-market strategy? Technology-enabled services kind of strategy? 

David Talby: It’s a mix. It’s about half and half. We do software licensing and we also do professional services. 

Sramana Mitra: Is the professional service yours or is it outsourced or tied up with system integrators?

Thought Leaders in Artificial Intelligence: Charlie Delingpole, CEO of ComplyAdvantage (Part 2)

Sramana Mitra: Am I understanding it correctly if I say that you are doing natural language processing on publicly-available news coverage from around the world to identify names of people who are involved in questionable activities?

Charlie Delingpole: That is correct. 

Thought Leaders in Artificial Intelligence: David Talby, CTO of John Snow Labs (Part 5)

Sramana Mitra: What technique do you use? Since this is not big data, you cannot use machine learning. Do you use expert systems? How are you setting these things up?

David Talby: We do use machine learning and deep learning. We use a lot of deep learning and transfer learning. Now, we have our own built-in buildings.

Thought Leaders in Artificial Intelligence: Charlie Delingpole, CEO of ComplyAdvantage (Part 1)

This conversation explores the use of AI to create a database of questionable players to address money laundering and other shady behavior. Excellent PaaS strategy!

Sramana Mitra: Let’s start by having you introduce yourself as well ComplyAdvantage.

Thought Leaders in Artificial Intelligence: David Talby, CTO of John Snow Labs (Part 4)

Sramana Mitra: Talk about the healthcare and life science domain-specific products. Is that all internal or is some of that also open source? 

David Talby: That’s our product. That’s a licensed product. We have two licensed products: Spark NLP for healthcare and Spark OCR. Spark NLP for healthcare is an extension of the open-source library but it uses a separate code base and a separate set of models.

Thought Leaders in Artificial Intelligence: David Talby, CTO of John Snow Labs (Part 3)

Sramana Mitra: If I understand this correctly, you have the NLP engine, which is fairly horizontal; and you are applying various domain-specific heuristics and workflows on top of that to create solutions for different use cases in different industry segments.

Although they are all data science users, the workflow is different and the domain is different. The oncology knowledge is different from the clinical trial identification.