Artesian CEO on AI and RegTech / RiskTech

The Artesian Opportunity View ties together Salesforce Opportunity data by stage with Artesian Sales Triggers, helping surface key opportunity insights in context.
The Artesian Opportunity View ties together Salesforce Opportunity data by stage with Artesian Sales Triggers, helping surface key opportunity insights in context.

Recently, I had the opportunity to sit down with Artesian Solutions CEO Andrew Yates and discuss topics including artificial intelligence and risk tools they are integrating into their social selling service.  This is the second in a series of interview excerpts I am publishing this week.  On Monday, Andrew discussed Artesian’s 2016 entry to the US market.


Michael: You have recently begun to introduce AI capabilities into your platform.

Andrew: What we’ve done in our first incarnation of bot-driven AI is we’ve created something that we call an “insight agent” that, through an API into Salesforce, can build you a view of threats and opportunities within your pipeline. Which, in itself, is pretty damn useful; much more useful than a forecast report or a dashboard which is the way you see it in Salesforce today. Then we’ll lay out all of those deals by stage and value and overlay today’s new social and demographic context on top.  That’s pretty useful.

With the latest release, we’ve created a bot which literally reads and interprets the news in relation to the stage of the sales process that you’re at. And, where it sees a particular trigger that has meaning in relationship to a particular stage, it flags that. Most organizations have implemented the concepts of sale stages when they’ve implemented CRM.

Typically, when I ask somebody, “how many stages do you have?” They’ll say, “between five and seven.” The system automatically builds you a view depending on how you’re implementing Salesforce, however many stages you’ve implemented and what you call them. Then what the bot does, is it crawls all over the news looking for things that could impact those opportunities at the stage they are at.

Let’s say, I’ve got a six-stage process where stage six is closed and stage five is a negotiation.  Artesian’s insight agent finds out about a CIO who has left the business. The insight agent will notify the user that there’s a potential problem with the deal in their pipeline. The agent will tell them why there is a problem and how it’s been categorized.  There’s half a dozen next-best actions that we bundle up with the insight as we deliver it. That’s our first attempt at taking the concept of machine-based learning and natural language processing, combining it with an AI bot, and trying to make that useful for customers.

We’ve introduced the ability for the user to customize their own topics, keywords, and trigger events. We offer a bunch out of the box, and we also wrap a managed service around it and easy implementation to every customer.

We’re also seeing a lot of activity in the “RegTech/RiskTech” arena with the growth of cybercrime and terrorism, and the sensitivity around regulation of any financial, FCA [UK Financial Control Authority] regulated [business]. There are regulations that organizations need to comply with. We’re increasingly being asked by our financial services customers, particularly the banks, to get deeper into being able to provide those capabilities inside of Artesian.

Organizations want to mitigate risks. They want to fall within the arena of whatever the regulation is and comply with the law, but they also want to exploit the technology as best they can to make sure they write the best business that they can. We’re doing some work at the moment in conjunction with one of our demographic data suppliers. What we’re looking to do is extend the capabilities in Artesian to provide some of the capabilities that our customers are asking for in the RegTech / RiskTech environment. We’re going to introduce risk agents. Risk agents look at the real-time present and it looks at the past. It specifically looks at things that are in-line with the regulations and also in-line with the stated risks that the customer has mapped out.

What that translates into is a service that is not only compelling in terms of customer acquisition, customer retention, and yield, but also compelling from a kind of, you don’t go to jail if you’re using Artesian because it’s doing the regulation and risk job for you as well.

Michael: When you say risk app, are you talking more about supplier risk, compliance risk, credit, reputational?

Andrew: There are 40 or 50 pretty big companies doing this thing already. What we’re talking about is company-centric intelligence, but also the people associated with that company and the intelligence that we’ll need to derive around whether something is risky or not. It could be the performance of a business. It could be some adverse news in relation to that performance. Or it could be that an individual who has a beneficial ownership, more than a 5% stake in a business, happens to be on a naughty list in terms of the PEP [Politically Exposed Persons] or sanctions.

At the moment, we have risk triggers in the opportunity view. They’re not compliance risk triggers. If you’re going to a client, they need to know about key beneficial ownership.

Michael: Is that part of the opportunity view or is that a new type of view?

Andrew: A new type of view.  We have risk triggers in the opportunity view, but they’re not compliance risk triggers.  If you go into a bank, they need to know about beneficial ownership, adverse news going back three years, PEP, sanctions, real-time alerts from stock exchanges.  None of that is feasible within a generic instance of Salesforce.com in an opportunity view.

Michael: It sounds you’re looking to move beyond the sales and marketing teams to start to get to into things like onboarding, KYC [Know Your Customer], AML [Anti-money Laundering], PEP, and other compliance aspects that really go into monitoring of clients as well as the initial onboarding.

Andrew: Yes, if you go back to the whole customer curious mantra and deep relationship management, we like to say that we put the R back into CRM.  We are all about that relationship.

The conversations we are having with our large customers would indicate we are on the right track with that.


The interview will be continuing over the next few days with discussions of what it means to be a “customer curious” business and how Artesian maintains a very high engagement rate amongst its users.  Monday’s blog discussed Artesian’s 2016 entry into the US market.

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