Thought Leaders in Artificial Intelligence: Cognitive Scale CEO Akshay Sabhikhi (Part 2)

Akshay Sabhikhi: I’ll give you a very high-level example. How do I understand you if you’re a patient or a shopper? How do I understand you at a really deep level? How can I use that to personalize the actions or recommendations to almost where it seems like you know me personally?

The second class of problems is what we call amplify. We believe that a lot of organizations have complex business processes. A complex business process is generally a combination of fully-automated or semi-automated and you have people who manage that process. The efficiency of those processes today is limited because it’s unable to look at all the extraneous data that surrounds the process.

Our view is, how can we bring AI to surface insights to the operator of the process or directly to the process. You can learn from the outcomes of a process and fine tune the process in-flight. For example, consider claims management in healthcare. You go and submit a claim. The hospital packages the claim and sends it to an insurance company. This entire process takes time. It’s one that is fraught with denials that happen because the insurance company doesn’t quite understand the reason for the claim or due to missing information.

About $500 million or so is stuck in this appeals process. It’s a complex process. How can you bring AI to help identify what’s likely to get denied so that you can go fix it right upfront. We have applied our augmented intelligence platform around engage, which is the front-end of how you deal with customers and amplify, which is how you deal with back-end processes.

Sramana Mitra: Excellent summary. Let’s take it one level down. Pick whatever customer you want to take and give me a real-world case study of the engage class of problems.

Akshay Sabhikhi: Think of a large bank. You have clients who have invested in your bank because they have brokers’ accounts or wealth management accounts. Most large banks will tell you that they are only able to deal with you as a customer, especially when it comes to wealth management, if you have above a million dollars. Think about what happens in a wealth management scenario.

You have a wealth advisor who is supposed to look at all the possible events that are happening around. He’s supposed to understand your portfolio and tell you things you should be concerned about. This is a very expensive proposition. Because banks can only serve populations who have $1 million or higher, all the people who are below that threshold are targets by other advisors out there. If we have our wealth advisors and they do a really good job of managing only 20 customers, can you bring AI to these wealth advisors to augment them so that if news breaks out, how can I have AI tell me that these are the clients that are impacted and this is the script of the conversation you need to have with them.

If I can do that with AI, imagine what wealth advisors can do. They can serve 200 customers. This is giving banks the ability to go further down in the threshold of assets under management to actually serve the population that is under threat. This is an example of how AI is constantly monitoring market events and market signals. Your portfolio could be a complex portfolio. It brings all of that into a very succinct timely advice to the wealth advisors so they can have a conversation with you and tell you exactly where your portfolio is. This is all about scale and productivity.

This segment is part 2 in the series : Thought Leaders in Artificial Intelligence: Cognitive Scale CEO Akshay Sabhikhi
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