WealthTech Insights #69 with Robert Kirk. Use Cases for AI Data Analysis: Marketing and Early Warning of Life Events

Can AI help advisors more accurately predict a life event and generate better marketing to drive more onboarding and investments?

Interview with Robert Kirk,
Founder & CEO of InterGen Data, Inc.

A new way of visualizing data

Advisors have access to tons of client data. With the help of CRM systems, advisors can now effectively utilize that information to get the most out of their technology and offer better advice. A handful of companies are now taking this data discovery to the next level with AI and machine learning algorithms. Technological advancements like these don’t typically offer much in terms of visuals and Machine Learning and AI are buzzwords that don’t really mean much to the average financial advisor.

However, Robert Kirk, Founder and CEO of InterGen Data, Inc. informs me that the reasoning behind their robo advisor widget Digital Advice Via Demographics, or DAViD for short, is to visually and contextually show advisors the most relevant information about their clients’ upcoming financial journey.

“What matters to me, and the reason I created DAViD, is to show people the relevance and elegance of AI-based machine learning.  Until now, its been really tough to show people what matters. Most people would ask, What are you going to show me? Data being juxtaposed and compared in Excel? That’s just not exciting and no one really cares.”

The visualized output also has to be easy to understand and beg the user to interact with it. DAViD offers a cashflow forecast that shows year-by-year expenses as an overlay to their income showing “Disposable Income.”  Therefore, more green in the cashflow statement is good and less green is bad. The beauty of machine learning is that this data can be displayed and/or used by advisors however they see fit. For example, advisors can create custom cash flow statements in real time with their clients, have them as base personas/profiles to start a conversation, or let their clients access it for themselves via smart speakers (Alexa, Google, Cortana, Siri).

The AI solution Robert and his team created finds correlations among millions of people and “learns” when advisors confirm DAViD’s suspicion. Once an advisor sees a layout of all the financial plans and the possible red flags for particular clients, they can call for a meeting, discuss the best ways to overcome unforeseen expenses, like medical bills, or even market to their customers.

Automated intelligent marketing

Neural storytelling may sound like a strange medical condition, but it’s actually machine learning and AI applied to content creation. How does this work? Deep learning algorithms identify what content is the most popular, find correlations, and create new content that gets more clicks and views than human-generated content. Robert says use cases already exist for things like lead-scoring and dynamic pricing.

No matter where machine learning is applied, the kick-starter is impetus (a life event). If advisors can market something before that life event, there’s a better chance of either getting a new client or helping an existing client.

“A good example of impetus to action is the following: When do you buy insurance? When it’s on sale? No. No one buys insurance on sale. You buy insurance because you either bought something, you broke something, or you created something. Those are life events!”

An early warning system based on AI

Robert says most advisors fall in one of two groups:

  1. Those who know about AI but don’t have a master data management strategy and/or approach to use their data
  2. Those who are scared of the implications of AI (e.g., “This is scary stuff. I don’t want to tell people they’re going to get cancer. How am I going to have this conversation?”)

Neither group is ready to embrace AI, so what changes should be made in the next couple of years?

Group 1 has to understand that without a good CRM or proper data management policies, you can forget about AI. Data has to be normalized so solutions like the one InterGen created can plug and chug. Clean data = better predictions = earlier warning of life events.

Group 2 has to realize that it is logically, morally, and ethically right to warn a person if there is a chance of the individual getting sick. Granted, advisors are not doctors by any stretch of the imagination. Instead, it is the advisor’s duty to know if there’s a possibility clients need to spend money for an unexpected event.

“The challenge is making sure advisors and firms are ready for that change. I have data that can change their practices. I have data that can really help their clients.”

Not all use cases are medical-related. Rob highlights an example of how their system can help in a use case for the mortgage industry. The U.S. Mortage industry is approximately $9.7 Trillion and the default rate is a little over 3.2%.  This means that defaults in the U.S. total up to around $310 Billion. However, after much research there are only 5 main reasons that people default on their loans; 1) Loss of Job, 2) Divorce, 3) Death of Spouse, 4) Critical Illness (Cancer), 5) Having to take care of a loved one. Now as you can see, each of these are Life Events but if you were to apply InterGen Data’s AI solutions to mortgage clients, you would be able to quickly find correlations to other clients who have defaulted. This doesn’t necessarily mean that they “will” default, but could be used as an early warning system in conjunction with their established risk systems – If you have predictive criteria, you know when something’s going to happen before it happens and be better prepared.

The bottom line

Deep learning algorithms were once mythical beasts. Now they’re being applied in everything from helping gamers find the quickest routes to beat video games, all sorts of prediction work and filtering like Google Translate does, and in the finance/investment world to pinpoint events that may trigger positive or negative outcomes. Nothing in the world is widely adopted right off the bat—it takes years of perfecting and molding the technology to provide the greatest benefit to users. AI and machine learning are no exception.

Rob tends to think otherwise … and I will gladly wait to see how they do.


Rob has been in the financial services industry for almost 30 years. He started his career as a financial advisor and eventually moved to asset management, electronic trading, wealth management and clearing. Over his career, he has served in multiple executive positions such as; the vice president in the CIO Group at Penson Financial Services, as Chief Information Officer at 1st Global Research & Consulting, and as Principal Consultant for Wealth and Brokerage at Mphasis, a Blackstone Company.  Robert has experience managing, creating, innovating and implementing financial tools and services, which he has employed at InterGen Data to quickly scale and grow.

Robert Kirk, InterGen Data


Interviewed by Vasyl Soloshchuk, CEO and co-owner at INSART, FinTech engineering company. Vasyl is also the author of WealthTech Club, which conducts research into Fortune and Startup Robo-advisor and Wealth Management companies in terms of the technology ecosystem.

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