The new focus on risk assessment

When the company decided to shift their focus to calculating risk, the first thing they did was research questionnaires being offered by financial institutions. They visited the institutions’ websites and took their questionnaires. The result were all over the board, but one thing was consistent… all of the questionnaires calculated how much risk a person wanted to take with no questions about their current life situation. Larry says:

“Even with 20 years of industry experience, I could not figure out the reasoning behind some of their questions… So if I’m an investor filling out this questionnaire, (1) it’s based on my preference in that exact moment in time, (2) some of the questions were not clear, so I guessed at about 30% of the answers. In the end, the score is not even close to what it should be because it was based on feelings, not facts.”

The company saw that this not only confused investors, but also created problems for advisors when they tried to explain risk scores to them, so Totum set out to create a product that analyzed the risk capacity of a client’s current life situation, not just their preferences.

“Academically, we found out that every person or household has on average of one major life event annually, whether positive or negative, that will affect their overall investment objective.”

This was the “aha” moment for them. Today, Totum Risk has deep, quantitative academic models and algorithms based on hundreds of variables on the backend. However, the company was able to make the front end simple, easy, and relatable for both the advisor and investor.

“We’re asking questions about their health. What’s their zip code? Do they own property? What sector do they work in? Our client interface makes it very easy to complete the front end.”

The system processes this information to reveal the potential downside that the investors would be comfortable with and the amount of risk they’re willing to take over a 12-month period.

Sources used to obtain robust data

Through Artificial Intelligence, blockchain technology, and accredited research data companies, Totum’s models and algorithms integrate data such as zip code analytics, statistical data for metropolitan areas (e.g., gross domestic product, cost of living, median income), and the investor’s net worth into their scores.

The company has an open API and currently integrates with other third-party vendors such as Black Diamond, Advison, and Emoney. According to Larry, the platform is pulling and pushing data through APIs to seamlessly communicate with other systems and to update data.

Totum is in discussions with some firms that focus on population analytics to potentially use their data to fill in the gaps in their in-depth data analysis.

“IBM has been a huge help in this space. They have another area that they call MetroPulse which has a lot of data.”