Traditionally, advisors were only able to capture inputs directly from their clients. This information was often very subjective and relied heavily on the clients’ feelings about investing and risk. Fact-based questions were often limited to a small set of questions, such as time horizon and availability of assets.
Even still, these “facts” were vulnerable to clients’ feelings or opinions, leaving the advisor to build a portfolio on unstable ground. To complicate matters further, advisors had to conduct massive amounts of research through limited sources and rely on a team.
Following the initial consultation, advisors couldn’t be sure if and when clients’ financial data or life factors had changed. Not only did they have to depend on the clients to tell them, but they would sometimes find out months or years later—if they ever found out at all. In the instances advisors were provided updates by the clients, the new information could still be inaccurate or incomplete.
Luckily, today’s advisors have access to online portfolio risk assessment tools that can solve these problems. AI, paired with big data, can facilitate better insights about clients and ultimately improve portfolio management. It also democratizes the access of risk intelligence, as even smaller firms can retrieve data that was once only available to firms with larger teams.
As explained in “How Advisors Can Harness Data to Optimize Financial Planning,” by Think Advisor, this greatly improves the role of financial advisors: “The advancement of digital innovation and efficiency, driven by data, enables advisors to optimize financial plans by expediting the analysis of needs for clients and prospects—and add greater value with more accurate cost projections and well-informed recommendations.”
Big data consists of large volumes of information that would be impossible for a human to decipher and analyze. Businesses can use AI to weed through this mass amount of data to solve problems.
One way advisors can use this technology during client meetings is to provide immediate recommendations. In the Investopedia article “How AI is Shaping the Advisory Landscape,” the author explains: “As an example, an advisor could use AI during a client meeting to call up specific client information and model the performance of potential recommendations, a task that previously would have taken a team of analysts several hours or more.”
This is one of the main functions of the TIFIN Risk platform. Our cutting-edge algorithms navigate a large universe of data based on 11 simple client inputs that is also known as risk tolerance questionnaire and then instantly creates a fact-based analysis of risk.
This analysis also weighs other factors that can affect a clients’ risk profile. For example, our system can assess a client’s cost of living based on their zip code or use historical data to predict future income.
This type of technology can also be used to improve portfolio management beyond the initial meeting. Using an integrated platform allows the advisor to stay current on both client and industry data. It also ensures accuracy since the data is curated from facts rather than emotions.
Finance is an industry where data has a huge impact on efficiency and outcomes, which is why using AI and big data will continue to be crucial. As Joris Lochy states in his Finextra article, “As the financial services sector is probably the most data-intensive sector in the global economy, the impact of big data on the sector is hard to overestimate.”
