Financial services institutions have several options when it comes to improving the decision-making process for investors.
- Reduce options
Probably the least-attractive idea for many providers is the notion of limiting the number of options available to clients. Though there are many examples in the manufacturing industry where decreasing the total number of different products in a line actually increased the company’s total market share, it is somewhat more problematic to do in the financial services – there may be plan concerns (in the retirement services space) or liability concerns when it comes to deciding which of the funds to keep. The desire to reduce the number of options was also a primary driver in the development of “lifecycle funds,” but instead of limiting the total number of funds, these were just added to the list.
- Make the differences concrete
It’s significantly easier to make a decision when you understand the consequences. For example, two groups of new employees in a company are presented with the same enrollment materials for their company’s 401(k) plan. One group is asked to imagine how having more money in their savings would impact their lives. That group of individuals increased their participation in the plan by 20% more than those who were not, and the deferral amount also increased four percent. By showing a customer that one fund has a greater performance between the best- and worst-projected return, while another fund has a lower but more stable return, it allows the client to truly understand their options (i.e., risks/rewards) better.
- Use categorization
This approach has been employed in the financial services industry for quite some time, but perhaps not as effectively as it could be. Companies need to do a better job when it comes to structuring and designing categories, so that clients can understand the meaning behind them. What companies often lose sight of is that the categorizations need to be structured so that the investor understands the categorization, not the company asking for the choice. For example, fund providers have categorized fund groups with terms like “international funds,” “foreign funds,” and “specialized funds.” The average enrollee in a 401(k) plan may not understand the differences between them, nor how those differences could impact their retirement savings.
- Design your categorizations to condition for complexity
As mentioned earlier, categorizations have been used in financial services for a long time, but they often stop short. Take, for example, a 401(k) plan that has 80 funds categorized into five primary groups. Once a participant has chosen “high-risk/high-return,” they are presented with 15 funds, ranging from small cap funds to country-specific precious metal funds. At this point, the client is probably more confused than they were before making the previous decision and less likely to choose a fund.
Multiple levels of categorization can be supported as long as they are organized correctly. Studies have been conducted on websites in which auto dealerships let customers choose hundreds of options for customizing a car. When presented a series of six choices, each with a different number of options (e.g., one option having four choices and the most complex having over 50), customers were much more likely to complete the selection process if they started with the fewest number options and built it up to the most number options. So, how you construct the categories can be very important when it comes ensuring your client has as an effective and rewarding experience.
- Use guided automated interaction to facilitate understanding
Over the past several years, robo-advisers have become more and more prevalent and useful in helping customers make key investment decisions. The successful implementation of a robo-adviser is dependent on two key components. First, it needs to provide solid guidance and recommendations. Next, it needs to provide a simple and engaging user experience in order for clients to trust and adopt this method of communication. While many financial service companies have already begun to implement robo-advisers, others are leveraging machine learning, cognitive computing, and artificial intelligence (AI) to implement virtual agents that can provide much of the service traditional advisors have provided.
The piece above is an excerpt from a new guide, in which we discuss the issues that stem from offering clients too many choices, as well as several concrete steps that can be taken to address them. You can download it here.
