Predictive analytics and natural language generation (NLG) are used throughout the financial services today, but are used less frequently in the case of wealth management. Narrative Science and Yseop are two of the few NLG companies currently selling to wealth managers. IBM Customer Insight is bringing its cognitive Watson technology to the wealth management industry. IBM Customer Insight is doing cool things related to behavioral segmentation, encouraging wealth managers to create more robust customer profiles by casting their data net beyond customer income information. More in my blog post here.

There are many use cases for NLG and predictive analytics in wealth management. For example, predictive analytics can assist with risk management by spotting anomalies in real-time, and therefore, enable advisors to resolve issues faster. NLG can be used to transpose customer data into a short narrative that summarizes a client’s performance. This narrative could be shared in an email to the client or used by an advisor preparing for an in-person client meeting.

In my report, Coaching the Advisor: Predictive Analytics and NLG in Wealth Management, I focus on how predictive analytics and NLG solutions can enhance advisor-client relationships, the attributes of competitive analytic solutions, and propose best practices for the modern advisor. I stress the importance of advisors’ establishing genuine connections with their clients in the midst of adopting new analytic tools.

In the next 12 to 18 months, I anticipate wider adoption of these tools in the wealth management industry.