Rewind to the mid/late nineties, when data was a grievance for many financial institutions. Poor organisation, inconsistency, inaccuracy, and having too much data were cited as reasons for not putting it to good use.
For the most-part data quality has improved dramatically since then, but with the quantity of data increasing exponentially, how can wealth managers use data to achieve profitable outcomes?
Today, 45% of wealth managers say that financial guidance from data analysis—and insights from the use of AI—will help them refine the advice they give to clients, according a Forbes study. And according to a recent Hubbis report, building a greater understanding of clients is the #1 priority for relationship managers. From the very first touchpoint, it must be quick and easy for relationship managers to collect client data automatically, to fuel data-driven insights.
5 key ways to use data to create loyalty
In a recent webinar, Antony Bream, Managing Director – EMEA and Americas at Wealth Dynamix, and Jonathan Drechsler, Head of Sales and Partnerships at Recordsure, discussed the following critical factors:
- Aggregate data to identify next best actions
With huge data sets being collected every day, and retained in many different systems, you must be able to aggregate this data automatically and analyse it in context, to determine next best steps that support every client’s onward journey.If a client is displaying negative sentiments, lack of confidence or has lodged a complaint, their relationship manager must be able to review all previous interactions quickly and easily, to identify the underlying cause. How many interactions have occurred in recent months? What is their preferred channel of communication? Which products have they expressed interest in, and what was the outcome? With instant access to all such data you will know how to respond, overcome objections and reduce churn.
- Digitise client activity to detect significant trends
The vast majority of interactions can now be digitised, enabling wealth managers to identify trends and formulate effective responses. Speech analytics, AI and NLP enable advanced analysis of face-to-face, online and telephonic interactions, which can be combined to create insights that all stakeholders can benefit from. For example, supervisors can analyse client experience across the entire business, and assess the ability of individual advisors to satisfy client requirements, which may influence action plans and training requirements moving forwards.
- Use granular segmentation to nurture emotionally connected client relationships
Segmentation only by age, gender and location is no longer sufficient. Research from Motista shows that emotionally connected clients (versus those that are only ‘satisfied’) can generate double the recommendations, a six-fold increase in AUM growth, and significant reduction in client churn.Emotional connections result from highly-granular segmentation and continuous sentiment analysis. Relationship managers must be able to gauge every aspect of client engagement that influences client sentiment – from routine processing of address or beneficiary changes, through to impactful shifts in attitude to risk due to market volatility.
- Present data in a meaningful form
The 2019 Capgemini World Wealth Report investigated ‘compatibility’, and coined the KBTK (Know Before They Know) acronym. Key to KBTK is a 360-view of the client, which enables relationship managers to quickly assess client interactions in an actionable form. Underpinning this requirement is the ability to finely slice data into a granular form that provides early indication of issues and desires, based on language and tone of voice used.As an example, was the client’s sentiment pre-COVID? What are they saying now, are they anxious or sanguine? Should you respond by contacting them regularly to reduce fear, or reporting periodically to provide reassurance? With early insights, accessed via easy-to-interpret dashboards, the relationship manager is fully-equipped to take next best actions.
- Derive greater value from data to drive return on investment
Client service aside, wealth managers are seeking cost-savings post-COVID. By automating the process of capturing, analysing and presenting client data in a meaningful form, as outlined above, relationship managers are enjoying 60-80% time savings, compared with performing the same work manually.
Now, more than ever before, relationship managers must equip themselves to get early insights into clients’ wants and needs, so they can build long-lasting relationships. Churn will be a fundamental measure of success post-COVID. With data in place there are no technological reasons to restrict the analysis and insight needed to ensure AUM growth, and emotionally connect with clients for the long term.