Of course, this digital transformation by its very nature must include the everyday business of servicing clients. This digitalisation shift has allowed for the unearthing and vast explosion of newly-available client data - voluminous information that is being digitised for secure and long-term storage, and for facilitating greater insights.
We believe that data is king. It has become the single most important element for allowing businesses to genuinely understand their clientele and best discern their unique needs and wants. Furthermore, analysis of data allows for companies to make more informed decisions about where to deploy revenues to drive company growth and/or expansion, what new competitive strategies to undertake, and which well-intentioned but faltering initiatives to abandon.
Data, data everywhere
The real question businesses are facing is: how to collect all of that critical but often scattered client data? That’s of particular importance where different business units within a single investment management firm possess a fraction of the entire dataset available for each. How can all of that internal data (including meeting notes, emails, CRM data and more) be integrated with external client data, and then converted into highly actionable intelligence? Armed with an abundance of properly culled, categorised and sorted data, asset management firms can utilise this for superior client interactions, enhanced levels of relationship management and servicing, and fostering loyalty.
As an asset/investment/portfolio manager, do you know each of your institutional clients; really know each client? Do you have enough data for a full and complete, holistic profile that can be created to best reflect all aspects of each client? Of course, that must include the basics like historical and current portfolio allocations, favored and disliked investment strategies and preferred geographic markets, performance goals, time horizons, risk profile and tolerance, investment mandates and restrictions, etc. But, do you also have the ability to easily review a client’s past behavior, such as how that client reacted to the latest market disruption event, the most recent recession, the abundance of bad news emanating from a particular sector/global market? That must all be combined to allow for a true understanding of the client.
What’s more, can you quickly access all of that data about each client within a centralised, attractive and easy-to-understand dashboard view? Dashboards are becoming the must-have digital technology that allows users to get a more informed and centralised view. Development of visually appealing dashboards that can showcase all critical information in a single viewer is becoming the de facto technology. Dashboards have been greatly enabled through the use of enhanced user experience design techniques, data analysis and cutting-edge machine learning tools.
Smartly leveraging data
Once a highly-structured 360-degree view of a customer can be developed - including behavioral insights based upon notable past and current behaviors and reactions to market-led and other events - asset management companies are setting the stage for enhanced client engagements. Based upon this data, and with the help of emerging data science tools such as predictive analytics models, relationship managers can be better prepared to understand and predict how clients will react in the future and which new products and services they may most positively respond to.
Although managers are well aware that ‘past performance is not an indicator of future results’, predictive analytic tools can help give managers a first-strike advantage. When a disruptive market event occurs, armed with the full and concise data-based profile of a customer a relationship manager, for example, can contact the most predictably reactionary clients first and begin discussions early. In addition, having deep and immediate insights into each customer’s needs, strategies and past behavior, managers can offer alternative investments or customised strategies that will specifically suit each client.
Advances in today’s data science-led techniques have also facilitated the ability to develop an individualised “score” that exquisitely reflects each customer’s nuanced portfolio management desires and needs. In parallel, firms can also develop metrics for each individual product, strategy and service they offer, then compare the generated numeric value for each of these to match, recommend and then predict which customers are most likely to accept these, based upon similar characteristic-derived scores. The goal is to shorten the marketing cycle and improve the hit-ratio and ROI.
In the end, it’s all about the optimal collection and utilisation of data that can drive a financial services firm to greater success.