Investment managers face many more challenges than they used to. Fortunately, they have never had so many opportunities to seize. Digital disruption has presented the buy-side with many possibilities, both large, established asset management (AM) firms and smaller, more nimble wealth or money managers. Innovating with the latest AI-enabled analytics solutions allows agile buy-side firms to develop a fearsome, knowledge-based weapon that can win business from less ingenious competitors. Thoughtful application of this emerging technology can help to lock in a profitable client base and capture additional market share.
Recent numbers from the “big 4” consulting firms show that investment managers implementing even modest digital advances can yield significant business benefits. Efficiency improvements of 10-15% can be realized even while increasing revenues by 5%. Such gains can be also achieved in a very short period of time – typically less than a year. These numbers hint at the huge potential for investment firms who are willing to reassess their processes, delivery channels, and technological capability and move towards a more customer-focused model.
While marginal process improvements are always welcome and help to reduce costs, the primary goal for any AM firm is to deliver the performance and service that keeps clients happy. A high retention rate due to happier clients results in greater money inflow to investment funds… and therefore more fees for the investment manager.
The value of relationships
Early adopters need to balance traditional, relationship-led asset and wealth management with simple-to-use digital products, services, and powerful internal guidance and reporting systems. The focus is on delivering superior customer services and bringing down attrition rates – the dreaded customer churn.
The pivotal point for customer experience among AMs is the quality of the relationship and depth of trust between an investment manager and her clients. Any high net worth individual who feels genuinely taken care of by his wealth management firm has little reason to take his business elsewhere. One who is extremely happy with his money manager might even tell his close friends, introducing more business that generates additional capital inflow and additional fees for the wealth manager.
One way for a typical, performance-focused buy-side firm to become more customer centric is to offer clients the latest communication tools and richer, even interactive investment reporting. This goes hand in hand with the digitalization trend; innovative firms know that taking a more informative approach can show positive client retention results. Nevertheless, offering online chat access to fund managers or delivering beautiful performance graphics on your client’s iPad is unlikely to be a decisive factor for staying with your wealth manager. Any advantage that exists today will dissipate when these practices become the norm. As digital disruption takes hold, benefitting from the trend means going a step further and using technology to more effectively understand a client’s needs and aversions. It’s this sort of insight that can double client retention rates.
Capturing every nuance
The next generation, customer-centric business model is one that leverages the analytics power of artificial intelligence (AI). Imagine having the support of a machine that can review all the emails, phone calls, chat messages that flow between the business and every customer – an oracle that makes sense of all communication taking place between an asset or wealth manager and his or her clients. This machine can cut through the volume, unify interactions spread across multiple channels, and understand who’s talking to who, about what, and in what context.
This automated, yet finely drawn analysis is now possible thanks to AI-driven software. Some buy-side firms are already piloting this technology, using it to flag up any expression of client aversion to any kind of topic. What would otherwise be a complex, disparate, even inaccessible assortment of information can now be delivered to an AM firm’s managers as an instantly comprehensible heat map of dissatisfaction.
Typical complaint areas in the investment sector are mostly related to financial performance, tailor-made investment propositions, relationship management, and research quality. AI can significantly alter performance in all of them by unlocking insights that would otherwise be hidden by the scale and unavoidable variability of human communications data. By accurately recognizing the early, often nuanced signs of dissatisfaction, firms leveraging AI-enabled analytics can see both a comprehensive picture and drill down into the detailed specifics.
Let’s take the example of a tailor-made investment product, one of the main differentiators for any wealth manager. Even though such products are labelled “tailor-made”, they are usually replicated to some degree for other clients. The AI analytics I’ve described will enable management to gain immediate feedback from across the group of clients using the related products, showing their aversion to particular investments. Armed with this information, management can react and ensure clients are offered more attractive solutions.
An objective approach
This data-driven approach is a substantial improvement on the subjective way that satisfaction insights are gathered within most firms today. A relationship manager will deliver internal reports of their client’s views and suggestions. The all-important interactions containing complaints are easily altered as they are transmitted, clouding diluting a client’s real concerns or intentions, or sometimes plain forgetting to include negative remarks.
Applying AI ensures all complaints are looked at in an objective light. There are no hurt feelings or politics involved. The software delivers pure client intelligence without any emotional filter. Tracking complaints and negative remarks over time allows norms to be understood, improved, and deviations from them more quickly alerted and rectified. Dissatisfaction related to particular entities – a product, an investment, a member of staff – can be mapped by business areas. Those subject to higher levels of dissatisfaction are revealed immediately, plus there is insight on what type of improvement needs to be made.
Managing the buy-side with AI insights
Firms that adopt the proactive, informed and considerate style of customer service that AI makes possible will ensure individual unhappy clients are given appropriate attention and support. More significantly in terms of business impact, complaints data can be used to better manage the business and trends over time will show the success of each change. The information could be articulated as performance targets to teams in parts of the business that don’t normally interact with client, fomenting a more direct relationship between their work and the clients it serves.
While much is currently being made about AI taking jobs in financial services, the traditional wealth manager and client relationship is likely to continue to emphasize a close human contact. Here, AI will play a valuable support role, significantly improving quality of service and trust. These factors are key to satisfaction, retention and, given time, the underlying attractiveness of an AM firm to new clients. For the agile investment manager, the outcome of AI should be a lot more business.
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