Transforming Client Lifecycle Management with AI-driven WealthTech

I recently moderated a panel discussion at the Automation and Innovation in Wealth Management conference in London. Featuring renowned industry experts James Howell, Director – Wealth Management Consulting at PwC, Janet Jones, Head of Industry Strategy – Financial Services at Microsoft and Ian Ewart, Board Member & CMO at Acin, we discussed how AI-driven technology is being used today throughout client lifecycle management. The panel prompted a range of questions from the audience around personalisation of services, better insights into client data and process efficiencies, and with such an interactive discussion I thought I would share some insights.

Is AI the future of wealth management?

Wealth management organisations today face a shifting landscape of opportunities and challenges. The industry is witnessing the biggest generational transfer of wealth in human history. But to take advantage, they need to handle a new breed of tech-savvy clients, whilst navigating unsure markets and fending off increased competition. In short, they need to maximise staff productivity and enhance the customer experience in order to drive success.

Technology lies at the heart of the opportunity here, which is why so many players are looking at what artificial intelligence (AI) and machine learning (ML) can do for them. With the right tools in place, and a close eye on data quality and governance, firms can reap major operational efficiencies and customer engagement benefits.

How is AI/ML being used?

At the heart of the machine learning value proposition is computers that access large data sets to automatically learn and improve over time, without the need for human involvement. As such, clever ML algorithms can be used to take over monotonous tasks usually completed by staff, freeing them to work on more high-value tasks. For example, you could get a ML program to deal with contract reading, clause analysis and grouping for regulatory change: a number of wealth managers are already doing this in LIBOR remediation to take the workload of paralegal teams.

The benefit of getting machines to do tasks like these is they can do them faster and more efficiently, and even uncover patterns in data that humans are not capable of seeing. For example, Microsoft worked with a client to build a model to surface their top 10 clients that are 10 times more likely to churn in three months’ time. The model was able not only to highlight these customers but also the potential financial outflow that could result, enabling the wealth manager to take action.

The key thing here is that such tools work in harmony with the wealth managers themselves. Think of them as a high-tech assistant rather than a replacement. So research projects could be accelerated by AI assistants that carry out the time-consuming initial stage of information processing. Human experts then focus on providing insights into the data that is selected for analysis.

Transforming customer service

AI tools can also drive major improvements to customer service. Part of this is because they’re able to take-on the repetitive admin tasks that can account for as much as 80% of a typical relationship manager’s day. Customer-facing AI chatbots can even be used to deal with the more routine enquiries that clients may have. They can be personalised to suit the brand and allow you to answer customer questions 24/7/365 while reducing operating costs. This all helps to free up your staff to hone their interpersonal skills and spend more time building relationships with their clients.

AI algorithms can also be used to trawl communications channels for sentiment analysis, alerting team members if clients are unhappy and suggesting possible actions. And they can be set to work analysing disparate market, core banking, portfolio management and other data sources to suggest product recommendations. Both these examples highlight how AI can make wealth managers more proactive, improving the service they offer customers whilst growing the business. 

A bright future

It’s great to see so many Proof of Concept (POC) projects taking place out there, although many organisations still find it difficult to scale these effectively, while organisational siloes and IT-business misalignment can add further challenges. In countries like the UK for example, there’s still cultural resistance to technology muscling in when so much business is done face-to-face.

Yet as we’ve discussed, the benefits speak for themselves. And those who have data security concerns should have their fears allayed by the fact that major public cloud providers now count governments and the military among their customers.

At Wealth Dynamix we used AI across our comprehensive client lifecycle management platform WDX1, to help our customers with everything from driving conversions to streamlining onboarding, enhancing compliance and improving relationship management. The tools are out there to transform how you do business. It’s up to you to use them.