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The Data-Driven Wealth Manager: AI’s Insights into Client Retention
Artificial Intelligence: Love it or Loathe it, it’s Here to Stay
With all the media coverage and sensational headlines, you’d be forgiven for thinking AI burst into the zeitgeist overnight. AI has been around for a while. The first chatbot was created in 1966 by MIT Professor Joseph Weizenbaum. Since then, AI has been embraced by a range of industries to underpin their daily operations.
Thanks to OpenAI’s ChatGPT, which launched in 2022, AI tools are now widely (and in many cases, freely) available, which has forced a reckoning among top companies about how they leverage AI in their organisations.
But the benefits of effective AI integration, specifically AI in wealth management, are only just being realised. A 2022 Accenture report found that 9 out of 10 advisers surveyed believe AI can help grow their book of business by more than 20%.
But before wealth management firms rush to use AI to draw in new clients, it’s important first to understand AI’s potential in identifying and reducing customer churn.
Wealth Managers and the Battle for Client Retention
For Wealth Managers, customer churn can take several forms. A client may decide to:
- Switch to a different wealth manager within the same firm.
- Move to a competitor wealth management firm.
- Independently manage their own wealth investment decisions.
In private banking, typical churn rates are estimated to be around 1-7%, according to a report by TCG Digital. While that might not sound too alarming, wealth management clients tend to be high-value customers, with a substantial amount of investable assets. Herein lies the problem. Even a small churn rate can translate to significant losses in managed money for the firm.
Client retention should be a vital component of a firm’s strategy, as customer acquisition costs (CAC) continue to rise. In the wealth management market, the CAC is estimated to be just over £1,700 per client, rising to over £3,250 per client for firms with more than £200,000 in revenue.
AI in Wealth Management: How Does it Work?
When used effectively, AI can be a powerful tool for firms looking to deliver a hyper-personalised client experience. With AI, advisers can collate and analyse vast amounts of data relating to their client’s finances, risk tolerance levels, and communication preferences, allowing them to deliver more tailored investment strategies and product recommendations that suit their client’s unique needs and goals.
A more personal and holistic approach undoubtedly strengthens client relationships and therefore lowers churn rate, but AI enables firms to do this at scale, making it a more sustainable long-term strategy. With this predictive model, firms can prioritise their outreach, optimise retention strategies, and keep costs low.
Just Like Rome, Your AI Strategy Shouldn’t Be Built in a Day
Like all good ideas, it’s the execution that’s make or break. For effective AI implementation, firms must have a streamlined, ethical, and robust AI policy. Employees need to be clear on what AI can and cannot be used for. Will the data be used to train the model? Is the firm using a closed AI model? What are the risks posed by open AI? Are AI-created materials for internal use only? These questions require definitive answers. Ultimately, if a client is talking to an AI chatbot, it must be disclosed.
Effective AI use is a balancing act between automation and human touch. As AI adoption increases, it mustn’t be overused or unnecessarily deployed. While AI can help develop more personalised strategies, it’s wealth management firms who will ultimately add that personal touch that clients respond to. In short, leave AI to get on with what it’s good at – automation, data synthesis, time-consuming admin – and leave the wealth managers to deliver a much-needed personal touch.
To find out more about the role of AI in Wealth Management, head to Morningstar Intelligence Engine and meet MO, your personal digital research assistant. Built on 5 core principles – ethical, secure, trustworthy, transparent, and accountable – MO leverages the depth and breadth of Morningstar’s data and research insights to surface the information wealth managers need to deliver a high-quality, personalised client experience.
Joshua McAlpine
Content Writer, Marketing, EMEA, Morningstar
