More than half of wealth managers are working on a “hyper-personalisation” strategy, saying this would represent the future of customer engagement post-Covid.
A survey of 48 firms by digital wealth and asset management software Objectway found that hyper-personalisation is becoming a top priority for wealth managers in their digital agenda.
Four out of 10 respondents said they were implementing hyper-personalised portfolio construction and product recommendations, where artificial intelligence, data analytics and machine learning are used to create personalised proposals.
For a third of the surveyed panel hyper-personalisation of investment proposals was the main goal, others included bespoke financial planning (18 per cent), risk profiling (18 per cent), and reporting (16 per cent).
Other respondents said the use of it was to maximise revenues (5 per cent), reduce customer acquisition costs (4 per cent) and automate work processes (4 per cent).
Objectway said this highlighted that using technology to analyse client behaviour could assist in providing well-rounded tailored advice on investment decisions.
But there is more work to be done as the industry is far from a data-driven culture, said Alberto Cuccu, chief executive officer at Objectway.
He said: “To hyper-personalise the client experience, investors' information and preferences should be captured at all touch points of the client journey.
“Almost half of respondents argue that the use of hyper-personalisation is essentially aimed at elevating customer experience and consequently to gain a competitive advantage. So far, the wealth management industry has still to work on it."
Respondents told the firm that financial advice and reporting were usually data-driven, but the information used for this purpose was generally limited.
Objectway stated that best practices would require all available data, including extra-corporate and unstructured items, subjecting it to the most advanced data science.
The report titled 'Are you developing a hyper-personalised strategy?' found that given the best practice scenario, a mere 25 per cent of interviewees thought they could effectively use behavioural sciences and sentiment analysis to personalise their client experience, and most would like to see additional support.
The firm said to achieve this goal, "artificial intelligence, machine learning and analytics are not enough", a data-driven culture with effective data management programs was needed.
Last year Greg Davies, the head of behavioural finance at Oxford Risk, told FTAdviser standard suitability processes were "extremely ill-equipped" and the current situation would require "hyper personalised" communication.
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