The Covid-19 crisis has accelerated the digital transformation of many sectors: online grocery shopping, virtual tourism… The financial sector is no exception. This opens up new possibilities for wealth management, especially when it comes to hyper-personalisation. Indeed, this trend is growing rapidly in all sectors, driven by consumer demand.

New customer expectations

According to a study by Capgemini, 40% of high-net-worth individuals (HNWI) are not satisfied with their wealth management advisor. This is partly due to a demographic shift. Millennials represent a growing share of clients. In fact, in the next twenty-five years, HNWI will transfer $68,000 billion to them. This tech-savvy generation is used to receiving personalised recommendations – from Netflix suggesting movies they might enjoy to Amazon reminding them to reorder certain products…

These new clients, therefore, demand the same quality of service when it comes to managing their financial assets. They expect advisors to tailor their analysis to their specific needs. Something that an increasing number of startups have clocked on. For instance Nalo, a startup rated by Early Metrics, offers personalised life insurance policies. It offers each client a unique investment portfolio, based on their situation and projects (retirement income, future real estate purchase, children’s education, etc.).

Younger clients also want to build a portfolio that reflects their personal values and interests. For example, clients who care about social and environmental issues will be more satisfied if their advisor offers them ESG investments.

Real-time information 24/7

These clients also want access to educational content to better understand their portfolio. Mon Petit Placement, also rated by Early Metrics, sends personalised videos made by financial advisors to advise clients on their investments. This educational aspect aims to make investing more accessible to beginners.

Omnichannel communication is another key challenge as these customers have become accustomed to receiving regular notifications. They want to be able to track the performance of their investments from any connected device. Hyper-personalisation allows companies to send them highly contextualised messages and information, at the right place and time, using the right channel.

Wealth management players are aware of these new consumer expectations. According to an Objectway survey, four out of ten players have already implemented a hyper-personalisation strategy for portfolio creation.

Hyper-personalisation as a competitive advantage

Hyper-personalisation is also a way to deal with increased competition. More and more fintechs and tech giants are entering the wealth management space. These players are familiar with data analytics and AI technologies, which enable hyper-personalisation. Although they are newcomers to this market, they benefit from significant technological advantages.

Hyper-personalisation allows for the generation of custom risk profiles. Traditionally, wealth managers categorised their clients into pre-defined risk profiles. However, this method does not take into account the particularities of each individual. Thanks to behavioural science and sentiment analysis, it is now possible to define the risk profile of each client more comprehensively.

These startups disrupting the wealth management sector are attracting both customers and investors. Wealthtech startups raised a total of $3.7 billion in 2020. To protect their market share, traditional wealth management players must step up their game and adopt new strategies. Hyper-personalisation will allow them to retain their existing clients, but also acquire new ones. In 2019, Temenos and Forbes Insights surveyed wealth managers about emerging technologies. The majority of participants believe that wealth managers who are adept at technology (84%) and increase the personalisation of products (82%) are more likely to succeed.

A wealth of data making hyper-personalisation a reality

Consumer data is a valuable and strategic resource and as such is often described as the “new oil” of the 21st century. It allows for improvements throughout the customer journey (personalised landing pages, dynamic pricing…). In fact, more and more customers are willing to share personal data to receive personalised offers in the financial sector.

However, collecting large volumes of data is not enough. Wealth managers need new, relevant technologies to analyse and leverage this data. AI and machine learning technologies process this data faster and more efficiently than a human. Among Early Metrics’ database of rated startups, Mieuxplacer.com offers a solution called Lucy that relies heavily on its AI technology. Customers complete an online questionnaire about their projects, situation and experience as a saver. Lucy then analyses more than 500,000 combinations in less than 10 seconds to select the contract best-suited to the customer.

The rise of open banking has made these processes easier. There are now many APIs that allow for the collection of data from various sources. The aggregation of these sources offers a more accurate and reliable analysis. For example, Lucy tracks the performance of all investment funds in real-time. It also provides up-to-date analysis, 24/7.

Finally, advances in technology are enabling wealth managers to offer personalised services while optimising their costs. The US-based bank Morgan Stanley has developed the Next Best Action (NBA) system, which generates hyper-personalised recommendations that advisors can present to their clients. The system can generate a personalised investment idea almost instantly, instead of 45 minutes previously.

Obstacles to hyper-personalisation

Nonetheless, wealth managers face several challenges that can hinder the hyper-personalisation of their offer. As we have seen, this trend relies heavily on data collection and analysis. Advisors must therefore obtain personal information about the client such as their personality traits, values, beliefs, behavioural and transactional habits… But obtaining such detailed and personal information can be difficult. This data challenge applies to all clients, from small individual investors to high-net-worth clients.

Moreover, personal data is subject to increasingly stringent regulations. In Europe, the General Data Protection Regulation (GDPR) limits the use of personal data. Data must be collected for a specific purpose, clearly stated at the beginning of the process. Once it achieves this purpose, the company must delete the information it no longer needs.

In addition, not all wealth managers have the means to leverage their data. Data is sometimes kept in silos by several departments. In this case, consolidating and standardising data can be a struggle. While AI has great potential, its application to wealth management is still in its infancy. Algorithms need to be trained for a long time before they provide reliable and relevant analysis.

While it was once reserved for the wealthy, hyper-personalisation is now gaining ground in wealth management for all. As they face growing competition from new fintech players, incumbent banks are starting to deploy AI and data analysis technologies. They hope to attract new customers, especially younger ones. Soon, customers will expect highly personalised services as a given. Hence, wealth managers must invest in these solutions now or else they might end up on the sidelines.