As this industry becomes increasingly competitive, personalised and cost-conscious, however, more efficient tools are needed to ensure businesses remain relevant.
Outdated, manual processes can place a drain on resources that could otherwise be freed up to focus on higher value and greater impact work – such as providing more personalised advice for existing clients.
This is where tech-first solutions, built upon data science, analytics and machine learning, can help.
‘Reading’ data is key
When it comes to winning new business in a highly competitive industry, sourcing prospects that need and want exactly what a business offers can be time-consuming and challenging.
Non-systematic, cumbersome methods – that can only produce an unqualified list of individuals with limited data points, that needs to be researched, qualified, and understood manually – are neither cost nor time effective.
This can also reduce the time spent on nurturing relationships with existing clients.
Some of the challenges can be solved by purchasing large, GDPR-compliant data sets from a third party that matches the target audience – for example, ‘HNWs over 40’.
This data can be used to demonstrate ‘real life’ viability, but it is only valuable if businesses invest in tools and platforms that can ingest, digest and intelligently use it to serve business objectives.
Investing in a dashboard that can present large data sets in a usable format, that is tailored to specific needs and usage, is a good first step to achieve this.
Once the data has become ‘readable’, the application of data analytics, AI and machine learning to create a sophisticated rules engine can be used to prioritise prospects by matching profiles to existing clients.
By utilising behavioural traits of current clients, securities characteristics and other internal rules specific to each business, wealth managers can deploy effective technology that filters out the prospects with a low likelihood of conversion, to prioritise those most likely to convert.
This enables managers and advisers to utilise their time and resources more efficiently.
Converting prospects into clients is a match-making task
Knowing who is likely to convert from prospect to client ensures valuable distribution of time and resources for prospect sourcing, but a secondary push is required to increase the likelihood of conversion.
Wealth management and financial advice are as much about money management as they are about maintaining good relationships with clients; as with any relationship, you need to establish and maintain trust for the partnership to flourish.
Provided the product matches consumer need, the deciding factor for prospects often boils down to trust and chemistry.
Technological solutions that leverage machine learning and data science can be applied to help ensure these human connections are formed, paving the way for establishing trust and therefore increasing the likelihood of conversion.
This occurs by ‘teaching’ an application to ‘read’ the underlying data of prospects, and match prospective clients to an appropriate manager based on their behavioural profile.
Much like a dating website, this tech-enabled match-making tool essentially lays the groundwork for managers to establish trust with prospects.
This same underlying technology can be leveraged for existing clients too, to implement personalised investment strategies based on attributes such as risk appetite, ESG requirements or geographical specifications.
To take this a level further, it can also be deployed to recognise and actively manage potential suitability conflicts, unwarranted recommendations, and unsuitable investments, by feeding back and leveraging historical data from within the firm.
All of this serves to ensure managers and advisers gain a head start in building and maintaining relationships with new, existing and potential clients.
The challenge of implementation
If these techniques ensure competitive edge then, why are they not being deployed by every wealth manager and IFA?
For one, implementation can require some initial cost and time commitment, which may put businesses off.
However, this should be considered an investment to remain relevant, competitive, and continue to win new clients. Any resources lost in the implementation phase will be gained back through a more effective prospecting process.
The industry also still has some catching up to do, in terms of realising the potential (not harm) of leveraging technology to support higher-impact human work.
Fortunately, wealth managers and advisers have never been in a better position to adopt machine learning, data science and analytics to enhance both lead generation and conversion.
It is simply a matter of finding the best partner to go on this journey with you.
This article was written for International Adviser by Ravnit Kohli, senior director of technology at digital, business consulting & technology services provider Synechron.