By Jayne Brown and Richard Shearwood, consultants at Simplify Consulting
Artificial Intelligence (AI) is being adopted across a wide breadth of industries where processes are enhanced using technology, replacing humans in full or in part.
Increased efficiency, reduction of errors, improved risk environment and enabling humans to focus on more value-add tasks are just some of the key benefits of using AI.
In wealth management, the advice journey is highly regulated, and rightly so. But this comes at a cost to the advice firm and adviser, who must ensure that they are always compliant.
What are the challenges around the advice process and how with the support of this technology could it evolve, to reduce some of the extensive administrative overheads that we see today and give the customer the face-to-face contact we know that they desire?
The advice journey today
The advice process has been subjected to additional regulatory scrutiny, with some hefty fines served for those that don’t meet the standards. In December 2022, the Financial Conduct Authority (FCA) fined Pembrokeshire Mortgage Centre £2.4million for giving unsuitable advice in relation to defined benefit pension scheme transfers.
There are also plenty of examples of firms having multiple claims against them at the Financial Services Compensation Scheme (FSCS), which has declared those firms to have defaulted.
Suitability is a key part of the advice process. Not only does it take a large amount of time and effort, it also attracts complaints to the Financial Ombudsman Service (FOS). Advisers can be criticised for not taking the right steps to ensure the advice given was suitable. They are required to ensure the advice is sufficiently aligned to the customer’s circumstances and that any information given about a product or investment is clear.
All complaints are investigated using evidence captured around the advice, so there is a responsibility for the advice firm to ensure that the reasons for a recommendation are clearly defined.
How can technology help?
Technology to support the advice process has made some advances, but more needs to be done as it does remain a highly manual process with integration struggles between adviser back-office systems and some platform providers. The benefits of reviewing the advice journey with AI-enabled assistants working alongside advisers are:
● Increased efficiency – AI ‘Assistants’ can listen in to conversations between the adviser and the client, document notes and track the capture of important information. The AI tool can parse huge amounts of data to find the best product or solution that best fits the clients wants, needs and risk appetite. It can identify products to the adviser to put forward as a recommendation.
● Reduction of errors – The ‘Assistant’ can notify the adviser in real time any alerts they should be aware of, missing data, anomalies in the data, red flags or controls that need some
specific attention. By learning from previous experiences, and how those red flags are dealt with, the assistant can build up its intelligence of the requirements in different advice meetings.
● Improved risk environment – AI assistants can act as a control in the advice process by comparing against historical advice given to clients in a similar segment with similar objectives. It can then highlight where there could be issues with recommendations.
The future
There is always a place for the adviser, and we don’t expect this type of assistant to have the capability to replace the adviser. Nor should it. It has become clear with the failure of many robo-advice products, people don’t want advisers to be replaced by automation.
Technology used in this way allows the adviser to spend more time focussed on building client relationships and trust, while also speeding up the process to reduce the administrative burden. Real-time analysis also helps to reduce the risk in the advice process.
Advisers, whether independent or restricted, who fully take advantage of the technology available to them will reap the benefits of reduced administrative overheads, reduction in data inaccuracies/rework, stronger relationships with their clients and minimised risk of mis-selling claims in the future.
