It's becoming more common to hear about artificial intelligence shaking up traditional and technology sectors, creating efficiencies and productivity, and financial advice is no exception.
What often slips under the radar are the everyday, less glamorous repetitive tasks that keep advisers buried in paperwork rather than engaging with their clients.
If we think that at the heart of financial advising, tasks such as KYC (know your client) fact-finding, suitability report generation, and routine client communications are crucial yet often thanklessly repetitive, leading many to view them as the necessary humdrum, boring stuff.
The irony lies in the fact that these tasks, while mundane, form the backbone of client service quality and compliance – two pillars upon which the reputation of a financial adviser and their firm stands.
These are the bits that don't get talked about at the lunches or the away conferences.
Hence, the question on many advisers' minds and the industry as a whole is: how can advisers navigate these tasks efficiently without compromising on service quality or falling afoul of regulatory requirements?
Freeing up the humdrum
This is precisely where AI and especially generative AI can hold the potential to make a significant impact.
Now, imagine as an adviser freeing up hours every week because an AI system is smartly navigating through files, drawing insights, writing reports and even answering basic client queries.
Prior to November 2022 and the release of OpenAI's first version of ChatGPT, this was seen as the distant future. However, since the GenAI phenomenon and the flurry of releases from companies like Microsoft, Google, Meta, Anthropic and Mistral, to name just a few, this imaginary view is now very much within reach.
The advent of GenAI has made it possible that AI systems can generate comprehensive reports, distil complex market data into actionable insights, and provide channels for client engagement.
This is where the conundrum for most financial advisers and wealth managers lies, especially when trying to introduce AI systems or AI tools – most of which have not been specifically built for the financial industry.
When you picture a financial adviser's day, you might imagine nice lunches, high-stakes decision-making, complex strategy planning, and in-depth client consultations. However, a significant portion of their day often gets bogged down with tasks that are anything but glamorous.
If we are of the view that the beauty of AI lies in its ability to handle routine and often repetitive tasks with ease, then by nature implementing such AI systems would potentially allow advisers to focus on what they do best: offering bespoke advice and building deeper relationships with their clients.
Who's to blame if it all goes wrong?
However, like with many things regulatory and in the financial services industry, we need to add a caveat: 'It's not as simple as that'.
Introducing AI into the mix brings its own set of challenges, particularly around regulatory compliance and the thorny issue of liability, especially when technology-driven decisions go awry.
