The promises of radical business transformation have driven the inexorable rise of artificial intelligence (AI) in the financial planning industry over recent years.
The idea of having a machine that can continually learn on its own and identify and solve complex problems in a nanosecond is extremely alluring. But, the reality is that machines that can think like humans, but with millions of times more brainpower, are some years away yet.
While no one has yet to hit on the ideal AI model for financial planning, there are still a number of key areas in which the current iterations of AI are of enormous benefit to the industry. A 2018 global survey of 2,135 businesses by McKinsey & Co revealed that within the financial services industry, the top three business functions using AI were service operations (49%), risk management (40%) and sales and marketing (33%).
AI can seem incredibly daunting to the uninitiated, not to mention the fear that it could put planners out of work. But in reality, the opportunities far outnumber the threats. AI can both enhance a financial advice business’ service offering and help it to grow. Love it or loathe it, you can’t ignore it. Do so and you’ll be left behind.
So, what are the benefits and challenges of AI for financial planners?
Benefits
Improved standard of client service
AI allows planners to spend more time servicing clients and adding to their value proposition by performing many of the mundane tasks that consume so much time. For example, AI applications can monitor client portfolios and send alerts when asset allocation changes or prices move outside of certain pre-set parameters
A planner might also use AI in client meetings to see various types of data and model potential outcomes of various investment options.
Cheaper and more efficient compliance function
AI allows planners to spend more time servicing clients and adding to their value proposition by performing many of the mundane tasks that consume so much time. For example, AI applications can monitor client portfolios and send alerts when asset allocation changes or prices move outside of certain pre-set parameters.
A planner might also use AI in client meetings to see various types of data and model potential outcomes of various investment options.
Cheaper and more efficient back-office function
AI can also improve efficiency in much of the back-office function. A number of fintechs are currently developing AI applications that can automate tasks such as compiling SOAs. At present they are best suited to the simpler SOAs and, even then, will generally require some human input.
The compliance function is another area where AI has huge potential for both planners and regulators, although it is still in the very early stages. As a licensee, I hope to see AI reduce compliance costs, which have blown out across the industry in recent years.
Lifespan is currently working with Kaplan on the development of its Red Marker Artemis software. Artemis uses AI to check compliance of written material with RG234.
The goal is to eventually be able to automatically run compliance checks on SOAs and other written representations as a starting point for humans to then use professional judgement on areas of concern. One of the challenges with supervision and monitoring is that 99% of what is reviewed is fine, however, AI can make zeroing in on the areas of concern much more efficient.
Nevertheless, having competent humans to then evaluate the possible risk and/or compliance breach and decide on a course of action is still critically important and I think we are a long way from having this replaced by AI.
- Chat bots to answer general advice queries.
- Fraud detection.
- Client database analytics, providing valuable insights.
- Algorithmic trading.
Effective way to reach Millenials
AI is potentially a good way to engage, or at least get a foot in the door with, the hard-to-reach under 40 demographic. Before you get too excited about the prospect of having a robot meet with your clients while you sit back and count the money, research shows that clients still value at least some face-to-face service from a human, even younger clients. A solution might be a combination of face-to-face service with AI taking care of the mundane back-office tasks.
This will undoubtedly change as AI becomes more intelligent, with greater deep learning/self-learning capabilities, and clients becoming more comfortable with technology handling their financial advice. Furthermore, with the industry professionalising and moving to a more user pays type structure, the cost of face to face advice is set to rise dramatically meaning that most consumers wont be able to access a live adviser and will have to settle for google or an AI for their advice.
Challenges
Don’t throw out the baby with the bathwater
It is important to remember that AI is just a tool to enhance your client value proposition. It is a long way from being a viable alternative to face-to-face service. Nevertheless, its transformative potential should not be ignored.
It should work away in the background, freeing you up to spend more time on the functions that add value for your clients.
There is a risk of putting the cart before the horse and focusing on AI for investment insights, for example, instead of using it to gain a deeper level of understanding of a client’s situation in order to deliver more tailored advice.
AI is still unable to present a truly end-to-end bespoke advice solution to clients. There are too many nuances to each client’s individual circumstances. It’s important not to be distracted by the latest gimmicks or to rely too heavily on the data rather than the individual.
Regulatory challenges
One of the more interesting aspects of AI is how the latest developments can draw the ire of regulators, given that governments can be sometimes slow to respond to technological innovations such as AI. Don’t forget that most regulations were written and put in place long before AI came along.
Having said that, I believe the fintech community is working closely with ASIC and the government to make the implementation of AI in the advice industry as smooth as possible, which could result in changes or carveouts to regulation to help facilitate growth in this space.
Given how rapidly technology evolves, fintech development will be difficult to keep up with from a regulatory point of view, especially when client demand for tech-driven tools is increasing.
ASIC’s guidance on providing digital product advice in RG255 is too broad and does not cover all of the issues that arise in interactions between robots and clients. New guidance will most likely need to be drafted to address AI where it interacts directly with clients.
Incompatibility of systems
There are still issues with compatibility of systems. No one has yet worked out a way for all the different applications to talk to one another and seamlessly integrate. Long standing providers of both advice and product solutions will continue to have to wrestle with legacy issues and old systems.
Client bases are also extremely diverse, with many older clients still wanting face-to-face appointments and information in writing. In any event, new technologies will give rise to new services, new systems and new product options.
New technology is generally the focus of younger demographics, both as providers of solutions and as end users of the technology. AI will soon have a central role to play in the financial services industry and advisers should be open minded and prepared to explore the benefits that these technologies will bring.
