Rise of the machines: AI for financial planners

Rise of the Machines: AI for Financial Planners

The promises of business transformation have driven the inexorable rise of artificial intelligence (AI) in the financial planning industry over recent years. However, no one is yet to hit on the ideal AI model for financial planning.

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.

According to American AI expert, Andrew Ng, almost all of the economic value created by AI to date is through one type of technology.

“[It] learns inputs, outputs, or maybe A-to-B mappings, such as you might input an email, telling you it’s spam or not. For speech recognition, you input an audio clip and output a text transcript. For machine translation, input an English sentence, output a Chinese sentence. For a self-driving car, input a picture of what’s in front of your car and your radar readings and output the position of the other cars,” he said.

Nevertheless, there are still a number of key areas of financial planning in which the current iterations of AI are of enormous benefit. A 2018 global survey of 2,135 businesses by McKinsey&Co revealed that within the financial services industry, the top three business functions utilising 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 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 montoring is that 99% of what is reviewed is fine, however to be able to find the 1% that can cause problems if not picked up, you cannot get around this and I believe that AI can make the zeroing in on the areas of concern much more efficient. Having competent humans to then evaluate the possible risk and/or compliance breach and decide on a course of action with then be important and I think we are a long way from this being replaced by AI. Other applications for AI in the financial advice industry include:

  • 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. 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.

A number of companies overseas are claiming they can provide end-to-end financial advice through an AI portal for US$10 a month. But this service still only places clients in one of 10 investment profiles and does not cater for the multitude of personal life events that often give cause to change in a client’s daily life. 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 rathger than the individual.

Regulatory challenges

Eugene/Alan – could you please write few sentences on this one? You may want to leave it out entirely. I understand if you don’t want to be critical of ASIC.

One of the more interesting points is how the latest developments may “butt heads” with the regulators, given that governments can besometimes slow to respond to the pace of technological change including the rapidly developing AI space. 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 it as smooth a transition as possible which could result in possible changes or careveouts to regulation to help facilitate this growing space.

Given how rapidly technology evolves, Fintech development will be difficult to keep up with from a regulatory point of view, especially when clients will drive much of demand in this space and most have little time for anything that prevents the use of technology to access many services.

RG255 is too broad and does not cover all of the issues that arise in interactions between robots and clients, therefore new guidance will most likely need to be written to address AI where it interacts directly with clients.

Not implementing AI could be damaging in the long term

There are a lot of unrealistic expectations and a lack of knowledge around AI among financial advisers. AI can seem overwhelming for many planners, and they might be tempted to avoid it completely as a result; like the ostrich sticking its head in the sand. The AI space is still in its infancy in financial advice, so you don’t need to run out immedialtely and sign up to an AI system tomorrow, however you should be keeping an eye on this space. But allowing your business to fall behind in the implementation of AI can make it harder to catch up when its utilisation becomes absolutely necessary.

Not embracing AI can also create the perception among clients that you are resistant to change in general. For example, clients might begin to wonder whether you also shun innovation in product development.

There has been much discussion in the industry about how Generations X and Y will be the beneficiaries of the largest intergenerational transfer of wealth in history when baby boomers begin to pass on. These tech savvy generations will expect their financial advisers to be able to work with them on their terms, with an emphasis on AI tools.

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 the advice and the product solutions will continue to have to wrestle with legacy issues and old systems.

Client bases are also extremely diverse with 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, they do not normally look backwards and are not always focused on dealing with client and advice that is already in place.

In the end new technology is often the focus of the younger demographic, both as a provider of solutions and as an end user of the technology. AI will soon have a role to play in most areas of Financial Services and advisers should be prepared to explore the benefits that these technologies will bring.

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