Artificial Intelligence: The Role it can Play in Wealth Management

Advances in Artificial Intelligence (AI) have augmented the processes in numerous industries, with a growing list of possibilities. Can AI be a tool to help wealth managers improve their investment techniques and boost the performance of their portfolios?

Advances in Artificial Intelligence (AI) have augmented the processes in numerous industries, with a growing list of possibilities. Can AI be a tool to help wealth managers improve their investment techniques and boost the performance of their portfolios?

We speak to Allan Lane, Founding Partner of Algo-Chain, a UK-based Fintech company that offers white label solutions for ETF model portfolios to wealth managers, to find out.

What role does AI currently play in the wealth management industry in general, and in portfolio construction and investing in particular?

Regarding the notion what role there is for AI in wealth management, let me start by leaving the academic discussion of what actually constitutes AI to others. I think most individuals know what is meant here. For example, are there patterns to the way different assets classes behave across the economic cycle? If so, can that insight be exploited to improve a buy and hold strategy, both on the performance and risk management front?

Historically, a significant percentage of quant hedge funds have used market and macroeconomic data to develop their proprietary strategies, so nothing new here. What is different now though, is the extent to which big data dominates the intellectual arms race.

Ironically, AI will continue to offer the most benefits to the less glamorous corners of the wealth management ecosystem. Only recently I read that JP Morgan was going to introduce Amazon’s virtual assistant, Alexa, to service clients’ enquiries for reports and the like.

How do you see the role of AI in the wealth management and investment industry changing and evolving in the coming years?

In many ways, AI has an image problem. More effort will be needed to promote the benefits and to dispel the notion that it will only take people’s jobs away. Where I see its biggest role is in the area of information curating. With every one of us drowning in too much data, all of us need help in this area.

What are some of the benefits of using AI in portfolio construction?

As a discipline, portfolio construction is about the art of designing an investment proposition that offers no surprises. It has been over 250 years since the English statistician, Thomas Bayes, introduced the world to the concept of conditional probability. By using these statistical techniques, along with the notion of analysing the input data on an expanding window basis, it is now possible to construct Risk Rated Model Portfolios that tactically adjust their asset allocation based on the most recent information in the market.

Do AI-constructed portfolios typically outperform those created solely by humans?

No, they probably don’t, but the amount of resources needed to run these portfolios is lower, and as a direct consequence, this will lead to a reduction in fees. Evolution, not revolution.

What are some of the risks, downsides, and potential pitfalls of using AI in portfolio construction?

It would be easy to fall into the trap where one starts to believe that these models could run with no human intervention. In fact, nothing could be further from the truth. In the world of machine learning there is now the notion of the ‘Kasparov Effect’, where having been beaten at chess by IBM’s Big Blue computer, once Kasparov could augment his skill with his own tech gadget, he went on to win. AI plus human intervention will beat AI nearly all of the time!

How does AI impact your company’s investing techniques, processes, and strategies?

We have found that getting on top of large amounts of ETF data takes an extraordinary amount of time. Once that data has been labelled and cleaned, maybe there’s a chance that one can tease out the secrets that it holds. It is the simple observations that are the most valuable, and it is these stylised facts that provide the foundation from which we further develop our ETF selection rules.

Commentators often think of AI as a very big black box process, when in reality the best-kept secret is that it is the aggregation of many small insights that lead to the best results.

How do you see the company changing and developing in the coming years?

Initially we have focused on ETFs, and we are thinking about extending the idea of an intelligent selection process to active funds.

The tidal wave of blockchain and cryptocurrencies that are raining down on us is best seen as one of the central planks to the digitisation of the financial services industry. The genie is out of the bottle, and our mission is to help other firms join the fintech revolution and take control.

This article was originally published by WEALTH, Asia’s marketplace for investors.

 

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