Robo-advisors (automated investment advisors) have become the flavour of the month in the financial services industry. Artificial intelligence (AI), machine learning (ML) and deep learning (DL) have become buzz words in all industries. This is a sexy area, and the financial services industry wants to use these advances, which is why even mainstream players like J.P. Morgan are getting into the act. After all, if they can automate the advice they provide to their clients, then they won’t need to pay for expensive wealth managers and this will dramatically increase their profit margins, which is why everyone wants to get onto the bandwagon.
This seems to be a very logical solution. After all, we know that one of the reasons why investors don’t do well in the financial markets is because of the fees which they are charged by their financial advisors. These fees impose friction costs, which reduces the amount of money the clients get to take home. If these fees could be reduced, then clients would get a better return on their investment. This is why every fintech startup now wants to get into this space which appears so lucrative at first blush.
This reduced cost has been the major selling proposition so far. These “intelligent” algorithms automatically rebalance your portfolio (deciding what percentage of your wealth should be allocated to fixed income, and what percentage to equities) according to a pre-set formula, which is principally based on your risk profile and your age.
Another advantage is that they offer the client much more convenience because they are deployed online. They are easy to use and the whole “set it and forget it” approach is very tempting for customers. The automation ensures that your portfolio doesn’t get neglected, and your asset allocation remains disciplined over time.
The Benefits/Problems Of Robo-advisors
In my opinion, the major benefit of this option is that your wealth manager is not tempted to keep on churning your portfolio in order to maximise his fees. This will definitely improve your returns, but the truth is that this is an unintended consequence of using an automated system!
The big problem with all these robo-advisors is that they are not really using artificial intelligence – they are just mindlessly applying a simple linear asset allocation formula on a regular basis. There is no personalisation and the performance is not tailored to market conditions, which means these are really dumb robo-advisors. They are no better than that of the average relationship manager because they use the same software which traditional advisors do.
Now, it makes a lot of sense for the financial services firm to invest in these robo-advisors. They are less costly than smooth-talking slick wealth managers who charge the firm an arm and a leg for their selling skills. The robo-advisors make it possible for the firms to service many more clients, at a fraction of the cost, because this can be done online.
While this is a value add for the financial services firm, how does this clever marketing add any value to the client’s life? After all, what a client really wants is better advice so he’ll get a better return. The only reason he gets a better return with robo-advisors is because the fees have been reduced – the quality of the advice remains unchanged.
Wealth Managers Are Important Too
Rather than think of the robo-advisor as an intelligent expert, you need to reframe the way you look at the wealth manager your bank employs to service you. He is usually just a good-looking dummy with great people skills, who has a little financial expertise, and just does what the script tells him to do. Do you really need to pay for expensive hand-holding from a polished salesman?
Going forward, I expect we will see hybrid models becoming more popular. They will combine high tech with high touch because HNIs have complex needs. While millennials may prefer talking and interacting with computers, older HNIs still need hand holding by a human.
The relationship manager will manage the human interaction; and will be able to do a better job because he will have a robo-advisor at the back end, which can ingest a lot more data, to provide more intelligent solutions, tailored to the client’s needs.
Thus, the software will be able to aggregate all the client’s bank accounts, credit cards, insurance, and alternative assets, so that the relationship manager will be able to give the customer a more accurate picture of his net worth. The robo-advisors will also be able to analyse spending patterns of millions of people all over the country and use big data analytics to give a more accurate picture of how much the client needs to save/spend to be able to meet his personal goals.
In Conclusion
I feel that the specialised human fund manager who can generate alpha still has an edge as regards portfolio management. None of the robo-advisors have been able to show that they can consistently outperform the market, even though is really where the huge opportunity lies. Finally, the focus needs to be on increasing the upside rather than just reducing the friction costs. This space will evolve over time but it’s still early days.
The disadvantage is that when some clever geek finally does develop some cool AI to improve the quality of the advice given to the client, we will not be able to appreciate the difference because we have misused these terms. The financial services firms are doing a dis-service to themselves and their clients by adding needless hype – but sadly, this is the way most wealth management firms operate. Their marketing is far better than the quality of their advice or their client’s returns!
Valuable insights for this article were generously provided by Pratik Oswal, who currently works at a robo-advisory firm (StratiFi) based out of Silicon Valley.
[This post by Dr. Aniruddha Malpani first appeared on LinkedIn and has been reproduced with permission.]
