Think about this situation. Imagine that you are client of any wealth manager and the staff sends you a report about the best chances for your investments, with recommendations and comments to obtain the best performance. Then, you talk to a friend, who is also client of the same wealth manager and you both comment about the report. You discover that both reports are personalised and are not the traditional recommendations’ standardised reports that these entities publish regularly. Each one have personalised information and you both discover that the entity has used your full data to design the best report to meet your needs. Then, you explain your friend several changes in your investments. Both have the same risk profile, but your portfolios (and the historic operations) have nothing to do to another.
The example could be larger, but it is enough to introduce the changes that we will live soon in the wealth management branch. The expression behind these changes is artificial intelligence. Shortened as AI, it is not a Steven Spielberg film. It is far from fiction, because it is reality. The learning capability of machines increased exponentially in the last years and the soar will keep on. There is a combination of big data analysis, natural language and machine learning. Big data analysis provides the capability of learning better not only about the customer, but also about any trend that goes around him. Natural language allows machines to interpret and generate spoken and written language. Machine learning uses algorithms that can learn and make predictions on data.
This will be the mix that we will see growing in the next years. The transformation will be deep in the whole financial sector. Currently, a 26% of assets and wealth manager firms already use AI to inform the next big decisions, according to PricewaterhouseCoopers. Money is flowing increasingly there, because all agree that this will be the next step for fintech business.
For instance, natural language processes will help comply better with regulations, as machines will learn immediately the changes and adaptations will be easier in platforms. This will also has a very relevant collateral effect managing risks more efficiently. The client will obtain a high-improved user experience with new interfaces. The advisor tasks will focus in asset gathering and portfolio monitoring. They will also become more responsive to client needs and increase the added value of their services.
Robo-advisor in the first deep step in this change. There will be further changes with a greater automation. Robo-advisors and human advisors will experience several transformations in their tasks and roles against clients. They, the clients, will be winners and the only losers will be entities (not only human, also fintech) that will not adapt to the new wave.