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Truly digital companies, such as Spotify and Tinder, regularly analyze hundreds of millions of events in order to understand their clients and to remain one step ahead of them—on an individual level.Ironically, the finance industry is the only industry I know for which the legislator has to step in and order the operators to know their clients: “Know your client, or you will be hit with legal sanctions!Settlements for alleged unsuitable advice—or breaches of fiduciary duties—have become a consequence of large market corrections.What is viewed as suitable at one point is not necessarily viewed as suitable in a future dispute, and history shows that no court is immune to hindsight bias.Robo-advisory models of today rely on the concept of single horizon, which is a basic assumption with no explanatory value.In theory, it is assumed that “assets with the same risk should have the same expected rate of return”, and vice versa.Models need to take into account that individual portfolios may have components with different investment horizons.Matching individual risk profiles and needs with customized-model portfolios is neither new nor very exciting, in my view.
Maybe it is because many banks operate in inefficient markets, with local oligopolies, high barriers and insufficient competition.
” In the light of reputation risks, fines and penalties, as well as missed business opportunities in the digital age, that’s quite bizarre, wouldn’t you agree?
Banks have a lot to learn from the digital world, and they have to become much more agile.
Such a multi-dimensional risk concept is, however, possible with new technology, including artificial intelligence.
Secondly, advisory models must also, ideally, generate some viable evidence to suggest that the investment advice was suitable to the best of everyone’s knowledge at the time when the advice was given.