Some banks have also started using machine learning for targeting clients in product campaigns, with dramatic hikes in conversion and profitability.
For some time, automation by means of machine learning from structured data has been widely used in trading and in asset management.
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.
Hence, the risk in the investment strategy depends on the time horizon and not only on the risk in the asset per se.
This is very important, and for as long as robo-advisory models don’t operate with a risk concept that integrates the intended investment horizon for various components, robo-advisory will never be really useful in real-life advisory situations, in my view.” 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?