wealth management, wealth advisory, machine-generated investment strategies, artificial intelligence, machine learning
Recommendation solutions are sometimes used by wealth management firms and banks to automatically suggest the product that a client may be interested in. They aim to increase client satisfaction and avoid wasting both the client’s and the relationship manager’s time with inappropriate offers.
After introducing non-bankable asset investing in the first article of this series, we here discuss some valuation approaches using machine learning to make nBA investing fit for total wealth management.
wealth management solutions, data science, artificial intelligence, machine learning
This is the first piece in a series of three short articles that will address investing in non-bankable assets and focus on critical considerations when one’s investment portfolio includes such alternative investment vehicles.
It may sound like an exaggeration, but there is hardly any person in the world that has never been part of a social network, or that has never used some sort of technical network. In a similar way, it’s almost impossible to come across any recent article about data science applications which does not mention the term “network”. Hence it is only natural to ask what is a network?
In this blog post, we will specifically delve into the type of challenges that arise in banks due to data quality and quantity-related issues and propose some concrete concepts that could mitigate these.