From 864cde8973585468f5d623581721b06f8c498816 Mon Sep 17 00:00:00 2001 From: Ornella Altunyan <44654695+ornellaalt@users.noreply.github.com> Date: Tue, 1 Jun 2021 15:16:37 -0700 Subject: [PATCH] Add paragraph about wealth management --- Real-World/1-Applications/README.md | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/Real-World/1-Applications/README.md b/Real-World/1-Applications/README.md index 58555b2c..b7b78d04 100644 --- a/Real-World/1-Applications/README.md +++ b/Real-World/1-Applications/README.md @@ -7,7 +7,7 @@ While a lot of interest in industry has been garnered by AI, which usually lever ## Finance -One of the major consumers of classical machine learning models is the finance industry. +One of the major consumers of classical machine learning models is the finance industry. Two specific examples we cover here are **credit card fraud detection** and **wealth management**. ### Credit card fraud detection @@ -17,6 +17,10 @@ K-means clustering comes in handy during a credit card fraud detection technique ### Wealth management +In wealth management, an individual or firm handles investments on behalf of their clients. Their job is to sustain and grow wealth in the long-term, so it is essential to choose investments that perform well. + +One way to evaluate how a particular investment performs is through statistical regression. [Linear regression](Regression/1-Tools/README.md) is a valuable tool for understanding how a fund performs relative to some benchmark. We can also deduce whether or not the results of the regression are statistically significant, or how much they would affect a client's investments. You could even further expand your analysis using multiple regression, where additional risk factors can be taken into account. For an example of how this would work for a specific fund, check out [this paper](http://www.brightwoodventures.com/evaluating-fund-performance-using-regression/) on evaluating fund performance using regression. + ## Education ### Predicting student behavior