Asset Retention Intelligence - The Good Defense

January 30, 2020

Report Abuse
Predicting Attrition and Assisting in Asset Retention - using Machine Learning - MS Cloudathon
**Business Scenario and Data** - Historically Clients are more likely to depart the firm with the Advisors. - Companies have a growth opportunity well with in their reach: asset retention. - We think this subject will only rise in importance in the coming years.... - Companies can see a large benefit with as little as five percentage-point improvement in asset/client retention. The input data is simulated to reflect features that are generic for most of the predictive maintenance scenarios for attrition. To enable the experiment to be completed very quickly, the data was simulated to be around 20K records with 16 data attributes but the same Python code can be easily applied to a much larger data set. The Dataset is generated in CSV format using Python and was imported into the Machine Learning Studio Workspace for model training. ======================================================================== **Techinal Specifications** Azure Machine Learning Designer Azure Machine Learning Studio (Classic) Python - Jupiter Notebook