Recipes and Datasets to Predict Customer Churn Risk for Wealth Management
The app created by using the Customer Churn Risk for Wealth Management template creates
three recipes. The recipes create example, historical, prediction, and predicted score
datasets.
Required Editions
Available in: Professional, Enterprise, and Unlimited editions
with the Revenue Intelligence for Financial Services license
Recipes and Datasets
Recipe
Description
Output
Wealth Management Churn Example Dataset
Evaluates account snapshot data, financial account snapshot data, and data from
configured objects to create an example dataset that Einstein learns from. If you chose to
include Feedback Management and Sentiment Insights features when creating the app, the recipe
also evaluates the example set containing these features.
Example dataset
Wealth Management Churn Feature Dataset
Evaluates account snapshot data, financial account snapshot data, and data from
configured objects to create a historical dataset with details of accounts that were
previously likely to churn. The recipe also creates a prediction dataset based on which
Wealth Management customers who are likely to churn are identified. If you chose to include
Feedback Management and Sentiment Insights features when creating the app, the recipe also
evaluates the prediction set containing these features.
Historical dataset
Prediction dataset
Wealth Management Churn Prediction Dataset
Evaluates the prediction dataset to get the churn score of customers and the top three
factors that possibly contribute to churn.
Predicted Score and Top Contributing Factor dataset
You can modify the recipes in these scenarios:
Your schema deviates from the Financial Services Cloud schema.
A custom field of an existing entity changes.
The use of feature data changes from an existing entity to a custom entity.
The data doesn’t load properly.
The app stops working because of incorrect data values.
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