Predictive Modeling Using Transactional Data

Publish date:

Analytics uses past data to forecast or predict future events, providing financial services firms with a strategic capability to be proactive. Predictive modeling offers the potential for firms to be proactive rather than reactive. Predictive modeling using transactional data poses particular challenges which need to be carefully addressed to create useful models. In this paper, […]

Analytics uses past data to forecast or predict future events, providing financial services firms with a strategic capability to be proactive.

Predictive modeling offers the potential for firms to be proactive rather than reactive. Predictive modeling using transactional data poses particular challenges which need to be carefully addressed to create useful models.

In this paper, Capgemini discusses challenges for predictive modeling such as data quality, cohort and trend analysis, model variable definition and model selection.

Related Resources

DRIVE MARKETING AGILITY TO IMPROVE OUTCOMES

A Guide for Financial Services CMOs: Download this e-book from Capgemini and Tealium to learn...

World InsurTech Report 2021

Get an overview of World InsurTech Report 2021 key findings by visiting the report’s...