Integrating Customer Portfolio Theory and the Multiple Sources of Risk Approaches to Model Risk-Adjusted Revenue

This study proposes new methods to formulate customers' risk-adjusted revenue (RAR) metrics applied the financial industry. Using a customer dataset provided by loan company, we compute RAR using benchmark approaches presented in literature and formulas that combine Customer Portfolio Theory Multiple Sources of Revenues approaches. We validate efficiency originality our formulations implementing statistical tests check for differences across different measures. find proposed models are unique can be implemented industry account multiple sources risk, hence providing managers with ways improve their valuation portfolios.