Machine Learning and Fundraising: Applications of Artificial Neural Networks

Diana Barro (), Luca Barzanti (), Marco Corazza () and Martina Nardon ()
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Diana Barro: Department of Economics, Ca' Foscari University of Venice
Luca Barzanti: Department of Mathematics, University of Bologna
Marco Corazza: Department of Economics, Ca' Foscari University of Venice

No 2023: 33, Working Papers from Department of Economics, University of Venice "Ca' Foscari"

Abstract: In fundraising management, the assessment of the expected gift is a key point. The availability of accurate estimates of the number of donations, their amounts, and the gift probability is relevant in order to evaluate the results of a fundraising campaign. The accuracy of the expected gift estimation depends on the appropriate use of the information about Donors. In this contribution, we propose a non-parametric methodology for the prediction of Donors' behavior based on Artificial Neural Networks. In particular, Multi-Layer Perceptron is applied. In the numerical experiments, the expected gift is then estimated based on a simulated dataset of Donors' individual characteristics and information on donations history.

Keywords: Fundraising Management; Donor's Profile; Gift Expectation; Artificial Neural Networks (search for similar items in EconPapers)
JEL-codes: C45 D64 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2023
New Economics Papers: this item is included in nep-big and nep-cmp
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