Predictive Analytics for Charitable giving

Machine learning in the charitable sector is only beginning to be used successfully. Fundmetric Inc has applied various machine learning algorithms to predict donor behaviour, such as who will become a major ($10,000+) donor and which lapsed donors will return if stewarded correctly. There is ample opportunity for research in this domain, including building a super model across various charities, investigating feature synthesis and importance, applying deep learning to make use of the rich temporal data concerning donations, and learning to sequence email appeals. We plan to investigate the application and creation of various machine learning techniques to these and other pressing charitable issues in order to both help the charitable sector be more effective in raising funds and help advance the field of machine learning.

Faculty Supervisor:

Greg Lee;Daniel Silver

Student:

Syed Sahwan;Kethineni Veera Raghavan;Srikanth Reddy Adunoor

Partner:

Fundmetric Inc

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Acadia University