Graduation Year

2016

Date of Submission

11-2015

Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts

Department

Economics

Reader 1

Manfred Keil

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Rights Information

© 2015 Alessandra L Savino

Abstract

Microfinance aims to develop a financial ecosystem that serves the various financial needs of the poor, in hopes of providing them with the tools to sustainably elevate their economic and social well-being. This paper observes the evolution of financial inclusion over the past 40 years. Although considerable strides have been made to increase the impact of microfinance services, inherent challenges continue to plague the success of the industry. These fundamental deficiencies in microfinance initiatives (MFI’s) include the inability to scale, operate profitably and contribute to their clients’ economic and social betterment.

This paper observes two fundamental changes that need to be made in order to insure the longevity and success of the industry. First, the industry needs to better integrate the use of innovative technology, which will allow organizations to be increasingly dynamic and targeted in their implementation. Businesses are quickly evolving to be data-centric to increase their profitability and customer base; if MFI’s were able to better understand their clients, they would be able to develop product offerings, delivery mechanisms and outreach efforts that are specifically focused to the needs of their target markets. The second fundamental change essential to success is that microfinance services need to be more fully integrated into the formal financial sector, and governments need to create an environment that encourages businesses and financial institutions to develop products to serve the poor.

Cluster analysis aims to identify natural shapes within high-dimensional data and can be applied to numerous fields. As businesses have become more adept at keeping track of their customer data, a common application has been to conduct customer segmentation to better understand and serve their clients. This paper conducts clustering analysis on borrower data from The Lending Club, an online market place for micro-credit in order to better understand the various customer segments.

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