Title of Oral/Poster Presentation

Improving Micro-Finance Productivity through Data Analysis

Presenter Information

Ryan TaylorFollow
Benjamin BlauFollow

Class

Article

Department

Economics and Finance

Faculty Mentor

Benjamin Blau

Presentation Type

Oral Presentation

Abstract

In social entrepreneurship, much of the downfall associated with loan defaults is related to the lack of sufficient information. In other words, it is theorized that with more sufficient data and analysis of this data, programs and incentives can be put into place to both help loan recipients achieve productivity and financial stability and to help social entrepreneurship firms recognize red flags sooner in order to address any problems. Another downfall is that the workers in the field often have a lack of accountability and structure in their day-to-day work environment. In addition to the creation of an accountability program for the SEED program, which is a cooperative endeavor between the Jon M. Huntsman School of Business, Wasatch Social Ventures, and DanPer-Trujillo, countless hours have been spent creating surveys, digging through files, and speaking with new entrepreneurs for one purpose - to gather data. After the collection of data from all SEED Peru and SEED Ghana operations, a series of non-linear analyses were run on these data sets. The aim of these analyses was to determine the probabilities of loan default AND success associated with a wide array of factors in micro finance. The data gathered and the conclusions drawn mark the beginning of a long-term controlled-research study in micro-finance with a goal of determining the best methods to motivate loan recipients and eliminate default rates in social entrepreneurship programs.

Start Date

4-9-2015 2:00 PM

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Apr 9th, 2:00 PM

Improving Micro-Finance Productivity through Data Analysis

In social entrepreneurship, much of the downfall associated with loan defaults is related to the lack of sufficient information. In other words, it is theorized that with more sufficient data and analysis of this data, programs and incentives can be put into place to both help loan recipients achieve productivity and financial stability and to help social entrepreneurship firms recognize red flags sooner in order to address any problems. Another downfall is that the workers in the field often have a lack of accountability and structure in their day-to-day work environment. In addition to the creation of an accountability program for the SEED program, which is a cooperative endeavor between the Jon M. Huntsman School of Business, Wasatch Social Ventures, and DanPer-Trujillo, countless hours have been spent creating surveys, digging through files, and speaking with new entrepreneurs for one purpose - to gather data. After the collection of data from all SEED Peru and SEED Ghana operations, a series of non-linear analyses were run on these data sets. The aim of these analyses was to determine the probabilities of loan default AND success associated with a wide array of factors in micro finance. The data gathered and the conclusions drawn mark the beginning of a long-term controlled-research study in micro-finance with a goal of determining the best methods to motivate loan recipients and eliminate default rates in social entrepreneurship programs.