Abstract
Financial exclusion has a major socio-economic impact on the poor and unbanked. Financially excluded smallholder farmers face challenges accessing credit facilities to fund their farming activities because they lack the financial history data required to create credit scores for credit risk evaluations. Non-financial data sources such as mobile applications have been proposed for the development of credit scoring models. However, context-specific alternative scoring factors which are independent of financial history information, must be developed for credit decision systems that use nonfinancial data. This research proposes an approach to developing alternative scoring factors based on stakeholder's requirements. An example of implementation of the proposed method is given using data collected from farmers in rural Cambodia through surveys and a mobile application. Alternative scoring factors are developed based on stakeholder's requirements and collected data. Multiple logistic regression and support vector machine models are trained and tested on this data to evaluate the selected factors. Models are compared by area under the receiver operating characteristics curve values and accuracy. Additional considerations are made to determine the most suitable model in this context. This stakeholder requirements-based approach can be used to design credit decision systems using nonfinancial data for financially excluded persons and facilitate greater financial inclusion.
| Original language | English |
|---|---|
| Title of host publication | 4th IEEE International Symposium on Systems Engineering, ISSE 2018 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781538644461 |
| DOIs | |
| Publication status | Published - 2018 Nov 26 |
| Event | 4th IEEE International Symposium on Systems Engineering, ISSE 2018 - Roma, Italy Duration: 2018 Oct 1 → 2018 Oct 3 |
Other
| Other | 4th IEEE International Symposium on Systems Engineering, ISSE 2018 |
|---|---|
| Country | Italy |
| City | Roma |
| Period | 18/10/1 → 18/10/3 |
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Keywords
- Agriculture
- Credit Scores
- Decision Making
- Mobile Applications
- Stakeholder Requirements
ASJC Scopus subject areas
- Computer Networks and Communications
- Hardware and Architecture
- Control and Systems Engineering
- Safety, Risk, Reliability and Quality
Cite this
Alternative scoring factors using non-financial data for credit decisions in agricultural microfinance. / Simumba, Naomi; Okami, Suguru; Kodaka, Akira; Kohtake, Naohiko.
4th IEEE International Symposium on Systems Engineering, ISSE 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8544442.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Alternative scoring factors using non-financial data for credit decisions in agricultural microfinance
AU - Simumba, Naomi
AU - Okami, Suguru
AU - Kodaka, Akira
AU - Kohtake, Naohiko
PY - 2018/11/26
Y1 - 2018/11/26
N2 - Financial exclusion has a major socio-economic impact on the poor and unbanked. Financially excluded smallholder farmers face challenges accessing credit facilities to fund their farming activities because they lack the financial history data required to create credit scores for credit risk evaluations. Non-financial data sources such as mobile applications have been proposed for the development of credit scoring models. However, context-specific alternative scoring factors which are independent of financial history information, must be developed for credit decision systems that use nonfinancial data. This research proposes an approach to developing alternative scoring factors based on stakeholder's requirements. An example of implementation of the proposed method is given using data collected from farmers in rural Cambodia through surveys and a mobile application. Alternative scoring factors are developed based on stakeholder's requirements and collected data. Multiple logistic regression and support vector machine models are trained and tested on this data to evaluate the selected factors. Models are compared by area under the receiver operating characteristics curve values and accuracy. Additional considerations are made to determine the most suitable model in this context. This stakeholder requirements-based approach can be used to design credit decision systems using nonfinancial data for financially excluded persons and facilitate greater financial inclusion.
AB - Financial exclusion has a major socio-economic impact on the poor and unbanked. Financially excluded smallholder farmers face challenges accessing credit facilities to fund their farming activities because they lack the financial history data required to create credit scores for credit risk evaluations. Non-financial data sources such as mobile applications have been proposed for the development of credit scoring models. However, context-specific alternative scoring factors which are independent of financial history information, must be developed for credit decision systems that use nonfinancial data. This research proposes an approach to developing alternative scoring factors based on stakeholder's requirements. An example of implementation of the proposed method is given using data collected from farmers in rural Cambodia through surveys and a mobile application. Alternative scoring factors are developed based on stakeholder's requirements and collected data. Multiple logistic regression and support vector machine models are trained and tested on this data to evaluate the selected factors. Models are compared by area under the receiver operating characteristics curve values and accuracy. Additional considerations are made to determine the most suitable model in this context. This stakeholder requirements-based approach can be used to design credit decision systems using nonfinancial data for financially excluded persons and facilitate greater financial inclusion.
KW - Agriculture
KW - Credit Scores
KW - Decision Making
KW - Mobile Applications
KW - Stakeholder Requirements
UR - http://www.scopus.com/inward/record.url?scp=85059981569&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059981569&partnerID=8YFLogxK
U2 - 10.1109/SysEng.2018.8544442
DO - 10.1109/SysEng.2018.8544442
M3 - Conference contribution
AN - SCOPUS:85059981569
BT - 4th IEEE International Symposium on Systems Engineering, ISSE 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -