Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data

Adedeji Olowe; James Kunle Olorundare; Temitope Phillips

doi:doi:10.11648/j.ijdst.20210701.12

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Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data

Adedeji Olowe, James Kunle Olorundare, Temitope Phillips

Published in International Journal on Data Science and Technology (Volume 7, Issue 1)

Received: 31 December 2020 Accepted: 11 January 2021 Published: 2 February 2021

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Abstract

Financial exclusion remains a significant challenge in developing economies. It has been shown that access to credit facilities is a strong predictor of financial inclusion. Credit reporting and scoring remain effective tools for both traditional and alternative lenders, however, access to credible credit data and scoring mechanisms is one of the biggest roadblocks that alternative lenders in developing economies face. While some lenders have developed systems that leverage social media analytics and data harvested from smartphones in order to create a scoring system, the poor and vulnerable are still excluded from such scoring systems. There have been significant advances in the use of telecoms data for credit scoring, making it a promising alternative to credit bureau data. However, readily available data is still an issue. With the increase in the development and use of open APIs, telecoms data could be made readily available for credit scoring, while addressing privacy and other issues. This paper is a conceptual paper that proposes a model for the use of Open APIs from telco data for credit scoring that will ultimately increase access to credit, and ultimately financial inclusion in Africa.

Published in	International Journal on Data Science and Technology (Volume 7, Issue 1)
DOI	10.11648/j.ijdst.20210701.12
Page(s)	17-22
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

APIs, Credit Scoring, Economic Development, Financial Inclusion, Call Detail Records

References

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APA Style

Adedeji Olowe, James Kunle Olorundare, Temitope Phillips. (2021). Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data. International Journal on Data Science and Technology, 7(1), 17-22. https://doi.org/10.11648/j.ijdst.20210701.12

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ACS Style

Adedeji Olowe; James Kunle Olorundare; Temitope Phillips. Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data. Int. J. Data Sci. Technol. 2021, 7(1), 17-22. doi: 10.11648/j.ijdst.20210701.12

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AMA Style

Adedeji Olowe, James Kunle Olorundare, Temitope Phillips. Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data. Int J Data Sci Technol. 2021;7(1):17-22. doi: 10.11648/j.ijdst.20210701.12

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@article{10.11648/j.ijdst.20210701.12,
  author = {Adedeji Olowe and James Kunle Olorundare and Temitope Phillips},
  title = {Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data},
  journal = {International Journal on Data Science and Technology},
  volume = {7},
  number = {1},
  pages = {17-22},
  doi = {10.11648/j.ijdst.20210701.12},
  url = {https://doi.org/10.11648/j.ijdst.20210701.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdst.20210701.12},
  abstract = {Financial exclusion remains a significant challenge in developing economies. It has been shown that access to credit facilities is a strong predictor of financial inclusion. Credit reporting and scoring remain effective tools for both traditional and alternative lenders, however, access to credible credit data and scoring mechanisms is one of the biggest roadblocks that alternative lenders in developing economies face. While some lenders have developed systems that leverage social media analytics and data harvested from smartphones in order to create a scoring system, the poor and vulnerable are still excluded from such scoring systems. There have been significant advances in the use of telecoms data for credit scoring, making it a promising alternative to credit bureau data. However, readily available data is still an issue. With the increase in the development and use of open APIs, telecoms data could be made readily available for credit scoring, while addressing privacy and other issues. This paper is a conceptual paper that proposes a model for the use of Open APIs from telco data for credit scoring that will ultimately increase access to credit, and ultimately financial inclusion in Africa.},
 year = {2021}
}

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TY  - JOUR
T1  - Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data
AU  - Adedeji Olowe
AU  - James Kunle Olorundare
AU  - Temitope Phillips
Y1  - 2021/02/02
PY  - 2021
N1  - https://doi.org/10.11648/j.ijdst.20210701.12
DO  - 10.11648/j.ijdst.20210701.12
T2  - International Journal on Data Science and Technology
JF  - International Journal on Data Science and Technology
JO  - International Journal on Data Science and Technology
SP  - 17
EP  - 22
PB  - Science Publishing Group
SN  - 2472-2235
UR  - https://doi.org/10.11648/j.ijdst.20210701.12
AB  - Financial exclusion remains a significant challenge in developing economies. It has been shown that access to credit facilities is a strong predictor of financial inclusion. Credit reporting and scoring remain effective tools for both traditional and alternative lenders, however, access to credible credit data and scoring mechanisms is one of the biggest roadblocks that alternative lenders in developing economies face. While some lenders have developed systems that leverage social media analytics and data harvested from smartphones in order to create a scoring system, the poor and vulnerable are still excluded from such scoring systems. There have been significant advances in the use of telecoms data for credit scoring, making it a promising alternative to credit bureau data. However, readily available data is still an issue. With the increase in the development and use of open APIs, telecoms data could be made readily available for credit scoring, while addressing privacy and other issues. This paper is a conceptual paper that proposes a model for the use of Open APIs from telco data for credit scoring that will ultimately increase access to credit, and ultimately financial inclusion in Africa.
VL  - 7
IS  - 1
ER  -

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Author Information

Adedeji Olowe

Open Banking Nigeria, Lagos, Nigeria
James Kunle Olorundare

Nigerian Communications Commission (NCC), Abuja, Nigeria
Temitope Phillips

Lendsqr, Lagos, Nigeria

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Plain Text BibTeX RIS

APA Style

Adedeji Olowe, James Kunle Olorundare, Temitope Phillips. (2021). Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data. International Journal on Data Science and Technology, 7(1), 17-22. https://doi.org/10.11648/j.ijdst.20210701.12

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ACS Style

Adedeji Olowe; James Kunle Olorundare; Temitope Phillips. Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data. Int. J. Data Sci. Technol. 2021, 7(1), 17-22. doi: 10.11648/j.ijdst.20210701.12

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AMA Style

Adedeji Olowe, James Kunle Olorundare, Temitope Phillips. Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data. Int J Data Sci Technol. 2021;7(1):17-22. doi: 10.11648/j.ijdst.20210701.12

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@article{10.11648/j.ijdst.20210701.12,
  author = {Adedeji Olowe and James Kunle Olorundare and Temitope Phillips},
  title = {Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data},
  journal = {International Journal on Data Science and Technology},
  volume = {7},
  number = {1},
  pages = {17-22},
  doi = {10.11648/j.ijdst.20210701.12},
  url = {https://doi.org/10.11648/j.ijdst.20210701.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdst.20210701.12},
  abstract = {Financial exclusion remains a significant challenge in developing economies. It has been shown that access to credit facilities is a strong predictor of financial inclusion. Credit reporting and scoring remain effective tools for both traditional and alternative lenders, however, access to credible credit data and scoring mechanisms is one of the biggest roadblocks that alternative lenders in developing economies face. While some lenders have developed systems that leverage social media analytics and data harvested from smartphones in order to create a scoring system, the poor and vulnerable are still excluded from such scoring systems. There have been significant advances in the use of telecoms data for credit scoring, making it a promising alternative to credit bureau data. However, readily available data is still an issue. With the increase in the development and use of open APIs, telecoms data could be made readily available for credit scoring, while addressing privacy and other issues. This paper is a conceptual paper that proposes a model for the use of Open APIs from telco data for credit scoring that will ultimately increase access to credit, and ultimately financial inclusion in Africa.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data
AU  - Adedeji Olowe
AU  - James Kunle Olorundare
AU  - Temitope Phillips
Y1  - 2021/02/02
PY  - 2021
N1  - https://doi.org/10.11648/j.ijdst.20210701.12
DO  - 10.11648/j.ijdst.20210701.12
T2  - International Journal on Data Science and Technology
JF  - International Journal on Data Science and Technology
JO  - International Journal on Data Science and Technology
SP  - 17
EP  - 22
PB  - Science Publishing Group
SN  - 2472-2235
UR  - https://doi.org/10.11648/j.ijdst.20210701.12
AB  - Financial exclusion remains a significant challenge in developing economies. It has been shown that access to credit facilities is a strong predictor of financial inclusion. Credit reporting and scoring remain effective tools for both traditional and alternative lenders, however, access to credible credit data and scoring mechanisms is one of the biggest roadblocks that alternative lenders in developing economies face. While some lenders have developed systems that leverage social media analytics and data harvested from smartphones in order to create a scoring system, the poor and vulnerable are still excluded from such scoring systems. There have been significant advances in the use of telecoms data for credit scoring, making it a promising alternative to credit bureau data. However, readily available data is still an issue. With the increase in the development and use of open APIs, telecoms data could be made readily available for credit scoring, while addressing privacy and other issues. This paper is a conceptual paper that proposes a model for the use of Open APIs from telco data for credit scoring that will ultimately increase access to credit, and ultimately financial inclusion in Africa.
VL  - 7
IS  - 1
ER  -

Copy | Download