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Thumbnail image for product with reference number 516-0175-1
Bringing Quick Loans to the Unbankable in Kenya (A)
Case
-
Reference no. 516-0175-1
Subject category: Marketing
Authors: Philip Parker (INSEAD); Carolyn Wendell (INSEAD)
Published by: INSEAD
Originally published in: 2016
Version: 09.2016
Length: 7 pages
Data source: Published sources
Topics: Loans; Unbankable; Emerging markets; Kenya; Banking; Entrepreneurship; Interest; Machine learning; Algorithm; Data science; Mobile; M-PESA
Share a link: https://casecent.re/p/138036
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Abstract

This is part of a case series. This case tells the story of InVenture, a data science company based in California, that has created a machine learning algorithm to identify the creditworthiness of those with no credit history by tracking their mobile data patterns. With this technology they define a credit score and can issue a loan almost instantly to the borrower via a mobile phone. The technology behind InVenture has been used to develop a smart phone app - Mkopo Rahisi - which enables loans to be approved quickly to small business owners in Kenya.
Industry:
Social finance
Other setting(s):
2014
Thumbnail image for product with reference number 516-0175-8
Bringing Quick Loans to the Unbankable in Kenya
Teaching note
-
Reference no. 516-0175-8
Subject category: Marketing
Authors: Philip Parker (INSEAD); Carolyn Wendell (INSEAD)
Published by: INSEAD
Originally published in: 2016
Version: 09.2016
Length: 2 pages
Data source: Published sources
View full details
Thumbnail image for product with reference number 516-0175-1B
Bringing Quick Loans to the Unbankable in Kenya (B)
Case
-
Reference no. 516-0175-1B
Subject category: Marketing
Authors: Philip Parker (INSEAD); Carolyn Wendell (INSEAD)
Published by: INSEAD
Originally published in: 2016
Version: 09.2016
Length: 6 pages
Data source: Published sources
Topics: Loans; Unbankable; Emerging markets; Kenya; Banking; Entrepreneurship; Interest; Machine learning; Algorithm; Data science; Mobile; M-PESA
View full details

About

Abstract

This is part of a case series. This case tells the story of InVenture, a data science company based in California, that has created a machine learning algorithm to identify the creditworthiness of those with no credit history by tracking their mobile data patterns. With this technology they define a credit score and can issue a loan almost instantly to the borrower via a mobile phone. The technology behind InVenture has been used to develop a smart phone app - Mkopo Rahisi - which enables loans to be approved quickly to small business owners in Kenya.

Settings

Industry:
Social finance
Other setting(s):
2014

Related

Thumbnail image for product with reference number 516-0175-8
Bringing Quick Loans to the Unbankable in Kenya
Teaching note
-
Reference no. 516-0175-8
Subject category: Marketing
Authors: Philip Parker (INSEAD); Carolyn Wendell (INSEAD)
Published by: INSEAD
Originally published in: 2016
Version: 09.2016
Length: 2 pages
Data source: Published sources
View full details
Thumbnail image for product with reference number 516-0175-1B
Bringing Quick Loans to the Unbankable in Kenya (B)
Case
-
Reference no. 516-0175-1B
Subject category: Marketing
Authors: Philip Parker (INSEAD); Carolyn Wendell (INSEAD)
Published by: INSEAD
Originally published in: 2016
Version: 09.2016
Length: 6 pages
Data source: Published sources
Topics: Loans; Unbankable; Emerging markets; Kenya; Banking; Entrepreneurship; Interest; Machine learning; Algorithm; Data science; Mobile; M-PESA
View full details