Targeting small businesses with personalised business advice and predicting successful loan applications
Micro, small and medium-sized enterprises (MSMEs) play a key role in economic development, but they face challenges in accessing finance.
This case study explores a Tanzanian initiative that aims to support MSMEs – particularly those owned by women and youth – by enabling business owners to locate, connect with and engage business advisors through an online platform.
In Tanzania over 2.7 million businesses are either MSMEs and are estimated to employ over 5.2 million people [1]. For most of these MSMEs, access to finance – and the use of business-appropriate financial products and services – serve as a major barrier to growth [2].
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This case study is part of the DataHack4FI Innovation Award competition Season 2 series. The competition brings together data enthusiasts and financial service providers to promote the use of data-driven decision-making in financial inclusion. For a similar case study in Season 1, read more here or find out more about the competition at datahack4fi.org.
[1] A firm is classified as a micro, small or medium-sized enterprise if it has fewer than 250 customers (Copenhagen Business School. N.D. Tanzania country study)
[2] FSDT. (n.d) SME Finance. Available at: http://www.fsdt.or.tz/sme-finance/
Targeting small businesses with personalised business advice and predicting successful loan applications
Micro, small and medium-sized enterprises (MSMEs) play a key role in economic development, but they face challenges in accessing finance.
This case study explores a Tanzanian initiative that aims to support MSMEs – particularly those owned by women and youth – by enabling business owners to locate, connect with and engage business advisors through an online platform.
In Tanzania over 2.7 million businesses are either MSMEs and are estimated to employ over 5.2 million people [1]. For most of these MSMEs, access to finance – and the use of business-appropriate financial products and services – serve as a major barrier to growth [2].
This case study is part of the DataHack4FI Innovation Award competition Season 2 series. The competition brings together data enthusiasts and financial service providers to promote the use of data-driven decision-making in financial inclusion. For a similar case study in Season 1, read more here or find out more about the competition at datahack4fi.org.
[1] A firm is classified as a micro, small or medium-sized enterprise if it has fewer than 250 customers (Copenhagen Business School. N.D. Tanzania country study)
[2] FSDT. (n.d) SME Finance. Available at: http://www.fsdt.or.tz/sme-finance/