Algorithms for Inclusion : Data Driven Lending for Women Owned SMEs

Algorithms for Inclusion : Data Driven Lending for Women Owned SMEs

All over the world, women have less access to credit than men. Because of both discriminatory property laws and unwritten social customs, women are less likely than men to own high-value assets that can be used as collateral to secure loans. Financ...

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Bibliographic Details
Main Authors: Alibhai, Salman, Achew, Mengistu Bessir, Coleman, Rachel, Khan, Anushe, Strobbe, Francesco
Format: Brief
Language:English
en_US
Published: World Bank, Washington, DC 2017
Subjects:
ACCESS TO FINANCE
MICROFINANCE
GENDER EQUITY
SMEs
MICROENTERPRISE
COLLATERAL
DATA ANALYSIS
Online Access:http://documents.worldbank.org/curated/en/492891498813444777/Algorithms-for-inclusion-data-driven-lending-for-women-owned-SMEs
http://hdl.handle.net/10986/27480

Internet

http://documents.worldbank.org/curated/en/492891498813444777/Algorithms-for-inclusion-data-driven-lending-for-women-owned-SMEs
http://hdl.handle.net/10986/27480

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