dc.contributor.author | Ntwiga, Davis B | |
dc.contributor.author | Weke, Patrick | |
dc.date.accessioned | 2017-03-20T08:30:27Z | |
dc.date.available | 2017-03-20T08:30:27Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Ntwiga, Davis Bundi, and Patrick Weke. "Consumer lending using social media data." International Journal of Scientific Research and Innovative Technology 3.2 (2016): 1-8. | en_US |
dc.identifier.uri | http://hdl.handle.net/11295/100617 | |
dc.description.abstract | Consumer credit has been around for a long period of time but the dynamics observable from the consumers
makes it hard to credit score and lend to the consumers. This difficulty results in the poor being excluded from
receiving credit as they lack financial history. We analyze the limitations of the traditional consumer lending
models due to use of historical data, and look at the benefits that could arise by incorporating social media
data in credit scoring process for consumer lending. A review of the research progress made in using social
media data for consumer scoring and lending process is presented. We found that social media data offers
rich, vast and attractive information on changing trends and shifting demographics in credit underwriting of
existing consumers and new consumers with minimal or no financial history. This data advances the lending
process by widening the data set available and capture of new markets that are excluded from financial
services | en_US |
dc.language.iso | en | en_US |
dc.publisher | University of Nairobi | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | Social media data, consumer lending, credit scoring, credit risk | en_US |
dc.title | Consumer lending using social media data | en_US |
dc.type | Article | en_US |