Till sidans topp

Sidansvarig: Webbredaktion
Sidan uppdaterades: 2012-09-11 15:12

Tipsa en vän
Utskriftsversion

Predicting likelihood for… - Göteborgs universitet Till startsida
Webbkarta
Till innehåll Läs mer om hur kakor används på gu.se

Predicting likelihood for loan default among bank borrowers

Artikel i vetenskaplig tidskrift
Författare Mohammad Aslam
Senthil Kumar
Shahryar Sorooshian
Publicerad i International Journal of Financial Research
Volym 11
Nummer/häfte 1
Sidor 318-328
ISSN 19234023
Publiceringsår 2020
Publicerad vid Företagsekonomiska institutionen
Sidor 318-328
Språk en
Länkar https://doi.org/10.5430/ijfr.v11n1p...
Ämnesord Loan default factors, Logistic regression, Microfinance, Poverty alleviation
Ämneskategorier Annan samhällsvetenskap

Sammanfattning

© 2019, Sciedu Press. Poverty is a threat to the world. In its extreme form at any part of the world, it will make endanger rest of the world. In fact, it is the source of crime and the worst form of violence. The poor people do not commit any crime but they get punishment out of being bom as a poor that is not controllable in then hand. Microfinance has been designed to eliminate poverty and help marginal and poor people through small income generating activities. The borrowers need capital to materialize their dream, may be in a small amount and microfinance can play important role in this scenario. Through microfinance. small entrepreneurs may acquire necessary inputs to start their business. Both local governments and international agencies are trying to eliminate poverty through microfinance programs, services and guidelines. With this concept. Microfinance has been hosted primarily in Bangladesh. Grameen Bank (GB) has been serving large number of people below poverty level in Bangladesh. However, impact of microfinance is still questionable in several studies. Microfinance used properly and returned back to the lender with stipulated amount and time shows its working effectively for poverty alleviation. Otherwise, there must be loan default and the whole system may be in question. We survey with questionnaire to find out factors contributing to loan default among GB borrowers using binomial logistic regression. The results showed that some factors were crucial for loan default and should be treated properly at the start of lending.

Sidansvarig: Webbredaktion|Sidan uppdaterades: 2012-09-11
Dela:

På Göteborgs universitet använder vi kakor (cookies) för att webbplatsen ska fungera på ett bra sätt för dig. Genom att surfa vidare godkänner du att vi använder kakor.  Vad är kakor?