The Role of alternative data in accurately determining credit score for mobile lending on digital wallets in Kenya / Anthony Gathu

By: Contributor(s): Publication details: Nairobi: Strathmore University: 2020.Description: ix,75pSubject(s):
LOC classification:
  • HF 5439.G388 2020
Online resources: Summary: The increased call for global financial inclusion especially for the low income earners, has resulted to increased use of mobile lending on digital wallets. The purpose of this study was to describe the role of alternative data in accurately determining credit score for mobile lending on digital wallets in Kenya. Alternative data as independent variables included social network data, mobile phone data and transaction data. The study employed a descriptive survey design to meet the research objectives. Primary quantitative data were collected using questionnaire tool. The survey was conducted to a 350 sampled respondents of mobile lending application users; where 230 were individuals while 120 were informal micro enterprises using mobile money applications. Scientific and non-probability sampling methods were used. Descriptive analysis and multivariate analysis through ordinary linear regression was used to develop the model of the study. Also, principal component analysis was conducted to describe the dimensionality of the dataset. Reliability and validity of the research instruments was determined to ensure that the information gathered addresses the research problem. Diagnostics tests such as normality test and multicollinearity tests were performed. The study findings on regression analysis to determine the relationship between social network data, mobile phone data and transaction data and credit score for mobile lending on digital wallets established that of the three independent variables of the study; there was significant positive relationship between transaction data and credit score for mobile lending on digital wallets in Kenya. That is, consumers’ increased transaction records improves their credit score. The results also revealed that there was insignificant positive relationship between social network data and credit score for mobile lending on digital wallets. Lastly, findings revealed that there was a significant inverse relationship between mobile phone data and credit score for mobile lending on digital wallets. On policy implications, the study recommends that both the government and mobile lending providers should design clearer policy frameworks that streamline the use of alternative data such as transaction records of consumers. Also, there is need for mobile wallet providers to adhere to regulations of privacy and educating their borrowers on the importance of having accurate information on their social media accounts that reflects their personalities. This also formed the knowledge contribution of the study. Since this study was carried out on individuals and informal micro enterprises, this study recommends that a similar study should be undertaken in the future but with Fintech or mobile lending providers as the target respondents.
Reviews from LibraryThing.com:
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Call number Status Date due Barcode Item holds
Thesis Thesis Strathmore University (Main Library) Special Collection HF 5439.G388 2020 Not for loan 26150
Total holds: 0

The increased call for global financial inclusion especially for the low income earners, has resulted to increased use of mobile lending on digital wallets. The purpose of this study was to describe the role of alternative data in accurately determining credit score for mobile lending on digital wallets in Kenya. Alternative data as independent variables included social network data, mobile phone data and transaction data. The study employed a descriptive survey design to meet the research objectives. Primary quantitative data were collected using questionnaire tool. The survey was conducted to a 350 sampled respondents of mobile lending application users; where 230 were individuals while 120 were informal micro enterprises using mobile money applications. Scientific and non-probability sampling methods were used. Descriptive analysis and multivariate analysis through ordinary linear regression was used to develop the model of the study. Also, principal component analysis was conducted to describe the dimensionality of the dataset. Reliability and validity of the research instruments was determined to ensure that the information gathered addresses the research problem. Diagnostics tests such as normality test and multicollinearity tests were performed. The study findings on regression analysis to determine the relationship between social network data, mobile phone data and transaction data and credit score for mobile lending on digital wallets established that of the three independent variables of the study; there was significant positive relationship between transaction data and credit score for mobile lending on digital wallets in Kenya. That is, consumers’ increased transaction records improves their credit score. The results also revealed that there was insignificant positive relationship between social network data and credit score for mobile lending on digital wallets. Lastly, findings revealed that there was a significant inverse relationship between mobile phone data and credit score for mobile lending on digital wallets. On policy implications, the study recommends that both the government and mobile lending providers should design clearer policy frameworks that streamline the use of alternative data such as transaction records of consumers. Also, there is need for mobile wallet providers to adhere to regulations of privacy and educating their borrowers on the importance of having accurate information on their social media accounts that reflects their personalities. This also formed the knowledge contribution of the study. Since this study was carried out on individuals and informal micro enterprises, this study recommends that a similar study should be undertaken in the future but with Fintech or mobile lending providers as the target respondents.

There are no comments on this title.

to post a comment.

© Strathmore University Library
Madaraka Estate, Ole Sangale Road | P. O. Box 59857 - 00200 City Square, Nairobi, Kenya
(+254) (0)703 034 000/200/300 | (+254) (0)20-607498