Evaluating Loan Performance in Kenya's Digital Lending Sector: The Role of Credit Risk Management

In Kenya, over 50% of loans from digital lending companies are defaulted by borrowers. These companies often assess borrowers' willingness, rather than their ability to repay loans, which contributes to high default rates and credit risk. The lack of collateral and ineffective credit risk management further exacerbates the problem, hindering the growth of digital lending firms. This study aimed to investigate the impact of risk identification, quantification, and measurement on loan performance in Kenyan digital lending companies. Anchored in modern portfolio theory, asymmetric information theory, and stewardship theory, the study has applied descriptive as well as analytical research design which incorporate correlational and explanatory research design. Data was collected from 108 digital firms using a census sampling technique and analyzed using SPSS version 20. The findings indicated that risk identification, quantification, and measurement positively impact loan performance. The study concluded that effective risk management, including detecting maximum probable losses and monitoring borrowers' cash flows, enhances loan performance. It recommended implementing a robust institutional framework for risk identification and ensuring timely communication of risks to management. The study also suggested that the Central Bank of Kenya should oversee the identification and planning for new risks by digital lending firms.

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Publication Details

Journal
SPIRE - Sciences Po Institutional REpository
Published
2024-10-09
Primary Topic
Microfinance and Financial Inclusion
Type
article
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article

Evaluating Loan Performance in Kenya's Digital Lending Sector: The Role of Credit Risk Management

SPIRE - Sciences Po Institutional REpository
Microfinance and Financial Inclusion
article

Evaluating Loan Performance in Kenya's Digital Lending Sector: The Role of Credit Risk Management

article en

Abstract

In Kenya, over 50% of loans from digital lending companies are defaulted by borrowers. These companies often assess borrowers' willingness, rather than their ability to repay loans, which contributes to high default rates and credit risk. The lack of collateral and ineffective credit risk management further exacerbates the problem, hindering the growth of digital lending firms. This study aimed to investigate the impact of risk identification, quantification, and measurement on loan performance in Kenyan digital lending companies. Anchored in modern portfolio theory, asymmetric information theory, and stewardship theory, the study has applied descriptive as well as analytical research design which incorporate correlational and explanatory research design. Data was collected from 108 digital firms using a census sampling technique and analyzed using SPSS version 20. The findings indicated that risk identification, quantification, and measurement positively impact loan performance. The study concluded that effective risk management, including detecting maximum probable losses and monitoring borrowers' cash flows, enhances loan performance. It recommended implementing a robust institutional framework for risk identification and ensuring timely communication of risks to management. The study also suggested that the Central Bank of Kenya should oversee the identification and planning for new risks by digital lending firms.

SPIRE - Sciences Po Institutional REpository
Kenyatta University (KE)
Openalex Percentile: Top 31%
Microfinance and Financial Inclusion
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