-
Research Article
Effect of Interest Rate on Loan Repayment for Small and Medium Enterprises in Kenya
Abdikadir Noor Fidow*
Issue:
Volume 11, Issue 3, September 2026
Pages:
116-123
Received:
27 June 2026
Accepted:
13 July 2026
Published:
10 August 2026
Abstract: The study researched how interest rate, inflation, and economic growth affect loan repayment of small and medium enterprises (SMEs) in Kenya. SMEs contribute Ninety eight percent of the business population and provide employment, economic growth, goods and services for low and middle income population in Kenya. The target population of the study was commercial, micro finances, and online lenders in Nairobi, Kenya. Secondary data was collected from financial lenders in Nairobi. SPSS tools of descriptive and inferential analysis were employed to analyze the data. The result indicated that interest rate is negatively and significantly correlated with loan repayment (r = -.431, p=.000). In the regression analysis result, interest rate is negatively and significantly related to loan repayment (β=-0.564, p=0.015). Inflation and economic growth were positively related to loan repayment, but not significantly. This means that, when lenders charge high interest rates, default rate increases thus reducing loan repayment rate. The study concluded that lenders should reduce interest rate as much as possible in order to reduce default rate and improve loan repayment. Payment period should be also extended to give the borrowers a leeway and reduced payment amount per term.
Abstract: The study researched how interest rate, inflation, and economic growth affect loan repayment of small and medium enterprises (SMEs) in Kenya. SMEs contribute Ninety eight percent of the business population and provide employment, economic growth, goods and services for low and middle income population in Kenya. The target population of the study wa...
Show More
-
Research Article
Cognitive Heuristics and Risk Perception as Determinants of Investment Strategies Among Selected Bank Customers in Nigeria: Evidence from Ondo State
Paul Obogo Ushie*,
Wale Henry Agbaje,
James Adeniyi Demehin,
Foluso Ololade Oluwole,
Toyin Waliu Otapo
Issue:
Volume 11, Issue 3, September 2026
Pages:
124-137
Received:
20 June 2026
Accepted:
21 July 2026
Published:
18 August 2026
Abstract: The proposition by traditional finance theory maintains that investors make rational decisions based on the single motive of maximizing shareholders’ wealth through the relationship between risk and return. However, growing empirical evidence indicates that psychological biases and cognitive processes influence investment decisions in ways that differ from classical predictions. Against this background, the study examined how behavioural finance factors, particularly cognitive heuristic bias and perceived risk–outcome distortion, influence the investment decision-making strategies of customers of selected investment banks in Akoko South-West, Ondo State, Nigeria. A survey research design was adopted, and data were collected from a clearly defined sample of 120 active customers of the selected investment banks. The data were analyzed using Chi-square and ordinary least squares regression techniques. The findings revealed that cognitive heuristic bias explained approximately 29% of the variation in customers’ investment decision quality (β = 0.54, p < 0.01), while perceived risk–outcome distortion explained approximately 34% of the variation in investment decisions (β = 0.59, p < 0.01). Contrary to the assumptions of classical finance theory, greater reliance on heuristics and heightened sensitivity to risk had positive and statistically significant effects on the investment decisions of the respondents. The study concluded that behavioural shortcuts may function as adaptive decision-making mechanisms in situations where financial information is scarce and market conditions are uncertain. Practically, the findings suggest that investment banks should incorporate investors’ behavioural tendencies into product design, customer advisory services, risk communication, and financial education programmes. The study therefore recommends that, behaviourally informed financial literacy policies supported by appropriate regulatory frameworks to improve investor decision-making and welfare.
Abstract: The proposition by traditional finance theory maintains that investors make rational decisions based on the single motive of maximizing shareholders’ wealth through the relationship between risk and return. However, growing empirical evidence indicates that psychological biases and cognitive processes influence investment decisions in ways that dif...
Show More
-
Research Article
Quantifying Cyber Risk Exposure and Risk-Based Pricing of Cyber Insurance: A Thematic Review of Actuarial, Statistical and Machine-Learning Approaches
Raveendran Narasimhan*
Issue:
Volume 11, Issue 3, September 2026
Pages:
138-147
Received:
19 July 2026
Accepted:
26 August 2026
Published:
18 September 2026
DOI:
10.11648/j.ijafrm.20261103.13
Downloads:
Views:
Abstract: Cyber risk has evolved from a niche operational hazard into one of the most consequential and least tractable classes of insurable risk. Insurers continue to rely largely on heuristic and experience-rated underwriting, while the academic literature has produced a rapidly expanding but fragmented body of quantitative models. This review synthesises the peer-reviewed literature on cyber risk quantification and cyber insurance pricing, drawing on a structured search of scholarly databases that returned 199 records, from which 102 studies are critically reviewed. The literature is organised into eight themes: the statistical properties of cyber losses; actuarial and mathematical pricing models; dependence modelling and systemic risk; machine-learning approaches to incident prediction and underwriting; technical risk-assessment frameworks and control-based premium adjustment; the economics of cyber insurance markets; sectoral heterogeneity in cyber exposure; and methods for modelling under data scarcity. Across themes, four persistent findings emerge: cyber losses are heavy-tailed and dynamically non-stationary; dependence among losses undermines classical portfolio diversification and is systematically under-modelled in practice; technical vulnerability metrics and financial loss models remain poorly integrated; and virtually all empirical evidence derives from United States loss databases, leaving emerging markets and firm-level primary data almost unexamined. These gaps motivate an integrated, industry-specific research agenda that couples asset-centric technical assessment (CVSS, FAIR, ISO/NIST alignment) with neural-network incident probability estimation, copula-based dependence modelling and explicit actuarial premium construction. The review concludes by positioning such a framework against the state of the art and identifying the contribution it would make to actuarial science, underwriting practice and regulation.
Abstract: Cyber risk has evolved from a niche operational hazard into one of the most consequential and least tractable classes of insurable risk. Insurers continue to rely largely on heuristic and experience-rated underwriting, while the academic literature has produced a rapidly expanding but fragmented body of quantitative models. This review synthesises ...
Show More
