Exploring the Use of Psychometrics and Data Mining as Novel Screening Mechanisms to Promote the Use of the Islamic Participatory Modes of Financing for SMEs: The Case Study of The Gambia

SMEs are widely acknowledged as engines of economic growth, employment, and innovation, particularly in developing and emerging economies. However, access to finance continues to pose a significant barrier to their development, scalability, and long-term sustainability. Traditional debt-based financing models, largely employed by the conventional financial institutions, often exclude SMEs due to several structural limitations, including the absence of verifiable credit histories, insufficient collateral, weak financial documentation, and informality. These limitations significantly reduce the ability of lenders to assess risk reliably, leading to credit rationing for SMEs. In contrast, Islamic participatory financing modes, such as Mudarabah (profit-sharing), Musharakah (joint venture) and Musharakah Mutanaqisah (Diminishing partnership), present ethical and inclusive alternatives. These financing instruments are underpinned by risk-sharing principles that align well with the economic characteristics and financing needs of SMEs and startups generally.
In theory, such Islamic participatory modes should enhance access to finance for SMEs by shifting the focus from collateral-based lending to partnership-based financing. However, in practice, the widespread application of these instruments particularly by Islamic Financial Institutions has remained limited. This reluctance is largely driven by challenges such as information asymmetry, a lack of mutual trust, and uncertainty regarding the entrepreneurial skills, character, and competence of prospective SME partners. To bridge this gap, this study sought to evaluate the potential value of psychometrics and data mining classification techniques as innovative screening mechanisms to assess SME operators’ trustworthiness, entrepreneurial aptitude, and financial management skills as a conduit to promote the use of the Islamic participatory modes of financing by the Islamic finance institutions for SMEs. This was done in two empirical analyses, beginning with psychometric testing with multiple regressions and concluding with the data mining technique of classification.
The first inferential analysis employed a three-stage psychometric evaluation using multiple regressions. Stage one established firm performance, stage two assessed the potential moral hazard risk uisng SME operator’s trustoworthiness as proxy, and stage three, evaluated the IFI’s decision to finance SMEs with participatory modes based on insights from the first two stages. Results from the first stage revealed that solvency ratio, operating leverage ratio, and financial management skills were significantly associated with firm performance. Variables such as firm age, financial leverage ratio, business sector, business location, entrepreneur’s experience, educational level, age, and gender, all showed positive but statistically insignificant relationships with firm performance. In stage two, entrepreneurial skills of the SME operator, financial management skills of the SME operator, willingness of the SME operator to use participatory financing modes, knowledge level of the SME operator on the Islamic finance principles and products, and firm age, were all significantly related to the trustworthiness of SME operators which was used as a proxy for mitigating moral hazard problem in Islamic participatory financing. In stage three, both mean and factor scores demonstrated that entrepreneurial skills, financial management skills, willingness to use participatory finance, along with both financial ratios (solvency, operating leverage, and financial leverage ratios) and non-financial ratios (firm age, ownership status, respondent’s age, educational level and experience) have a statistically significant influence on IFI’s decisions to deploy Islamic participatory financing. Interestingly, the knowledge level of SME operators on the Islamic finance principle and products showed a negative but statistically insignificant relationship with IFI’s decision to use participatory modes for SME finaning.
In the second inferential analysis, SME respondents were classified into ‘suitable’ or ‘unsuitable’ candidates for financing with the Islamic participatory modes, using four classification algorithms including CART, CHAID, C5.0, and REPTree and criteria such as precision, recall and F-measure. Results from the analysis showed that, the CHAID althorithm outperformed the others with over 78 per cent accuracy for mean scores and 72 per cent for factor scores. The confusion matrix showed that the model correctly classified 73 per cent of suitable SMEs and 84 per cent of unsuitable SMEs using mean scores, and 78 per cent of suitable SMEs and 66 per cent of unsuitable SMEs using factor scores.
In conclusion, the thesis presents a compelling case for incorporating psychometric testing and data mining into SME risk assessment frameworks, especially with regard to using equity-like financing arrangements like the Islamic participatory modes. This integration could significantly enhance the ability of Islamic financial institutions to identify reliable SME partners and expand the use of participatory financing mechanisms.