Shari’ah analytics of Riba

Purpose This study aims to explore riba fundamentals from the main Islamic law source, i.e. al-Qur’an, and from the Islamic legal texts (furūʿ al-fiqh) of the five Imam madhhabs, i.e. Ḥanafī, Mālikī, Shāfiʿī, Ḥanbalī and Jaʿfarī. Design/methodology/approach Grounded by Islamicate digital humanities (IDH), this work introduces Sharīʿah analytics, which primarily uses machine learning tools and big data analytics techniques. The machine learning tools used are phyton-based machine learning toolkits, i.e. Orange Data Mining developed by Demšar et al. (2013), and Phyton cloud-based service, i.e. Google Colaboratory (Colab). Data analytics techniques used in this work is text mining. Dataset of al-Qur’ān is from Tanzil Project by Zarrabi-Zadeh et al. (2025), while dataset of furūʿ al-fiqh is from Lange et al. (2021). Findings This study identifies al-Baqarah 275 as the most cited Qur’anic verse across the five madhhabs in their riba discussions. Although Shāfiʿī texts (e.g. Al-Mawārdī’s Ḥawī al-Kabīr) exhibit the highest frequency of riba mentions (472 times), the Ḥanafī school dominates in average riba frequency (175.27 mentions per kitab), while Ḥanbalī scholars show the lowest (42.09). Ribā al-fāḍl and ribā al-nasīʿah are the most discussed types, which we identified in 18 and 10 kitab, respectively. Notably, Al-Sarakhsī’s Mabsūṭ (Ḥanafī) and Ibn Qudamah’s Al-Mughnī (Ḥanbalī) extensively discuss ribā al-fāḍl in currency and agricultural transactions, while Shāfiʿī works emphasise prohibitions on ambiguous sales. Our statistical tests revealed no significant differences in riba mentions across madhhabs, nor in Qur’anic citation patterns. Research limitations/implications The fiqh dataset used in this study is limited to 55 kitab from five madhhabs from Lange et al. (2021), which limits generalisability of the findings due to non-probabilistic sample size. Furthermore, the semi-supervised text mining approach constrained by a 10-word context generated textual data may overlook understated contextual arguments. Practical implications Future research may replicate our Sharīʿah analytics approach to investigate other timely issues, e.g. fundamentals of zakat and waqf, or fundamental of currency for investigating cryptocurrency issues from the Sharīʿah perspective, among others. Originality/value This study offers a novel approach to the study of Sharīʿah within timely issues in Islamic economics debates. This Sharīʿah analytics primarily uses machine learning tools and text analytics to quantitatively examines riba theological foundations, its discussion across the 5 madhhabs, and the similarity of Qur’ānic citations in these juristic discourses.