Risk‑Based Counterparty Due Diligence Framework for the Crude Segment: Case Study of PT Pertamina (Persero)

Abstract

This paper develops and applies an integrated risk-based counterparty due diligence framework for Pertamina’s crude segment, combining a structured questionnaire with Fuzzy Analytical Hierarchy Process Fuzzy AHP and TOPSIS. The framework operationalizes four risk domains, legal compliance, corporate image, operational performance, and financial management, by converting qualitative judgments from experts and counterparties into probability–impact scores and normalized risk indices. Expert judgements gathered via a Focus Group Discussion are modeled using Fuzzy AHP to derive uncertainty-aware weights that emphasize operational 0.45 and legal compliance 0.30 risks, with financial management 0.20 and corporate image 0.05 playing supporting roles. These weights are applied to indicator-level indices from five crude counterparties CRD-01–CRD-05 to obtain composite risk scores, which are then processed using TOPSIS to compute closeness coefficients and produce a transparent ranking relative to an ideal low-risk profile. The empirical results show that all assessed counterparties pass minimum compliance screening and fall predominantly within Low to Moderate and Moderate risk bands, with operational and financial dimensions emerging as the dominant sources of residual exposure. The resulting Counterparty Risk Ratings provide a direct link to Pertamina’s risk appetite, enabling differentiated decision rules such as standard approval, conditional approval with enhanced covenants, or restricted engagement. The study demonstrates that integrating Fuzzy AHP and TOPSIS into counterparty due diligence can enhance the rigor, transparency, and defensibility of crude supplier evaluations, while also highlighting limitations related to sample size, reliance on subjective judgments, and opportunities for incorporating longitudinal and more objective performance data in future applications. The integrated use of Fuzzy AHP for deriving domain and sub‑criterion weights, combined with TOPSIS for ranking crude counterparties, allows Pertamina to move from qualitative checklists to a traceable, quantitative risk rating. This integration strengthens methodological rigor (through consistency‑checked expert weights), transparency (through explicit criteria and weights), and defensibility (through a documented link from raw scores to final ratings).