Optimizing Business Rule Engines Reduces Trade Finance Compliance Errors: A Practice-Based Framework - Mancenido, Alvin; Tumaroy, Leanne Aireca; Go, Michelle; Mahilum Jr., Teodulfo; Magno, Rosemarie (JPAIR Multidisciplinary Research, 2026)
Trade finance compliance has become increasingly complex as financial institutions navigate evolving anti-money laundering, know-your-customer, and environmental, social, and governance requirements across global markets. Business rule engines have emerged as essential automation tools, yet their optimization remains insufficiently explored in banking contexts. This narrative literature review synthesizes evidence from 53 sources across six continents to develop a practice-based framework strengthening rule engine design quality, governance features, stakeholder involvement, and policy integration. Evidence from regulatory studies, banking analyses, and international fintech research reveals four mechanisms enhancing compliance performance: high-quality rule design reduces processing errors by 30-45 percent through modular architecture and version control; governance features including audit trails and explainability improve transparency and regulatory defensibility; stakeholder involvement through participatory design increases system usability and adoption by 25-40 percent; and policy integration aligning rule logic with regulatory intent reduces compliance breaches by embedding statutory requirements directly into executable logic. The study concludes that business rule engine optimization requires systemic alignment of technical architecture, organizational governance, and regulatory frameworks rather than isolated technological enhancement. The proposed framework offers banks a validated model for achieving robust, auditable, and efficient compliance automation in trade finance operations.