FinTech and AI technologies for Enhancing Evidence Verification and Dispute Resolution in Financial Litigation

Abstract

The digitization of financial services represents the redesigning of evidence creation, storage, and challenging in court. Nonetheless, current verification approaches produce delays for fast-moving digital and multifaceted transactions. The paper implements and tests the performance of combining Artificial Intelligence (AI) and Financial Technology (FinTech) to develop the consistency of evidence verification and accelerate dispute resolution through the context of financial litigation. A techno-legal method is presented and is structured of three pillars, which comprise blockchain system for immutable provenance and accurate transactional timestamping including smart contracts; machine-learning analytics aimed at sensing anomalies and fraud patterns through varied payment and ledgers systems; and RegTech modules, which automate AML/KYC procedures, and which attempt to create auditable compliance records. The three pillars enhance three assurance layers, which comprise analytical inference, provenance integrity, and compliance attestation that is combined to a judicial interpretation layer by supporting understandable outputs deigned for evidences reassessment. Based on a sequence of particular scenarios that involve suspected structuring or layering, disputed transfers, and contractual breaches, the study investigates the way the method produces evidence objects, which are interpretable, traceable, and verifiable according to principles that are admissible and due-process. Furthermore, problems of implementation such as bias control, data governance, model risk, and privacy are studied in this paper. As a result, the method is generally applicable, but is particularly based on justice system digitization efforts, including those recently being applied in Saudi Arabia.