Incorporating AI-Driven Knowledge Graphs And Natural Language Processing For Astute Interpretation, Summarisation, And The Harmonisation Of Cross-Border Financial Reporting
Keywords:
Cross-Border Compliance, Regulatory Harmonisation, AI SummarisationAbstract
In a context of more complex and globally integrated financial systems, issues of harmonisation in cross-border reporting are intensifying. Regulatory disparities, linguistic variations, data compartmentalisation, and the continued emergence of unstructured disclosures persist as impediments to the efficacy of transparency, compliance, and efficiency initiatives. This research presents a novel fusion of AI-driven Knowledge Graphs (KG) with Natural Language Processing (NLP), which we propose as a potential solution for enhancing financial interpretation and summarisation across jurisdictions. Knowledge Graphs (KGs) serve as organised semantic representations of financial institutions, their attributes, and interrelationships, enabling machines to comprehend and contextualise information. This architecture, when integrated with advanced NLP models such as transformers and specialised large language models (LLMs), can effectively and clearly extract, disambiguate, and summarise financial disclosures, audit reports, and regulatory filings. These features are especially beneficial for multinationals, auditors, and regulators seeking to cross-map diverging financial standards, such as IFRS and GAAP, or to automate compliance mapping. The document delineates a system architecture that leverages multi-source data, entity recognition, relation extraction, and multilingual semantic alignment utilising AI-augmented ontologies. Practical instances from the EU, ASEAN, and North America demonstrate how artificial intelligence-driven systems may streamline manual tasks, identify anomalies in reporting, and generate reconciled summaries for stakeholders across borders. The findings underscore the capability of NLP utilised in Knowledge Graphs, not just for automating reporting processes but also as a foundation for providing intelligent, transparent financial governance solutions.