Insurance finance functions continue to encounter challenges from fragmented policy, claims, broker, bank, and reinsurance data, even when core underwriting and claims platforms are digitally advanced. This review evaluates the potential for intelligent automation to transform receivables, payables, and reinsurance finance processes into a unified, controlled operating system instead of isolated efficiency initiatives. A structured integrative review was conducted, drawing on peer-reviewed research and credible regulatory or standard-setting publications from 2020 to 2025. Evidence was systematically coded by process scope, technology, control design, performance effects, implementation conditions, and insurance-specific accounting requirements. The findings show that robotic process automation is most effective for stable, rule-based activities, while document intelligence, machine learning, application programming interfaces, workflow orchestration, and process mining extend automation to unstructured documents, exception prediction, continuous reconciliation, and operational monitoring. Automation of receivables enhances cash application, ageing visibility, dispute routing, and collection prioritisation. Automation of payables improves invoice capture, matching, approval, duplicate detection, and payment control. Reinsurance automation delivers additional value through contract-data standardisation, bordereaux validation, ceded-premium calculation, recoverable tracking, settlement matching, and IFRS 17 data lineage. Realising these benefits depends on process redesign, master-data quality, segregation of duties, human review of material exceptions, cyber resilience, and accountable model governance. This paper presents an integrated target architecture, a staged maturity pathway, and a balanced performance framework encompassing speed, accuracy, liquidity, compliance, resilience, and stakeholder outcomes.