AI-Driven Automation for Death Claim Processing In Pension Systems: Enhancing Accuracy and Reducing Cycle Time

Abstract

It has been established that processing claims to death in a pension scheme is no better in its administration, wastes time, results in lost income, leads to inaccuracies, and is not in the best interests of the beneficiary because it is an institutional liability. Human verification, incomplete documentation, and other outdated practices can lead to delays in processing time and increase the risk of fraud. Recently, the development of Artificial Intelligence (AI) has enabled the automation of processes, improving accuracy and cycle time to near-negligible levels. The paper discusses explicitly Machine Learning (ML), Natural Language Processing (NLP), and Robotic Process Automation (RPA) in the assessment of AI automation options for death claim processing. The more effective methodology employed in the article is the synthesis of literature, combined with case study research on pension systems globally, to quantify the effects of AI on simplifying decision-making mechanisms by reviewing and detecting fraud cases, and then passing them directly to the beneficiary. Some evidence suggests AI could significantly lessen reported processing time from several months to weeks (or days) and substantially reduce errors. The paper also discusses the ethical and regulatory implications that may arise from AI automation, including transparency, data privacy, and algorithmic bias. The paper suggests that the next step in moving beyond AI automation of pensions is a hybrid approach combining blockchain technology with explainable AI to establish greater legitimacy and consumer confidence. The research is relevant to the field of study and policy, as AI-led automation is viewed as a disruptive innovation that can facilitate sustainable and assured pension administration