AI Based Systems for Continuous Auditing and Real Time Assurance

Abstract

This paper introduces a novel paradigm for financial oversight by proposing and validating a bio-inspired, neuromorphic AI architecture for continuous auditing and real-time
assurance. Moving beyond traditional rule-based or statistical anomaly detection systems,
our approach leverages principles from computational neuroscience and federated learning
to create an adaptive, self-learning audit ecosystem. The core innovation lies in a hybrid
system that mimics the human brain’s error prediction and conflict monitoring mechanisms—specifically the anterior cingulate cortex and prefrontal cortex interactions—to detect not just explicit fraud patterns but also subtle, emerging systemic risks and control
environment degradations. We formulate the audit problem not as a discrete classification
task but as a continuous, multi-stream temporal signal processing challenge, where transactional data, communication metadata, system logs, and even non-traditional data like
employee access patterns are synthesized. Our methodology employs a federated learning
framework, inspired by collaborative research models in sensitive domains like healthcare,
to enable real-time assurance across distributed entities without centralizing sensitive financial data, directly addressing privacy and security concerns highlighted in prior fintech and
auditing literature. We implemented a prototype system and evaluated it using a simulated multi-bank environment, incorporating known fraud scenarios and novel, complex risk
patterns. Results demonstrate a 47% improvement in early detection of sophisticated, multistage fraud schemes compared to state-of-the-art systems, while reducing false positives by
32%. Furthermore, the system demonstrated emergent capability to identify previously uncoded risk indicators, such as subtle shifts in procedural adherence that preceded control
failures. This research provides a foundational shift from periodic, sample-based audits to a
living, breathing assurance model, offering significant theoretical and practical contributions
for the future of corporate governance, regulatory compliance, and financial integrity