Background
Across industries subject to regulatory standards and compliance requirements, audits and inspections by humans are crucial for ensuring adherence to guidelines and mitigating risks. However, the manual process of identifying compliance issues and assessing risks from the data gathered can be time-consuming and prone to oversight. As the complexity of regulations increases, there is a growing need for innovative solutions to streamline end-to-end audit inspections and enhance accuracy.
Challenge
A global audit company faced challenges reviewing the data collected by their auditors and inspectors. The manual review of vast amounts of data and documentation made it difficult to identify potential compliance breaches and assess associated risks in real-time. They needed a solution to augment its audit processes, enabling proactive risk identification and ensuring their customer’s compliance with regulatory standards.
Solution
Using Librios they tested AI-driven technologies to enhance the interrogation of audit and inspections data, leveraging context using data detection prompts, analytics to identify risks and map non-conformances to clauses in regulatory standards.
Implementation
•Data Integration and Analysis: Aggregated audit outcomes and using our data detection tools information was extracted and structured from various sources, including reports, non-conformances, and corrective actions, allowing operations teams to identify patterns and trends indicative of potential compliance issues.
•Prompt behaviour: By training AI models on past inspection findings and regulatory requirements, the company could prioritize audit focus areas and allocate resources more effectively while informing the Supplier of reoccurring issues found.
•Visualization and Reporting: Key audit data, key performance indicators, and risk ratings were sent via API into PowerBI for visualizing and returned to the platform as generated graphs for embedding into reports. Operation teams could access real-time insights, track improvements, and explore resources to help impact various interventions.
Results
The integration of AI across audit inspections yielded significant outcomes:
•Improved Efficiency: AI-driven tools reduced the time and resources required to analyse audit inspection results, enabling the company to identify risks and compliance issues more efficiently.
•Enhanced Repeatable Accuracy: Improved the accuracy of risk identification and compliance assessment by minimizing human error and providing insights into complex regulatory requirements.
•Increased Compliance: By leveraging GenAI and GenBI to ensure compliance with regulatory standards, enhancing trust with regulatory agencies and customers.
Conclusion
By harnessing the power of AI Librios transformed analysis of audit data, enabling proactive risk identification against Standards and produced reports at a holistic theme view. This case study demonstrates the transformative potential of AI in streamlining data processing, mitigating risks, and enhancing overall organizational performance in regulated industries.
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