Product Demonstration, Statement
Compliance and Audit
- The global compliance and audit workforce in the US and Europe is approaching 4 million, driven by escalating regulatory costs.
- Expanding regulatory frameworks creating compliance demands include GDPR, Dodd-Frank, financial AML/KYC, and ESG reporting.
- Traditional workflows are characterized by manual reading of dense regulations, cross-checking internal policies, sampling frontline work, and generating repetitive reports.
- Auditors currently rely on manual sifting of unstructured data to identify issues, creating a high demand for automation.
- Large Language Models (LLMs) are positioned to automate compliance tasks by processing regulatory documents, corporate policies, and financial statements to highlight anomalies and contradictions.
- Unlike current sampling methods, LLMs enable continuous auditing of entire datasets, allowing for the analysis of all records simultaneously rather than limited samples.
- Future capabilities of these tools include the ability to continuously audit every company globally by identifying incomplete records and spotting data anomalies.
- The transcript includes a call to action for entities building solutions in the automated compliance space.