Record-to-report trusted AI explainer on video
Learn how trusted AI improves accuracy in record to report processes.
The final episode in the Trusted AI series explores how AI-powered automation is revolutionizing the Record to Report (R2R) process area. In this session, Peter Cook from Kognitos and Nisarg Dhakan from Wipro delve into the critical aspects of the R2R process, highlighting why it is a prime candidate for automation and showcasing success stories that demonstrate real-world impact. This event covers:
- Overview of Record to Report
- R2R as an Ideal Candidate for AI Automation
- Real-World R2R Success Stories
Common questions
What is record-to-report and why is AI relevant?
Record-to-report (R2R) is the accounting close cycle: journal entries, reconciliations, consolidation, and financial reporting. AI is relevant because each step involves repetitive document-intensive work with high accuracy requirements where traditional RPA fails on variation.
What does Kognitos automate in the record-to-report cycle?
Journal entry processing, intercompany reconciliation, bank and GL reconciliation, variance analysis, consolidation data gathering, and management reporting preparation. Each step runs with a full audit trail and exception handling for any out-of-tolerance item.
How does hallucination-free AI matter for record-to-report?
Financial close requires exact figures. An LLM that hallucinates a number creates real financial exposure. Kognitos uses deterministic execution for all write-backs: the LLM interprets intent, the neurosymbolic engine guarantees the output matches the instruction exactly.
What ERP systems does Kognitos support for R2R automation?
SAP (S/4HANA and ECC), Oracle Cloud ERP and EBS, Microsoft Dynamics 365, NetSuite, and Workday. Kognitos reads from and writes back to each system without screen scraping or brittle API wrappers.