Accruals for Pending Invoices
At the accruals cut-off, the Accruals Co-Pilot queries the Invoice Processing Co-Pilot to identify all pending invoices and dynamically adjusts the accrual list as new information emerges.
Key Features
Data synchronization at cut-off
On the accruals cut-off date, the Hyperbots Accruals Co-Pilot initiates a query to the Hyperbots Invoice Processing Co-Pilot for a real-time list of all invoices that have been received but remain unposted or pending.
Status and criteria check
The Invoice Processing Co-Pilot returns invoice details—such as vendor name, invoice amount, due date, and service delivery period—enabling the Accruals Co-Pilot to identify which invoices meet the criteria for accrual (e.g., services rendered or goods received prior to the cut-off, but invoice not yet recorded).
Accrual candidate listing
Using the returned information, the Accruals Co-Pilot compiles a dynamic list of pending invoices that are eligible for accrual. This ensures that any invoice not fully processed by the accounting system is ready to be accrued, preventing understatement of liabilities.
Dynamic adjustment of accrual window
If the accruals window is longer or if certain invoices remain unbooked after the initial cut-off sweep, the Accruals Co-Pilot adjusts its filters and time horizons. This iterative process ensures newly identified pending invoices are added to the accrual list before the final close.
Continuous dialogue between co-pilots
Throughout the accrual closing process, the Accruals Co-Pilot continues to “speak” to the Invoice Processing Co-Pilot, refreshing the list as invoices get posted or new pending invoices surface. This ensures the accrual list remains current and accurate up to the actual close date.
Controlled visibility and reporting
Finally, the Accruals Co-Pilot presents the finance team with a clear, up-to-date accrual register that includes all pending invoices identified. Any changes—such as additional invoices discovered or previously listed invoices posted—are reflected in near-real time, improving the accuracy and transparency of the closing process.
80%
Accrual processing cost
Co-pilot reports all accrued expenses using AI eliminating the need for manual accruals completely
<5%
Variance in accured Vs actual costs
Co-pilot identifies all expenses comprehensively for all type of scenarios through data using AI.
Human Errors
Accrual reversal
Month end closing pressure
Auditability
VALUE PROPOSITION
Why Hyperbots Accruals Co-Pilot
Hyperbots Accruals Co-pilot automates accrual identification, booking, and reversal processes with high configurability and accuracy, ensuring timely and compliant financial reporting while reducing manual effort and errors.
Why Hyperbots Agentic AI Platform?
Finance specific
Best-in-class accuracy
Synthesis of unstructured and strutured finance data
Pre-trained agents with state of the art models
Company specific inference time learning
FAQs: Accruals for Pending Invoices
How does the Hyperbots Accruals Co-Pilot initially identify which invoices are pending at the accrual cut-off date?
What role does the Invoice Processing Co-Pilot’s returned data (e.g., vendor, amount, due date) play in determining whether an invoice qualifies for accrual?
In what ways does the Accruals Co-Pilot ensure that invoices identified for accrual remain accurate if the accrual window extends beyond the initial cut-off?
How do ongoing communications between the Accruals Co-Pilot and the Invoice Processing Co-Pilot help maintain an up-to-date accrual list throughout the closing process?
What happens to the accrual list when previously pending invoices are finally posted after the initial cut-off query?
How does the Accruals Co-Pilot’s dynamic filtering and time horizon adjustments prevent liabilities from being understated?
What benefits do finance teams gain from having a near-real-time, controlled visibility of all pending invoices in the accrual register?
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