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Agnostic Finance
Use Case

Intercompany Reconciliation

An AI agent that extracts intercompany transaction data from multiple ERPs or ledgers of different entities, performs automated matching, identifies discrepancies, facilitates resolution workflows, and suggests elimination entries.

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Process Details

Inputs

Intercompany AR and AP sub-ledger data from all entities, General ledger balances for intercompany accounts

Outputs

Intercompany reconciliation reports (List of matched and unmatched transactions), Prioritized list of discrepancies with suggested reasons, Proposed adjustment and elimination entries

Systems

ERP System (SAP, Oracle NetSuite, Microsoft Dynamics 365)

The Challenge

Manual processes
create real problems.

  1. 1

    High potential for costly errors from manual data handling.

  2. 2

    Significant time and resources are spent on repetitive, low-value work.

  3. 3

    The manual process is difficult to scale without increasing headcount.

  4. 4

    Process bottlenecks lead to delays and missed deadlines.

The Solution

Describe it in English.
It runs deterministically.

  1. 1

    Data Extraction

    Retrieves intercompany payable and receivable balances and transaction details from ERP Systems of participating entities.

  2. 2

    Automated Matching

    Applies predefined matching rules (e.g., based on invoice number, amount, date, reference fields).

  3. 3

    Discrepancy Identification & Prioritization

    Identifies mismatches in amounts, currencies, or missing counterparty transactions. Prioritizes discrepancies based on aging and monetary value.

  4. 4

    Automated Discrepancy Resolution Workflow

    Routes identified discrepancies to the respective entity contacts

  5. 5

    Automated Adjustment & Elimination Entry Suggestion

    Based on resolved discrepancies or standard intercompany settlement processes, suggests adjustment or elimination journal entries for review and posting in the respective ERP Systems.

  6. 6

    Reporting

    Provides reconciliation status, aging of discrepancies, and resolution progress.

Primary Benefits

What you gain with
Kognitos automation.

Increase Efficiency

Dramatically reduce the time and manual effort required to complete the process.

Enhance Accuracy

Eliminate human error to ensure data integrity and reduce financial risk.

Empower Employees

Free your team from monotonous tasks, allowing them to focus on strategic work that requires their expertise.

Improve Scalability

Handle growing volumes of work without a proportional increase in operational costs.

Ensure Transparency

Maintain a complete, auditable trail of every action the AI agent takes, described in plain English.

FAQ

Common questions
answered.

This is a core strength of the agent. It is designed specifically for heterogeneous environments. Using a combination of APIs and secure data connectors, the agent extracts the necessary transaction data (payables, receivables, etc.) from each entity's source system, regardless of the underlying platform. It then standardizes the data into a common format for matching.
It applies multi-level rules that you can configure, such as matching on Invoice Number, PO Number, Amount, and Date. For cross-currency transactions, it can apply the correct foreign exchange (FX) rates for a specified period to validate matches. You can also define matching tolerances to handle minor rounding differences.
The agent creates a complete, unchangeable audit trail for the entire process. This captures every event like: when data was extracted, which rule was used for a match, who was notified of a discrepancy, and who approved the final adjustment. This provides auditors with a transparent, easily verifiable record, strengthening your SOX compliance.
No. To maintain strict financial control and segregation of duties, the agent suggests the necessary journal entries. These suggestions, complete with all supporting documentation, are routed to an authorized reviewer (e.g., a Senior Accountant or Controller) for validation and approval before being manually or automatically posted to the respective ERPs. You always maintain control over what gets posted to your ledgers.
Implementation is a structured process, typically taking 4-6 weeks, depending on the number of entities and ERP systems. The process includes:
Discovery: Mapping your entities, ERPs, and current intercompany processes.
Configuration: Setting up data connectors, defining initial matching rules, and configuring resolution workflows.
Testing: Running a pilot with a subset of entities to validate the process.
Go-Live & Training: Rolling out the agent and training your teams.
The agent provides reports that give management insight into the intercompany process, including.
Reconciliation Status: A high-level view of matched vs. unmatched balances across all entities.
Discrepancy Aging Report: Highlights unresolved items by age and value, showing who is responsible for resolving them.
Resolution Cycle Time: Tracks the efficiency of your teams in resolving mismatches.
The agent is designed to automate the process, not the negotiation. When a complex issue arises, the agent acts as a facilitator. It provides all the relevant data to facilitate discussion and agreement on a resolution. This ensures that human judgment and business context are applied where they are needed most, while the agent handles the operational legwork.
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Challenges

Solution

This use case solution follows these general steps at a high level:

  1. Data ExtractionRetrieves intercompany payable and receivable balances and transaction details from ERP Systems of participating entities.
  2. Automated MatchingApplies predefined matching rules (e.g., based on invoice number, amount, date, reference fields).
  3. Discrepancy Identification & PrioritizationIdentifies mismatches in amounts, currencies, or missing counterparty transactions. Prioritizes discrepancies based on aging and monetary value.
  4. Automated Discrepancy Resolution WorkflowRoutes identified discrepancies to the respective entity contacts
  5. Automated Adjustment & Elimination Entry SuggestionBased on resolved discrepancies or standard intercompany settlement processes, suggests adjustment or elimination journal entries for review and posting in the respective ERP Systems.
  6. ReportingProvides reconciliation status, aging of discrepancies, and resolution progress.

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