Infrastructure for Revenue Cycle Management

Revenue cycle management under ASC 606 requires formally documented and machine-queryable revenue recognition rules: performance obligation identification criteria, transaction price allocation methods, recognition timing triggers, and contract modification handling. These must be explicit and structured for programmatic application — the AI executes recognition schedules by applying formal accounting rules to contract and billing data. SOX compliance requires that the revenue recognition logic is auditable and formally defined, not interpreted case-by-case. Billing validation rules and collection prioritization criteria also require formal documentation executable by the system.

Revenue cycle management requires systematic capture of contract terms, order data, billing records, payment events, and customer creditworthiness indicators through defined workflows. Contract intake must follow structured templates ensuring recognition-relevant terms are captured (performance obligations, payment terms, variable consideration). Billing events and payment receipts must be logged through defined processes with complete metadata. Systematic capture ensures the AI has complete contract and billing history to compute accurate recognition schedules and prioritize collections.

Revenue recognition and billing validation require formal ontology: Contract linked to Customer, PerformanceObligations, TransactionPrice, RecognitionSchedule, BillingMilestones, and PaymentHistory. Relationships must be formally defined: PerformanceObligation.hasAllocation.TransactionPriceAmount, BillingMilestone.triggers.RevenueRecognition, PaymentHistory.informs.CollectionPriority. Without this ontology, the AI cannot execute ASC 606 recognition — each recognition event requires traversing contract terms through performance obligation completion to recognition timing with variable consideration adjustments.

Revenue cycle management requires API access to contract and order management systems, billing platforms, GL (for recognition posting), payment processing systems, and customer credit databases. The baseline confirms modern ERP systems have API capabilities for GL data. For revenue cycle management, the critical systems — contract management, billing, and GL — are accessible via API with IT configuration. The AI must query contract terms, post recognition entries, and retrieve payment history programmatically to automate the recognition and collections workflow.

Revenue recognition rules must update when ASC 606 guidance is revised, when new contract types are introduced, and when billing terms change. Event-triggered maintenance ensures the AI applies current accounting standards — when new contract templates are approved, the recognition logic updates to handle new performance obligation structures. Customer creditworthiness profiles must update when payment behavior changes, ensuring collection prioritization reflects current risk. Event-triggered updates prevent the AI from applying outdated recognition rules to new contract types.

Revenue cycle management requires an integration platform orchestrating data flows between contract/order management, billing systems, GL (recognition posting), payment processing, customer master (credit data), and financial reporting. Recognition schedules must feed GL in real-time as performance obligations are completed. Billing validation results must trigger alerts to billing teams. Collection prioritization must consume payment history and credit data from multiple systems simultaneously. An integration platform ensures these data flows are orchestrated with consistent timing and data contracts, preventing recognition-to-billing-to-collection workflow breaks.