AI Workflow for Proactive Credit and Refund Issuance for Service Interruptions

This workflow eliminates the costly, manual bottleneck of processing individual customer claims after an outage. By automatically monitoring confirmed outage durations from the OMS and SCADA systems, it applies predefined credit rules—such as state-mandated compensation for outages exceeding a threshold—and executes the refund in the CIS and billing system. The operational upside comes from guaranteed policy compliance, reduced administrative labor, and the significant customer goodwill generated by proactive resolution, directly improving CSAT and reducing call volume related to compensation inquiries.

Implementation requires integrating the orchestrator with the Outage Management System (OMS), Customer Information System (CIS), and billing engine. Key controls include configurable approval gates for high-value credits, exception routing for edge cases to human reviewers, and comprehensive audit trails for regulatory compliance. The architecture must handle data quality variances in outage timestamps and include rollback logic for any failed transactions, ensuring financial accuracy and customer trust.

This workflow automates a high-volume, low-margin compliance task: applying regulatory or company-mandated credits for service interruptions. It eliminates the manual bottleneck of customers filing claims and agents verifying outage durations against SCADA and CIS data. The operational upside comes from guaranteed policy adherence, reduced administrative labor, and proactive customer satisfaction improvements that mitigate churn risk following disruptive events.

Implementation integrates with the Outage Management System (OMS), Customer Information System (CIS), and a configurable policy engine. The orchestrator agent validates the outage duration, retrieves the affected account, and applies the correct credit formula. Controls include pre-approval thresholds, exception routing for edge cases to a human queue, and a full audit trail for regulatory compliance. The system deploys as a containerized service, polling the OMS event log or reacting to webhooks.

Phase 1 establishes the core detection and calculation engine, minimizing initial risk. An orchestration agent, built on LangGraph, ingests confirmed outage closures from the Outage Management System (OMS) and customer data from the CIS. It applies jurisdiction-specific credit rules (e.g., $25 for >24 hours) to generate a batch of proposed credit memos. This batch is routed nightly to a human-in-the-loop queue in ServiceNow for review and approval before any financial system touch, validating logic and building operational trust.

Phase 2 introduces automation gates and direct system integration, scaling the operational benefit. Approved memos are posted autonomously to the Customer Information System (CIS) and billing engine via secured APIs. The orchestrator then triggers omnichannel notifications (SMS, email) to affected accounts. Phase 3 adds predictive analytics, using historical outage patterns to pre-calculate potential credits during major storms, enabling near-instant issuance post-restoration. Each phase includes robust observability dashboards and rollback procedures, ensuring financial controls and auditability are never compromised.

This workflow automates a high-volume, compliance-sensitive financial operation. It triggers when a confirmed outage duration from the Outage Management System (OMS) exceeds a policy or regulatory threshold (e.g., 4+ hours). The AI agent retrieves the affected account list from the Customer Information System (CIS), applies the correct credit formula, and generates a batch for the billing system. This eliminates manual data reconciliation between OMS and CIS, reduces administrative labor by 80%, and ensures 100% policy adherence, directly improving customer satisfaction and regulatory audit readiness.

Operational rollout requires phased deployment, starting with non-critical residential accounts. Key controls include a pre-execution approval gate for credits above a defined dollar amount, routed to a supervisor dashboard. A mandatory 72-hour post-issuance review period allows for customer dispute intake via the standard service channel. The system must integrate with the utility's existing audit trail (e.g., ServiceNow, SAP) to log every decision's rationale, policy version, and affected data points, creating a defensible record for regulators and internal compliance teams.

Scoping this workflow begins by mapping the data flow from outage confirmation to credit issuance. You'll need to integrate your Outage Management System (OMS) or SCADA for confirmed outage durations, your Customer Information System (CIS) for account and policy data, and your billing engine for transaction posting. The core logic applies regulatory rules (e.g., California's Rule 14) or internal policies to calculate credit amounts, requiring a rules engine or coded business logic layer. Exception handling for edge cases, such as overlapping outages or critical care customers, must be designed into the orchestration from day one.

Implementation requires a phased rollout, starting with a pilot for a single outage cause or customer segment. Build the orchestrator using a framework like LangGraph to manage state and agentic steps between systems. Critical controls include pre- and post-execution data validation, a human-in-the-loop approval gate for high-value credits, and comprehensive audit logging for regulatory compliance. The final architecture must support real-time observability into credit volumes, exception rates, and customer sentiment impact to prove ROI in reduced manual processing cost and improved CSAT.