Maximus
Maximus — Automated Citizen Benefits Processing in Government BPO
Situation
Maximus Inc., a US-based government services company with approximately $4.6 billion in revenue (FY2022) and over 39,000 employees, provides business process services to federal, state, and local governments. The company operates citizen contact centers, benefits enrollment programs, eligibility assessments, and health services administration. Many of these processes were labor-intensive: eligibility determinations for programs like Medicaid, SNAP, and unemployment insurance required caseworkers to manually review applications, verify documentation, cross-reference databases, and make determination decisions. Each case could take 30-60 minutes of caseworker time, and error rates of 5-8% required rework and appeals processing. With government budgets constrained and citizen service expectations rising post-COVID, Maximus needed to process more cases accurately at lower cost per determination.
Action
Between 2021 and 2023, Maximus deployed workflow automation across its government benefits processing operations:
- Intelligent document processing: Deployed AI-powered document classification and data extraction tools that automatically categorized incoming documents (pay stubs, identity verification, medical records), extracted relevant data fields, and populated case management systems. This replaced manual data entry that consumed approximately 15-20 minutes per application.
- Rules-based eligibility engine: Built automated eligibility determination engines for standardized benefit programs that could process straightforward applications without caseworker intervention. Applications meeting predefined criteria (complete documentation, clear eligibility) were auto-determined, with caseworkers focusing only on complex or edge cases.
- Automated verification workflows: Integrated with federal and state data sources (IRS, Social Security Administration, state employment databases) for automated income and identity verification, eliminating manual verification steps that previously required phone calls and document requests.
- Chatbot and IVR modernization: Deployed AI-powered chatbots and modernized interactive voice response (IVR) systems for citizen contact centers, enabling citizens to check application status, submit documents, and complete simple transactions without agent assistance.
- Workforce management automation: Implemented automated case routing and workload distribution systems that assigned cases to caseworkers based on complexity, expertise, and current workload, improving throughput and reducing idle time.
Result
- Processing speed: Automated document processing and rules-based eligibility determinations significantly reduced average case processing time, enabling higher throughput per caseworker.
- Error rate reduction: Automated rules engines and data verification reduced eligibility determination error rates, lowering costly rework and appeals processing.
- Revenue growth: Total revenue grew from $3.5 billion (FY2020) to $4.6 billion (FY2022), with automation enabling Maximus to take on higher-volume contracts without proportional headcount increases.
- Operating margin: Automation improvements contributed to operating margin stability despite wage inflation pressure on the government services workforce.
- Citizen experience: Faster processing times and self-service capabilities improved citizen satisfaction scores on government program contracts.
- Timeframe: Automation deployment scaled over FY2021-FY2023.
Key Enablers
- Government clients' post-COVID urgency to modernize benefits processing created receptivity to automation that had previously faced bureaucratic resistance
- Maximus's position as the largest government BPO provider provided sufficient case volume to train AI models and justify automation investment
- Standardized eligibility rules for federal programs (Medicaid, SNAP) were well-suited to rules-based automation
- Cloud-based deployment enabled rapid scaling of automation tools across multiple government client programs
Sources
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