Small and community financial institutions increasingly rely on interconnected transaction, payment, lending, accounting, and reporting systems while revenue controls often remain periodic. This study develops and validates the Open Revenue Data Assurance, Integrity & Reliability (R-DAIR) Maturity Framework as the empirical core of an openly deployable, vendor-neutral standard for continuous revenue-data integrity assessment and leakage prevention. The study combined framework design, expert content validation, pilot testing, survey-based maturity assessment, and operational validation across 30 institutions, 240 main respondents, 12 experts, 40 pilot respondents, and 360 institution-month records. Ten validated subdimensions were organized beneath four public-facing domains: Data Quality & Record Integrity, Anomaly Detection & Revenue Assurance, Workflow & Systems Integration, and Workforce Capability. Average relevance and clarity I-CVIs were 0.94 and 0.92. Cronbach alpha ranged from 0.84 to 0.91, composite reliability from 0.87 to 0.93, and AVE from 0.55 to 0.68. Model fit was good (CFI=0.955, TLI=0.947, RMSEA=0.049, SRMR=0.043). The mean maturity score was 2.99. Higher maturity was positively associated with reconciliation completeness (r=0.750), recovery (r=0.788), and automation (r=0.804), and negatively associated with revenue leakage (r=-0.743), detection latency (r=-0.814), unresolved exceptions (r=-0.740), and recurrence (r=-0.745), all p<0.001. The results support R DAIR as a measurable pathway from periodic checking to continuous, preventive revenue assurance suitable for smaller institutions and extensible to SMEs.

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