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Bad data drives bad decisions and rarely surfaces until the cost shows up. A Data Quality Scoring Playbook reads completeness, accuracy, and consistency signals across financial systems to score data quality and flag issues before they propagate into close, forecast, or disclosure.
The Challenge
Data quality issues rarely surface as alerts. They compound silently across systems. By the time a number looks wrong on a report, the underlying issue has been propagating for weeks and the downstream decisions have been made on bad input.
Most finance teams run data quality checks manually each close cycle: matching totals, spot-checking accounts, reviewing exception lists. The checks are repetitive, time-consuming, and miss issues in areas not on the checklist.
Without a continuous quality score per system and per data domain, the team cannot see whether quality is improving or degrading over time. Quality stays a vague concern rather than a tracked operational metric.
How eyko Solves It
A Data Quality Scoring Playbook reads completeness signals (missing fields, blank records), accuracy signals (out-of-range values, format violations), consistency signals (cross-system reconciliation), and freshness signals (timeliness against expected cadence) to score data quality per system and per data domain. It surfaces quality issues before they propagate, decomposes the contributing signals, and recommends specific remediation moves.
The Playbook scored data quality across 14 financial data domains (GL, AP, AR, payroll, inventory, fixed assets, intercompany, tax, treasury, etc.) over the past 90 days. 4 domains forecast material quality risk (worth immediate remediation). 6 forecast moderate quality risk. 4 forecast high quality. Aggregate quality score: 84/100 against a target of 92. The 4 material-risk domains drive 68% of the score gap.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
Data Quality Scoring reads completeness signals (missing fields, blank records), accuracy signals (out-of-range values, format violations), consistency signals (cross-system reconciliation), and freshness signals (timeliness against expected cadence) to score data quality per system and per data domain. The Playbook surfaces quality issues before they propagate, decomposes the contributing signals, and recommends specific remediation moves.
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FAQ
Everything you need to know about Data Quality Score.
Data Quality Scoring is an AI-driven continuous score on financial data quality per system and per data domain using completeness signals (missing fields, blank records), accuracy signals (out-of-range values, format violations), consistency signals (cross-system reconciliation), and freshness signals (timeliness against expected cadence). The Playbook surfaces quality issues before they propagate, decomposes the contributing signals, and recommends specific remediation moves.
The Playbook reads from your ERP and GL (transactional records, master data), source systems (operational data feeding finance), reporting platforms (downstream data consumers), and reconciliation data (cross-system match records). Continuous data feeds from all in-scope systems enable real-time scoring.
Manual data quality checks run once per close cycle and depend on the specific items on the reviewer's checklist. Continuous data quality scoring runs continuously and covers every monitored signal across every domain. The two are complementary, but continuous scoring is what catches issues before they propagate into decisions.
Yes. For each domain with material quality risk the Playbook names the contributing signal (consistency gap, completeness gap, accuracy gap, freshness gap) and recommends a specific remediation move with named owner. Each recommendation projects quality-score impact and downstream-decision-failure reduction.
Join the enterprises replacing weeks of manual analysis with a single prompt. See what eyko Playbooks can do with your data.
