Accounting Data Management
Accounting data management is the framework that guarantees financial data is complete, accurate, traceable, and accessible within a modern accounting system such as ReAI. When data is managed systematically, the organisation can automate several processes, strengthen internal controls, and deliver high-quality reports.
Section 1: What is accounting data management?
Accounting data governance encompasses policies, roles, processes, and technology that control the lifecycle of financial data. The strategy should be closely aligned with the company’s internal control and support the requirements of the Companies Act.
| Element | Description | Example in ReAI |
|---|---|---|
| Policies | Documented rules for data quality, access, and storage | Guidelines for attachment structure and approval workflows |
| Roles | Dedicated owners for data quality and access management | Controller responsible for approving integrations |
| Processes | Controls that ensure data correctness | Automatic validation of vouchers against account and VAT codes |
| Technology | Tools that monitor and document data flow | Data lake in accounting connected to ReAI |
Section 2: Roles and Responsibilities
Effective management requires clear role delineation:
- Data owner: defines standards for chart of accounts, dimensions, and reporting structures.
- Data manager: monitors data quality and resolves discrepancies in collaboration with the accounting team.
- Technology owner: responsible for integrations and authorisations within ReAI and related systems.
- Audit contact: ensures documentation for controls is available for auditors.
ReAI can assign tasks through role-based access controls so that each user only sees the data relevant to their responsibilities, aligning with role-based access management .
Section 3: Critical processes for data quality
To handle the volume of transactions in modern accounting systems, the organisation must establish automated controls:
- Integration Validation: ensuring API streams and file imports contain complete and correct data fields (API Integration ).
- Document Standardisation: mandatory metadata for supplier, dimension, and VAT code before posting.
- Periodic Reconciliations: automatic matching against bank statements, the ledger, and data warehouses.
- Change Log: traceable record of manual corrections and deletions.
The table below illustrates how these controls relate to specific activities in ReAI:
| Control Area | Activity in ReAI | Documentation |
|---|---|---|
| Incoming document flow | Validated voucher templates | Log in ReAI and report in Data Lake |
| Master data changes | Two-step approval for chart of accounts | Chart of Account Update Checklist |
| Reporting | Continuous reporting | Export with version control |
| Audit trail | Automatic journal entries | Auditor’s access to history |
Section 4: KPIs for data governance in accounting
Data quality metrics should be reviewed weekly to identify deviations. Common KPIs include:
- Percentage of attachments passing automatic checks on first attempt.
- Time from voucher receipt to completion of payment processing .
- Number of master data changes with documented approval.
- Coverage of audit trails across modules and integrations.
ReAI provides these KPIs via an accounting dashboard so that financial management can monitor progress continuously.
Section 5: Common challenges and solutions
| Challenge | Consequence | Measures |
|---|---|---|
| Lack of ownership | Unclear priorities | Assign a data owner for each data stream |
| Unstructured documentation | Increased auditing time | Standardise folders and metadata |
| Unattended integrations | Risk of errors | Monitor API logs and set up notification rules |
| Limited change control | Breach of accounting policies | Require two-step approval for chart of accounts and other master data changes |
Section 6: How to get started
- Map all sources of financial data and assign responsible roles.
- Develop a governance policy covering data quality, availability, security, and archiving.
- Prioritise automation of controls in ReAI for high-risk processes.
- Conduct monthly reviews to log and resolve KPIs and deviations.
- Keep the board informed about governance status through dedicated sections in reports, for example alongside board fees .
Effective accounting data management provides reliable insights, faster reporting, and more secure decision-making. With a comprehensive governance model in ReAI, automated financial processes become scalable and compliant.