Financial reporting: ensuring the reliability of your reporting data

Your finance department becomes more reliable and faster when reporting data are consolidated and traced. Here is a concrete case study.

The DATALIA team · Published August 2026 · Updated August 2026

Direct answer

Consolidating financial data at the source level, automating reconciliations and tracing every transformation reduces the time to close and errors. This case study shows a measured reduction in manual tasks and a reliable dashboard for finance leadership.

Context

A mid-sized European fintech with 150 employees, multi-entity across Europe, engaged us to improve the reliability of its financial reporting. The finance function faced three problems: recurring differences between accounting and consolidation, a long monthly close period (several days of unplanned work), and a lack of traceability for external audits.

Problem and objectives

Measurable objectives defined by the steering committee:

• Reduce the monthly close time from X days to Y days (quantified target set initially).
• Eliminate re-entries between 3 main systems: ERP, perimeter spreadsheet, consolidation tool.
• Obtain full traceability of adjustments for external audit.

The CFO sought a clear, comparable cost estimate to present the project to the executive committee. The technical scope had to remain compatible with regulatory hosting and the internal security policy.

Solution implemented

We adopted a four-phase approach, designed to be measurable and replicable by a CFO or a financial controller.

1 — Diagnosis and data mapping

We mapped flows from the source systems to the reporting statements: accounting ERP, payroll module, commercial platform, and adjustment spreadsheets. Deliverable: a "source → transformation → destination" matrix with volumes, frequency and owners.

2 — Reduce re-entries through targeted automation

We prioritized integrations according to value (hours saved) and risk (critical errors). Then we automated:

• the daily extraction of journal entries from the ERP;
• automatic reconciliation of intercompany accounts;
• validation of adjustment entries in a workflow with an audit trail.

3 — Governance of transformations and business rules

Each transformation (e.g. commission restatement, currency conversion) was described as an executable rule, tested on a sample and versioned. The rule records the author, date, accounting justification and a minimal unit test.

4 — Trust dashboard and close automation

We delivered a single dashboard displaying: data quality indicators (detected variances), status of close processes, and the list of exceptions to handle manually. Workflows notify owners and retain the history.

Operational deliverables (ready to use today)

Deliverable 1 — Flow prioritization grid

Objective: Identify which flows to automate first to reduce the cost of closing.
To gather: lists of systems, daily volumes, processing time, owner.
Method:
- List all incoming and outgoing flows.
- Estimate hours/month lost per flow.
- Rank by priority = hours × criticality.
Output: Prioritized list [Flow] / [Estimated hours] / [Owner] / [Risks].
Note: Works well for environments with 3–10 systems. Does not replace an IT audit for complex interconnections.

Deliverable 2 — Exception tracking template for the close

Objective: Process exceptions within 48 hours and keep an audit trail.
To gather: validation rules, business owners, SLAs.
Method:
- Define exception types (rates, allocations, intercompany).
- Create workflow: creation → assignment → resolution → validation.
- Log every action (user, date, justification).
Output: Exportable CSV exceptions table + weekly summary.
Note: Useful from the first month. Avoid opening >7 exception categories initially.

Results (before / after)

Measurement carried out over 6 months after deployment, reported to the internal finance team. The figures come from project tracking and activity exports.

What didn't work (and why)

Issue → Why → Fix :

• Initial delays in data ingestion → poor quality of ERP exports → Fix: define export specifications, budget a 5-day cleanup sprint.
• Too many exception categories → overload for owners → Fix: limit categories to 5 priority ones and reopen later.
• Resistance to documenting rules → perceived as administrative overhead → Fix: integrate documentation into the approval interface and make it mandatory for any change.

Key lessons for a CFO

• First measure the real cost of re-entries: hours × average rate. This is the figure presented to the committee.
• Automate high-frequency, low-exception flows. Leave humans handling critical exceptions.
• Version every business rule. An undocumented rule becomes operational debt.
• Plan 20% of the project budget for post-deployment adjustments (cleanup, additional testing).
• Don't compare quotes without identical scope: request the same input/output matrix.

Role of DATALIA

We acted as integrator and operational lead: diagnosis, flow automation, rule definition and user training. DATALIA delivered the technical deliverables and the data governance required to demonstrate an operational return on investment. For details on the product approach, consult DATALIA.App or contact our team via https://www.datalia.app/.

Scaling up: decision checklist for a CFO

Quick checklist to decide whether to start a similar project:

• Do you have more than 40 hours per month lost to re-entries?
• Do your current closes involve 3+ distinct systems?
• Do you have a business lead and an IT lead available 0.5 day/week?
• Does the executive committee require a better audit trail for compliance?

If you answer yes to at least two items, a 4–6 week pilot is appropriate.

Limitations of the approach

This type of intervention greatly reduces mechanical tasks but does not replace business analysis. Complex exceptions still require human judgment. Also, the measured gains depend on the initial quality of exports and the availability of leads to validate the rules.

Next operational step

Run a two-day diagnostic on your critical flows: mapping, estimate of hours lost, and a first prioritization plan. This deliverable enables you to obtain a comprehensible estimate for the CFO and the executive committee.

Frequently asked questions

How much does a reporting reliability pilot cost?

A pilot (diagnostic + automation of a priority flow) is often estimated in person-days: 10–20 days depending on complexity. The actual cost depends on system scope and data access time.

Can we keep spreadsheets while automating?

Yes. The pragmatic approach is to automate exports and validations, then automatically populate the management spreadsheets. This way, manual effort decreases without challenging reporting habits.

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