AI Financial Performance: Automation and Monitoring

Concrete example of AI deployed in a French group: automation of bank reconciliations, dynamic reporting and real-time decision-making based on live data.

In a French industrial group with 420 employees, a DATALIA deployment automated 87% of monthly bank reconciliations and reduced financial statement production from 6 days to 24 hours. The sovereign AI, hosted on-premise and connected to ERPs and management tools, enabled dynamic reporting fed in real-time. Result: data reliability above 99.2% and improved responsiveness of accounting and monitoring teams.

Context: An Industrial Group Facing Financial Data Complexity

The group, operating in France and Belgium, manages 12 production sites and over 300 suppliers. Each month, accounting teams receive over 1,200 supporting documents, of which 800 relate to recurring bank reconciliations. The manual process, fragmented across Excel, the accounting software and an Odoo ERP, generates frequent errors and delays in financial statement production.

The 2023 budget forecast indicates that 15 hours per month are spent on manual data entry and reconciliation, i.e. 180 hours annually. The CFO estimates this cost at over €12,000 per year, excluding input errors corrected afterward. The lack of real-time visibility also prevents monitoring teams from quickly reacting to budget variances.

The challenge is clear: automate repetitive tasks, ensure data reliability and provide dynamic reporting to optimize decision-making.

Problem and Measurable Objectives

The project has three objectives:

• Automate 80% of bank reconciliations within 6 months to free up time for analysis.
• Reduce the financial statement production time from 6 days to 2 business days.
• Implement dynamic reporting fed in real-time, accessible to monitoring teams and management.

These objectives are measurable and tracked using key performance indicators (KPIs), integrated into a shared dashboard.

The CFO also sets an error tolerance level below 1%, compared to 5% currently.

The Solution Deployed: Sovereign AI and Intelligent Reporting

Technical Architecture and Integration

DATALIA recommends and deploys a sovereign, private and self-hosted AI within the group's environment. This architecture is based on:

• A local language model (LLM) for interpreting supporting documents and extracting contextual data.
• A RAG connector (Retrieval-Augmented Generation) linking the AI to historical accounting data, the Odoo ERP and internal databases.
• An automated validation flow for suspicious entries, redirected to the accountants.

These components are integrated via secure APIs, with data encryption in transit and at rest. The entire system is hosted on internal servers, in compliance with GDPR and AI Act requirements.

Bank Reconciliation Automation

The AI analyzes each supporting document (invoices, receipts, transfers) and automatically reconciles it with the accounting entries. Discrepancies or anomalies are flagged with a confidence score. In three months, the automation rate reached 87%, reducing monthly manual workload from 13h to 1h9.

Dynamic Reporting and Data-Driven Decision Making

An interactive dashboard, fed in real-time by the AI, allows monitoring teams to access key indicators: cash flow, margin per product, budget variances, and updated forecasts. Data is presented as dynamic charts, exportable and shareable. Management can thus respond in real-time to market trends.

Results Achieved: Before / After Table

Measurement period: 8 months (January to August 2024). Source: internal group report.

What Didn't Work: Errors to Avoid

The initial deployment encountered two major obstacles:

1. An overly ambitious configuration at launch. The AI was connected to all tools simultaneously, causing latency and data conflicts. The team had to step back and integrate sources one by one.
2. User resistance from accounting teams. Several staff members feared job loss. Targeted training and introductory workshops helped alleviate this concern.

These experiences led to adopting a phased approach and rigorous tracking of user adoption.

Key Lessons for CFOs

Deliverable: Checklist for Framing an AI Project in Finance

1. Objective: Validate technical and business feasibility before deployment.
2. To gather: Current data flows, ERP, reporting tools, user profiles.
3. Method: Map automatable tasks → Prioritize high-volume processes → Identify risks (sensitive data, business rules) → Define KPIs.
4. Output: A requirements document validated by the CFO and CIO, with a phased deployment plan.

Ready to use as-is. Variables in [BRACKETS] to be adapted.

Key lessons learned:

• Start with a limited scope: One type of supporting document or one site allows validating the approach before global deployment.
• Involve teams from the beginning: Show them AI as a collaborative tool, not a replacement.
• Prioritize data quality: AI generates value only if source data is clean and standardized.
• Measure impact from the first days: Early visible ROI strengthens stakeholder commitment.
• Ensure compliance from design: Choosing sovereign AI avoids GDPR and AI Act risks.

How DATALIA Supports CFOs in This Transformation

DATALIA designs sovereign, private and self-hosted AI solutions, specifically tailored to the needs of CFOs and management control teams. Our approach is based on three pillars:

1. Audit & Diagnosis: We identify automatable tasks and assess potential impact in hours and costs.
2. Integration & Deployment: Our AI connects to your ERP (Odoo, SAP, Oracle) and internal tools, hosted according to your security standards.
3. Training & Adoption: We train your teams to use AI, emphasizing the perceived added value.
4. Discover how DATALIA can transform your finance function with sovereign AI.

Frequently Asked Questions

Is on-premise AI as performant as cloud AI?

Yes, for internal data processing tasks. A well-trained sovereign AI, on your historical data, offers equal or superior accuracy with full control over data confidentiality. According to our deployments, user satisfaction rate is 89%.

Can AI replace a CFO or financial controller?

No. AI automates repetitive tasks and calculations. It frees up the CFO to focus on strategic analysis and decision-making. The human role remains central in data interpretation and validation.

In Summary

• Finance automation can free up to 87% of time spent on manual tasks.
• Dynamic real-time reporting improves responsiveness of monitoring teams.
• Sovereign AI ensures GDPR and AI Act compliance without sacrificing performance.
• Phased deployment and targeted training are essential for successful adoption.
• The value of AI lies in enhancing decision-making capacity, not replacing human expertise.

Next Step

Ready to transform your finance function? Start with a free audit of your accounting processes and identify the first applications of sovereign AI in your organization.

Book your call and free audit today with a DATALIA expert: DATALIA →