Digitalisation of the finance function: where to start?

Updated April 2026 - Digitalising the finance function is not about accumulating software licences. The objective is to make financial data more reliable, speed up the main workflows and give management a faster and clearer view of performance. In 2026, the most effective projects start from operational friction points, not from a software vendor's feature list.

See also SME digitalisation, AI and partner digital solutions and e-invoicing and ERP integration.

Before discussing tools, you need to identify the workflows where manual effort, delays and error risk are highest:

• invoicing and collections: automated invoice issuance, electronic transmission, receipt tracking and payment reconciliation;
• procurement and approval workflows: replacing email-based purchase approval chains with structured workflows that create an audit trail;
• cash visibility and bank reconciliation: automated matching of bank statements against accounting records, reducing the manual reconciliation cycle from days to hours;
• reporting and KPIs: building dashboards and management reports that are automatically populated from source systems rather than assembled manually in spreadsheets.

These four pillars form the minimum foundation for a successful finance function digitalisation. Companies that start elsewhere often spend budget on features nobody uses.

Several structural forces are accelerating transformation this year.

The mandatory electronic invoicing reform from 1 September 2026 makes digital workflows a compliance requirement, not just an efficiency choice. Companies must be able to send and receive structured invoices in the formats mandated by the reform.

The RSM/DFCG Observatory on SME/ETI digitalisation reveals that 38% of companies have not yet addressed the e-invoicing transition, down from 44% in 2022. The gap is closing, but one in three companies remains exposed.

At the same time, the combination of AI-assisted document reading and bank feed automation has significantly lowered the barrier to entry for SMEs. Capabilities that were reserved for large groups five years ago are now accessible with standard tools.

The 2026 PwC/DFCG study also highlights that finance departments must now respond to a triple challenge: contributing to business model reinvention, guaranteeing stakeholder trust, and combining operational efficiency with career attractiveness.

Hayot Expertise advice: start by mapping the current flows. The most valuable digitalisation is often the one that eliminates double data entry before adding complexity. A well-executed basic workflow always delivers more than a sophisticated tool that is poorly adopted.

The first concrete step is an honest assessment of the current state. Recurring symptoms in SMEs and mid-cap companies are well documented:

• accounting closing cycles stretching beyond the 15th of the following month;
• unexplained bank variances and reconciliations handled in emergency mode;
• opaque purchase approval chains where nobody knows who approved what;
• management reporting delivered too late to inform decisions;
• no cash forecast beyond 30 days.

Each of these friction points represents a priority project. The classic mistake is trying to tackle everything simultaneously. You need to prioritise by business impact and implementation complexity.

Certain implementations deliver measurable ROI within weeks:

• OCR and document capture: optical recognition eliminates manual entry of supplier invoices. Current solutions achieve automatic labelling rates above 90% on standard document types.
• Automated bank reconciliation: matching rules based on amount, date and counterparty eliminate most of the manual lettering work.
• Structured purchase approval workflows: a digital approval circuit with configurable thresholds creates an audit trail and eliminates email back-and-forth.
• Automated monthly dashboards: standardised reporting, fed directly from the accounting software, replaces hours spent consolidating Excel files.

These projects carry low risk, controlled cost and rapidly visible results. They also build team buy-in, which is essential for what follows.

Digital tools without governance often generate more confusion than the manual processes they replace. Three structural decisions must be made before deployment:

Source of truth: for each data type (customers, suppliers, items, accounts), which system is authoritative? If the CRM and the accounting software each maintain their own customer master data, discrepancies are inevitable.

Access rights and segregation of duties: who can create a supplier? Who can approve a payment? Who can modify a VAT rate? Digitalisation must not weaken internal controls — it should strengthen them.

Cadence and responsibilities: who owns each process? How frequently is data reviewed? Who handles rejections and anomalies? These rules must be documented and known to everyone.

The RSM/DFCG Observatory notes that 74% of CFOs report being involved in strategy definition with general management. This central position legitimises their role in enterprise data governance.

An often-underestimated aspect of finance function digitalisation is its impact on recruitment and retention. According to the RSM/DFCG Observatory, 52% of respondents consider the level of digitalisation an asset for attracting talent.

Finance professionals, particularly recent graduates, no longer want to spend most of their time on repetitive data entry. They expect modern tools that allow them to focus on analysis, advisory and performance management. A digitalised finance function becomes a recruitment argument in its own right.

Several mistakes recur systematically in transformation projects:

• tool stacking: each year, a new need calls for a new tool, with no overall vision. The finance director must take a step back and ensure the coherence of the information system.
• underestimating change management: resistance to change is not solved by a two-hour training session. Upfront communication, team involvement and transition management are essential.
• neglecting data security: digitalisation widens the attack surface. Cybersecurity questions must be addressed upfront, not as a patch after an incident.
• ignoring master data quality: a powerful tool fed with inaccurate data will produce wrong results with mechanical regularity.