Mission
At Supervizor, our mission is to give finance teams full confidence in their numbers — before the auditors arrive, before the quarter closes, before the damage is done.
We believe every finance team should be able to continuously monitor the totality of their own data: across every entity, system, and geography, without depending on external auditors or internal technical resources.
In a world where financial complexity only grows, we give finance and audit teams the autonomy to detect risks earlier, understand them deeper, and act faster.
Solution
Supervizor is an analytics platform providing 350+ ready-to-use checks to continuously detect anomalies in financial data. It monitors 100% of transactions across all ERPs, refreshes data automatically, and requires no IT or data science skills. Finance teams can run controls that used to take days in a matter of minutes, freeing them from manual, repetitive work and giving them more time for analysis, judgment, and higher-value contributions.
Built on this foundation, two AI capabilities take the platform further:
AI Insights automatically prioritizes the most critical findings, so teams know exactly where to focus. It cuts through noise to provide the most relevant insights, whether that’s investigating a specific supplier, validating a closing entry, or escalating a risk to the CFO.
AI Xplore connects tools like Microsoft Copilot, Claude, or ChatGPT directly to Supervizor’s engine, enabling natural language queries on live financial data, with full traceability. Controllers and finance managers can now interrogate their data in seconds, without waiting on IT, without exporting spreadsheets, and without losing the audit trail.
Supervizor also powers the rise of agentic finance: ensuring agents work from accurate, complete data — and act within the right boundaries.
Success story with Orange
Yes. During a webinar, Hélène Peel, Director of Internal Audit at Orange (Belgium), shared how Supervizor played a critical role in helping them manage massive volumes of data for their SOX (Sarbanes-Oxley) compliance, specifically regarding fraud management and the override of controls.
Faced with a volume of 1.2 million accounting entries (a task she noted was humanly impossible to process manually), Orange used Supervizor to automatically identify anomalies. The platform successfully filtered this massive dataset down to just about 100 anomalies, which ultimately led to 10 highly relevant issues requiring a deep-dive investigation.
Furthermore, she mentioned that Orange’s external auditor (Deloitte) reviewed this process and acknowledged that Supervizor’s intelligent sampling approach yielded better results than traditional random sampling techniques.
Analysis of 1M+ manual journal entries at Orange SA
Scope: Orange SA feeds all manual journal entries into Supervizor — around 45,000 entries per year, representing 1.6 million lines. The control then filters out purely analytical entries and any entry below €100K, keeping only those with an accounting impact on the closing period.
Objective: The goal is to surface the most atypical manual entries so that the team can focus its review where it matters. A flagged entry is not necessarily wrong — it simply has an unusual profile that warrants a closer look.
Methodology: Each entry is run through 25 controls, drawing on the Supervizor reference library, a behavioural algorithm that flags entries deviating from usual patterns of amount, account and user, comparisons against budget and forecast, and a 457-word watchlist of sensitive terms. Each entry is then scored on a 0–100 scale so the team can tackle the most atypical entries first.
Key findings (Nov 2025): The work led to a material reduction of long-standing provisions, both in number and in amount, and highlighted that justifications provided by controllers remain insufficient. P&L-impacting entries proved to be the highest-value targets. Next steps include new controls to detect aged entries via label patterns (e.g. T12022, ANNEE2022) and entries likely split to stay under thresholds.
Impact
Supervizor changes what finance teams can deliver. By moving from periodic, sample-based reviews to real-time monitoring of every transaction, finance functions gain something beyond better controls: they gain speed, confidence, and strategic relevance.
Closing cycles become more reliable because issues are caught before the books are finalized, not after. Reporting becomes more defensible because every figure has a traceable control behind it. And finance teams spend less time on manual verification and more time advising the business.
In practice, this means:
Errors and anomalies caught during the close, not after
Audit cycles that used to take days reduced to minutes with AI Xplore
Less dependency on external auditors for routine control work
Finance teams that spend less time on compliance and more time on analysis
A clear, traceable audit trail that satisfies both internal governance and external reviewers
The result is a finance function that controls more, costs less, and earns a seat at the table.