Solutions by role / CFO and Finance
AI for CFOs: calculate faster and keep every result traceable
Finance does not need another black box. It needs fewer manual transfers, earlier warning of variance and a full cost model. Every important number must lead back to a source.
- A baseline before the pilot
- Traceable source data
- Approval for consequential actions
01 / The problem
Where time, money and control are being lost
This is not a list of fashionable tools. These are operating problems we can test against your data and measure before development starts.
Close depends on manual reconciliation
Specialists copy data, look for mismatches and repeat the same checks across spreadsheets and systems.
Explore this problem 02The report arrives after the decision window
By the time a variance is visible, there is little time to act and explaining it requires another manual search.
Explore this problem 03The full cost of AI is unclear
A model invoice does not include integration, controls, storage, support and employee time.
Explore this problem 04Automation can create a larger control risk
Speed is not useful when a system changes payment data or takes an action without a trace and approval.
Explore this problem02 / In depth
What each problem looks like in practice
The short cards above are navigation. Each problem below is explained through business impact, a practical operating change, a measurable outcome and the questions leaders usually need answered before a pilot.
Close depends on manual reconciliation
Specialists copy data, look for mismatches and repeat the same checks across spreadsheets and systems.
Why it becomes expensive
Manual reconciliation delays close and consumes skilled finance time searching for differences. Most lines are routine, yet people inspect them with the same effort, while decisions about exceptions remain scattered across spreadsheets and messages.
What changes in the workflow
We formalize matching rules, sources and accepted tolerances. The system links clear transactions, preserves provenance and creates a separate exception queue. Finance reviews disputed cases and retains approval over entries and payments.
What a verifiable result looks like
The team spends time on differences instead of mechanically reviewing every line. Every transaction shows its source, rule and human decision. Improvement is measured through close time, review volume and repeated errors.
Practical questions
Can people be removed from reconciliation entirely?
Stable, low-risk matches can become automated after the rules are validated. Exceptions, new transaction types and material amounts should remain in an approval queue.
What is needed for a pilot?
A bounded historical transaction set, the current matching rules and prior decisions for known exceptions. That sample supports an honest comparison.
The report arrives after the decision window
By the time a variance is visible, there is little time to act and explaining it requires another manual search.
Why it becomes expensive
When a report is manually assembled from multiple systems, leaders see a problem after it has developed. Analysts spend time moving and reconciling versions instead of explaining changes in margin, cash or receivables.
What changes in the workflow
We connect only the required metrics to their source, fix definitions and set an update cadence. The system prepares a brief, flags deviations and links the source evidence. An analyst validates the conclusion and adds business context.
What a verifiable result looks like
Finance gets a repeatable report with consistent calculation logic and visible provenance for every number. Leadership sees deviations sooner, and the next reporting cycle does not begin with another manual rebuild.
Practical questions
Does this replace our BI system?
Not necessarily. BI remains the metric source, while AI helps assemble context, explain deviations and prepare questions for the responsible owner.
How do we prevent competing definitions of one metric?
Assign an owner, formula, source and refresh period. AI must not invent a metric definition from the wording of a question.
The full cost of AI is unclear
A model invoice does not include integration, controls, storage, support and employee time.
Why it becomes expensive
Comparing only model prices hides integration, infrastructure, storage, support, evaluation and human review. A promising pilot gets a false business case, and vendors cannot be compared on an equal basis.
What changes in the workflow
We model total cost per completed business task. It includes model calls, retrieval, infrastructure, licenses, implementation, quality control and human effort. Alternatives use the same volumes and service requirements.
What a verifiable result looks like
The CFO can see the cost of one document, inquiry, report or other unit before and after implementation. Volume, quality and model-choice scenarios support budget boundaries and review triggers.
Practical questions
How do we model a project when adoption is unknown?
Use several volume scenarios and separate fixed from variable cost. Replace assumptions with actual usage after the pilot.
Should employee time be included?
Yes. Review, correction and support can cost more than the model. Excluding them produces an incomplete comparison.
Automation can create a larger control risk
Speed is not useful when a system changes payment data or takes an action without a trace and approval.
Why it becomes expensive
An error in a finance workflow can cause a wrong payment, misstated report or audit issue. The more freely an agent acts across systems, the greater the impact of one bad instruction, missing context or compromised credential.
What changes in the workflow
We separate preparation from execution. AI may extract data, propose a classification and prepare a document, but financially material actions pass rules, limits and authorized approval. Sources and every step are retained.
What a verifiable result looks like
Speed improves in repeatable work while control becomes stronger at the points of actual risk. An auditor can see the evidence, rule, approver and final system outcome.
Practical questions
Which actions should never run without approval?
Payments, bank-detail changes, material postings and mandatory filings are common examples. The exact list follows the company’s authority policy.
How should errors be tested before implementation?
Replay historical cases including fraud, unusual documents and boundary amounts. Failed cases must enter a visible queue rather than finish silently.
03 / KPI
What we measure before a pilot
A result needs a baseline. We record the current cost, speed and quality first, then compare the pilot with the same work.
- Time to close
- Manual reconciliations
- Forecast variance
- Cost per transaction
04 / Workflows
What can change in day-to-day work
Every workflow has a clear action, a system boundary and a human decision point. You know what is automated and who remains accountable.
Reconciliation queue
Match records across sources and move only the differences into a review queue.
Control: Finance resolves exceptions and approves the result.Document processing
Extract terms, totals and fields, check completeness and pass structured data into the process.
Control: Payments and bank-detail changes always require approval.Variance explanation
Collect related data and prepare a sourced explanation for a material change.
Control: An analyst checks the evidence and publishes the commentary.AI cost control
Separate model, infrastructure and workflow costs to show the price of a completed useful task.
Control: Finance and IT set limits and model-selection rules together.IBM’s 2026 finance research links mature execution to redesigned workflows, standardized data, controls and explicit exception management. Source.
Finance gets value when the end-to-end workflow changes, not when one isolated step gets a new tool.
05 / Delivery
From one useful workflow to a working system
We do not redesign the company around a pilot. We test one bounded workflow, prove the economics and expand only when the evidence is good.
Diagnose
Choose the process, owner, data and constraints.
Baseline
Record current cost, time, errors and risk.
Pilot
Test a bounded slice of real work with real users.
Integrate
Connect systems, permissions, logs and approvals.
Decide
Scale, revise or stop based on measured results.
06 / Next
Related services
Questions to answer before you start
Where should a finance team start?
Choose a repeated process with a clear volume, owner and cost. Reconciliation, document handling and variance commentary are often good candidates.
Can we trust an AI-generated figure?
Not blindly. The system should cite its source, keep a log and route exceptions to a person. Control depth should match the consequence of an error.
Can you integrate with our ERP?
Yes, when it provides a secure way to exchange data. The exact method depends on the product, version, customizations and access rules.
How is ROI calculated?
We compare the current process cost with pilot and operating cost, including errors, delays and employee time.
Discuss your workflow
Discuss my workflow
Choose one manual finance operation. We will help quantify its current cost, error risk and the boundary of a safe pilot.