If a critical technology platform failed on Monday morning, no responsible engineering team would wait until month-end to investigate.

An alert would fire. Someone would take ownership, assess the impact and contain the problem. Once service was restored, the team would ask why the safeguards failed and what needed to change.

Finance often discovers its equivalent failures differently.

An incorrect supplier rate surfaces during a quarterly review. Work that was delivered but never billed emerges during the close. A policy override is questioned after payment. An unusual transaction is reconstructed weeks later from emails, spreadsheets and the memories of the people involved.

The invoice may have been approved. The reconciliation may be complete. The accounts may even balance.

But the financial control system has still failed.

Site reliability engineering, or SRE, offers a useful way to think about that gap. Developed to keep complex software services dependable, it combines monitoring, measurable objectives, incident response and learning from failure.

The same principle applies to finance. A control is only as reliable as the system that puts it to work: the data it uses, the decisions it supports and the response when something goes wrong. Reliability is not proven by a documented process. It is proven when the right control produces the right outcome, consistently.

Finance already runs a distributed system

A supplier payment depends on contracts, purchase orders, delivery records and invoices. Customer billing depends on agreements, service records and pricing data. When that evidence sits across separate systems, no single approval proves the transaction is correct.

People bridge those gaps, but terms change, records diverge and context gets lost. A completed approval or reconciliation proves a step happened, not that the business paid the right amount or billed for everything delivered.

Controls must therefore be assessed end to end, against the outcomes they are meant to protect.

Observe the system, not just the workflow

In technology, observability means having enough evidence to understand how a system is behaving. In finance, that means seeing not only the volume of completed transactions, but also where controls are weakening and value may be at risk.

A dashboard may show how quickly invoices are approved. A more useful view would also show how many were checked against current contract terms, which warnings were overridden, how long exceptions have been open and where the evidence needed to make a decision is missing.

SRE often groups operational signals into traffic, latency, errors and saturation. Finance can adapt those signals:

  • Volume: How many transactions are entering the process, and has the mix changed?
  • Time: How long do approvals and exceptions remain unresolved?
  • Errors: How often do mismatches, unsupported overrides, duplicates or missing records occur?
  • Pressure: Where are queues, workloads or deadlines making thorough review harder?

These signals matter most when they reveal financial exposure. An overdue exception needs attention, but its potential value and risk help determine how urgently it should be investigated. An alert is not a confirmed loss, so estimated exposure should be distinguished from validated leakage.

The goal is to spot weakening controls and act before value is lost.

Define what reliable control looks like

Technology teams use service-level objectives to express the reliability expected of a service. Finance can use the same discipline to make control performance measurable.

“Invoices are reviewed before payment” describes an activity. A stronger objective defines which invoices are in scope, what evidence must be checked, when the check must occur and what happens if it cannot be completed.

For example, a supplier control might measure the proportion of in-scope invoice lines checked against the applicable contract and delivery evidence before approval. A revenue control might measure the proportion of delivered services matched to customer billing by a defined point in the close.

Each measure needs a clear numerator, denominator, owner and reporting period. Just as importantly, finance needs to know when the underlying contract, rate card or delivery data is missing or out of date: a check against the wrong information can create false confidence.

Useful measures include:

  • Coverage of in-scope transactions and availability of the evidence required to test them
  • Time to detect, contain and resolve material exceptions
  • False-positive rates and manual overrides
  • Age and estimated value of unresolved exceptions
  • Recurring failures and corrective actions completed on time

The target should reflect the risk and the obligation. It should make weak coverage, stale data and routine bypasses visible, not reward a team merely for closing alerts quickly.

Treat material exceptions as incidents

A serious technology outage is not handled as an ordinary support ticket. It has an owner, a severity and a coordinated response. Financial exceptions deserve a similarly proportionate approach.

A suspicious bank-detail change, a major supplier overcharge and a missing approval should not disappear into the same undifferentiated queue. A material incident needs:

  • A severity assessment and accountable owner
  • Immediate containment steps
  • Evidence of the issue and the decisions made
  • A communication path for affected stakeholders
  • A resolution target proportionate to the risk

Containment comes first. Can the payment be held? Can a billing run be corrected? Should further transactions using the same supplier record or pricing rule be paused?

Then comes recovery: what is needed to return the process to a controlled state?

Finally, prevention: what must change so the same conditions are detected earlier or cannot recur?

The incident record should show what the organisation knew, when it knew it and why it acted. That record is valuable both for decision-making and for the audit trail.

Engineer out repeated failure

SRE is not only about responding well. It is about making common failures less likely and less damaging.

For finance, that means checking transactions against the right evidence before money moves. An invoice checked against the agreement and delivery record can expose an overcharge before it becomes a payment, rather than a recovery exercise months later.

Automate repeatable checks and give accountable people the context to resolve exceptions. Human judgement stays focused on ambiguity and material decisions, not piecing together evidence after the fact.

Where to start

Start with one material process, such as supplier invoice approval. Follow it from the agreement through to payment and ask whether the right evidence is available when each decision is made. Review past exceptions to understand where controls have failed, then set clear ownership and test how the team would respond if the same issue occurred again.

RedOwl can support this approach by connecting the evidence across existing systems and surfacing discrepancies before approval. That gives finance a clearer view of where value is at risk and helps turn what it learns into stronger ongoing controls.

Start where the risk is meaningful, demonstrate that the process works, and expand from there.