What should organisations do before presenting authentication savings to finance?

What finance needs before the savings claim will hold up

Before presenting authentication savings to finance, organisations need to show the model, not just the headline number. That means exposing each assumption that drives the estimate, especially the reset effort per event, the percentage reduction being claimed, and the labour rate used to turn time into dollars. Without that detail, finance can review logic but cannot test whether the savings are real.

The practical issue is that authentication savings are usually an inference, not a directly observed line item. The savings number depends on how often resets happen, how much work each reset consumes, what proportion of that work the new control removes, and whether the labour cost reflects loaded cost, contractor cost, or a simple wage proxy. If any of those inputs are hidden, the output becomes difficult to defend.

It also helps to separate gross savings from net savings. A reduction in reset volume may be partially offset by rollout effort, licensing, support changes, exception handling, or user recovery work. Finance teams are usually willing to challenge assumptions, but they need transparent inputs to decide whether the estimate is conservative, aggressive, or incomplete.

How to present the numbers so finance can validate them

Use a simple chain from operational event to financial impact: baseline volume, expected reduction, unit effort, and unit cost. That structure makes the claim auditable because each step can be traced to a source, a measurement, or a judgement call. If the estimate relies on a benchmark or pilot result, label that clearly so finance can test whether it applies to your environment.

Where possible, present a range rather than a single point estimate. For example, show low, expected, and high cases for reset volume and labour cost, then keep the calculation visible. This avoids false precision and gives finance a clearer basis for scenario review. A small change in reset rate or cost per reset can materially change the annual savings figure.

Use NIST SP 800-63 Digital Identity Guidelines as a reference point when your savings case depends on stronger authentication reducing account recovery and reset burden. If you are comparing methods, MFA Guide and Passwordless and Passkeys Guide provide the implementation context behind lower-friction sign-in and reduced recovery effort.

What can undermine an authentication savings model

The most common failure is assuming every avoided reset becomes a full labour saving. In reality, some work is displaced rather than removed, especially when help desk teams absorb password recovery, device re-enrolment, account unlocks, or exception handling. Another common problem is using the wrong baseline, such as a one-time spike in tickets or a pilot group that does not reflect steady-state demand.

There is also a security-side risk to overselling savings if the control changes user behaviour but leaves recovery paths weak. Weak recovery can shift cost from one channel to another while increasing exposure to takeover or support abuse. That is why savings estimates should be aligned with the actual authentication and recovery design, not just the expected user experience.

For attack patterns that often sit behind identity cost and recovery assumptions, Workforce Identity Security Guide helps connect savings claims to reset, recovery, and session theft realities. If your business case depends on reducing phishing and reset-driven exposure, the most relevant external control references are RFC 8705: OAuth 2.0 Mutual-TLS Client Authentication and Certificate-Bound Access Tokens and RFC 7523: JWT Profile for OAuth 2.0 Client Authentication and Authorization Grants, because they show how stronger client authentication changes trust and recovery assumptions.

Practitioner Guidance

What to verify: Make sure every dollar figure can be traced back to a visible assumption, not a single opaque ROI number. The minimum audit trail is baseline event volume, expected reduction percentage, unit labour cost, and the time period used.

Decision rule: If you cannot defend the reset baseline or the reduction percentage, present the case as a scenario analysis instead of a fact. That is usually the difference between a credible business case and a number finance will reject on sight.

What good looks like: Finance should be able to change one assumption and immediately see how the savings number moves. If the model does not behave that way, the calculation is too brittle for investment approval.

Practitioner takeaway: The strongest savings case is transparent and testable, because finance funds assumptions it can inspect, not outputs it has to trust blindly.

Related resources from NHI Mgmt Group

• How do organisations operationalise NHI ownership at scale?
• When should organisations treat an NHI as a high-priority risk?
• How can organisations reduce the blast radius of compromised agent identities?
• Should organisations prioritise external exposure or internal credential governance first?