A Finance Reconciliation Agent yields a net monthly value of $4,458 when handling 1,000 interactions with a 65% success rate. This return is calculated by subtracting the $1,500 platform cost from the $5,958 in labour value created through saved time.
Efficiency is driven by saving 12 minutes per accepted outcome, even when accounting for 2 minutes of required human review. While 35% of interactions are escalated to staff, the agent successfully automates 650 outcomes monthly, reducing the burden on finance teams at a loaded cost of $55 per hour.
Agent ROI worked example
Worked example for Finance Reconciliation Agent using stated NetLift assumptions:
| Input (stated assumption) |
Value |
| Interactions handled per month |
1,000 |
| Accepted / successful outcomes |
65% |
| Escalated to a person |
35% |
| Staff minutes saved per accepted outcome |
12 min |
| Human review per accepted outcome |
2 min |
| Loaded staff cost |
$55/hour |
| Agent platform cost per month |
$1,500 (stated assumption) |
| Computed result |
Value |
| Successful outcomes per month |
650 |
| Cost per successful outcome |
$2.31 |
| Net staff time saved |
108 h / month |
| Labour value of time saved |
$5,958 / month |
| Current net value |
$4,458 / month |
Escalation, review and rework are part of the true cost of an AI agent. Track them — an agent that resolves fewer tickets with less rework can beat one that closes more tickets badly.
What is the true cost of a successful outcome?
In a finance context, the cost of an agent extends beyond the subscription fee. The true cost per successful outcome—$2.31 in this model—is a factor of the platform price and the volume of work the agent actually completes without requiring a full manual takeover.
Why track escalations and review time?
Escalations, review, and rework are essential components of AI cost management. This model accounts for a 35% escalation rate and allocates 2 minutes of human review for every "successful" outcome. Measuring the net value ensures that the cost of this human oversight is subtracted from the gross labour savings, providing a realistic view of the agent's impact on the department budget.
NetLift measures the actual labour value of time saved by comparing AI-assisted work against established human baselines. We categorize the evidence quality of these savings to ensure a deterministic view of ROI, rather than relying on self-estimated productivity. By tracking the net value—realised time savings minus implementation, platform, and review costs—NetLift provides a clear decision state on whether to expand the reconciliation agent or improve its accuracy to reduce escalations.