Three CFO Metrics That Prove AI’s Real ROI in RCM

Hi and happy Tuesday,

After we shared results from a recent pilot—$450K in projected revenue recovered from a small batch of claims—we heard from the CFO of a 20-site healthcare group.

They’d seen the numbers. But they'd also seen plenty of tools make similar promises.

That’s why they came back with a direct question: What does this actually change in our numbers?

It’s a question that cuts through the noise. Because for most financial leaders, the real value of AI isn’t in the concept—it’s in the impact.

If you're asking the same, we offer two simple ways to start:
👉 Try a free 100-claim review using your data, or
👉 Book a 15-minute demo to see how it works in real time.

But before you can move the numbers—you have to know where to look and why.

That’s why we always start with three simple, financial metrics that consistently reflect real RCM impact.

The 3 metrics CFOs actually care about

Here are three metrics that prove ROI and show where revenue cycle improvements are working.

1. Clean-claim rate

What it tells them: How much friction the system prevents upfront
Target benchmark: ≥90%
Why it matters: Every clean claim shortens cash cycles and reduces the need for manual rework.
What to track: Month-over-month percentage of claims submitted without corrections

One group raised their rate from 67% to 91% in 90 days by using AI to flag coding errors and documentation gaps before submission—saving an estimated $80K per month in rework time and staffing costs.

2. Days sales outstanding (DSO)

What it tells them: How long revenue is stuck in limbo
Target benchmark: Fewer than 30 days
Why it matters: Lower DSO means faster reinvestment, better liquidity, and less pressure on credit lines.
What to track: Average DSO by payer group and by intervention date

Practices using AI tools like Auxee have cut DSO by up to 14 days by addressing issues before claims are submitted—without changing systems or adding staff.

3. Denial rate by claim type

What it tells them: Where hidden risk is driving cost
Target benchmark: Under 5% (compared to the national average of 12–15%)
Why it matters: Fewer denials reduce appeal cycles, ease team workload, and improve financial performance.
What to track: Denial rates by CPT code or service type, pre- and post-intervention

In one multi-location group, denial rates dropped from 16% to 7% after applying pre-submission checks—resulting in a projected $668K in recovered annual revenue.

Next week, I’ll show you where denials go to die—and the 3-step loop smart RCM teams use to turn them into clean claims.

See you next Tuesday,
Dino Gane-Palmer