ROI Calculator · For BSA officers, CCOs & compliance leaders

What does 1990s rule-based
monitoring actually cost
your institution?

A bottom-up business case calculator built on industry-standard time-per-task benchmarks. Adjust to match your actual volumes — every figure reconciles cleanly to your analyst budget. No marketing math.

Run the numbers
01  /  The cost of noise

Three numbers every BSA team already knows.

90%+
False-positive rate

Rule-based transaction monitoring systems produce false-positive rates exceeding 90% — flooding understaffed teams with noise.

30–40 hr
SAR lifecycle

Hours spent per SAR across investigation, narrative drafting, QA review, and filing — industry midpoint per LexisNexis & ACAMS.

4.7M
SARs filed in FY24

FinCEN processed 4.7 million Suspicious Activity Reports in fiscal year 2024 — roughly 12,870 per day, the majority never actioned.

+34.5%
Enforcement actions · 2024

Banking regulator enforcement actions rose 34.5% year-over-year. OCC actions alone nearly doubled, from 56 to 107.

02  /  Methodology

Bottom-up. Internally consistent. No hand-waved unit costs.

Step 1

Effective hourly rate

Fully loaded FTE cost ÷ productive hours per year × (1 + indirect overhead). Default: $90,000 ÷ 1,800 hrs × 1.15 = $57.50/hour.

Step 2

Time × volume × rate

Annual labor cost summed across alerts, cases, SARs, continuing SARs, and rework — every line derived from time-per-task benchmarks.

Step 3

Reconciliation check

Implied FTE need vs. stated FTEs. If they don't match, the calculator flags it — and that gap usually reveals what's actually happening on the ground.

03  /  Build your case

Pick your tier. Adjust everything. Watch the numbers reconcile.



This is an Estimator only · not financial advice.

04  /  Next step

Bring this analysis to your actual portfolio. Thirty minutes with a founder.

Vigilic replaces legacy rule engines with an ML-native platform — 275 behavioral features across 14 risk categories, generating high-confidence investigation cases instead of alert floods. We're working with community banks and credit unions to validate the model against real volumes.