AI Playbook for Child Care Subsidy Provider Fraud

A state child care subsidy agency's payment data shows 18 providers with billing anomalies: billing for more children than licensed capacity, billing on days the facility is documented closed, and billing for children enrolled in school full-time. Total overpayments estimated at $1.1M.

When to use this playbook

• Use this playbook when the decision looks like the situation above: A state child care subsidy agency's payment data shows 18 providers with billing anomalies: billing for more children than licensed capacity, billing on days the facility is documented closed, and billing for children enrolled in school full-time.
• It is a fit when you have source files in hand and need a structured, reviewable analysis — not a generic chat answer about "Child Care Subsidy Provider Fraud".
• Do not use it as a substitute for licensed, legal, clinical, or authorized official judgment in the domain.

What you'll need

• Subsidy payment records for all 18 providers (24 months)
• State child care facility licensing records
• School enrollment records for billed children
• Parent-signed attendance records vs. billed attendance
• State child care fraud prosecution history

Attachments: Documents (Documents)

You are a public benefits fraud investigator examining child care subsidy billing fraud for 18 providers. I am attaching:

Work only from the attached source files. If a conclusion is not supported, say so.

Produce:
1. Calculate the capacity billing overage for each provider: on how many days did billing exceed licensed capacity and what is the overbilling amount?
2. Identify billing on documented closure days: cross-reference payment dates against licensing records.
3. Flag children billed as present in child care while school records show full-day school attendance.
4. Prioritize the 18 providers by evidence quality for immediate action.
5. Tell me the overpayment demand process, provider appeal rights, and what constitutes sufficient evidence for criminal referral.

Call out where independent models are likely to disagree, and list follow-up documents a reviewer should request.

What to expect

• Capacity overbilling calculation per provider
• Closure-day billing analysis
• School enrollment double-billing instances
• Evidence quality ranking of 18 providers
• Overpayment demand process and criminal referral threshold

Review before you act

• Validate this output against source files before relying on it: Calculate the capacity billing overage for each provider: on how many days did billing exceed licensed capacity and what is the overbilling amount?.
• Validate this output against source files before relying on it: Identify billing on documented closure days: cross-reference payment dates against licensing records.
• Validate this output against source files before relying on it: Flag children billed as present in child care while school records show full-day school attendance.
• Validate this output against source files before relying on it: Prioritize the 18 providers by evidence quality for immediate action.
• Confirm every cited figure, date, counterparty, or requirement against the attached originals — models compress and can drop a qualifier.
• Treat disagreement between models as a review item, especially on classification, materiality, and recommended next action.
• Do not authorize an operational, clinical, legal, credit, or enforcement action solely because the models agree.