AI Playbook for Benefits Issuance System Data Integrity

A state benefits agency is migrating its eligibility and issuance system to a new platform. Data migration testing found 4,300 records with integrity issues: duplicate SSNs, benefit amounts outside program limits, and eligibility dates that don't match case notes. Go-live is in 45 days.

When to use this playbook

• Use this playbook when the decision looks like the situation above: A state benefits agency is migrating its eligibility and issuance system to a new platform.
• It is a fit when you have source files in hand and need a structured, reviewable analysis — not a generic chat answer about "Benefits Issuance System Data Integrity".
• Do not use it as a substitute for licensed, legal, clinical, or authorized official judgment in the domain.

What you'll need

• Data migration test results (4,300 flagged records with error codes)
• Source system data extract
• Target system validation rules
• State agency go-live criteria and risk assessment
• Federal reporting requirements for the benefit programs affected

Attachments: Documents (Documents)

You are a benefits IT program manager assessing data integrity issues before a system migration go-live. I am attaching:

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

Produce:
1. Classify the 4,300 errors by type and severity: which require fix before go-live vs. which can be remediated post-migration?
2. Assess the duplicate SSN records: data entry errors, potential identity fraud, or system migration artifacts?
3. Identify the amount errors outside program limits: field mapping issues or actual benefit calculation errors?
4. Calculate the timeline and resource requirement to resolve all go-live-blocking errors in 45 days.
5. Tell me whether to proceed with go-live, delay, or go live with known issues — with the risk assessment for each option.

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

What to expect

• Error classification matrix by type and severity
• Duplicate SSN analysis
• Benefit amount error root cause
• 45-day remediation timeline and resource requirement
• Go-live recommendation with risk assessment

Review before you act

• Validate this output against source files before relying on it: Classify the 4,300 errors by type and severity: which require fix before go-live vs. which can be remediated post-migration?.
• Validate this output against source files before relying on it: Assess the duplicate SSN records: data entry errors, potential identity fraud, or system migration artifacts?.
• Validate this output against source files before relying on it: Identify the amount errors outside program limits: field mapping issues or actual benefit calculation errors?.
• Validate this output against source files before relying on it: Calculate the timeline and resource requirement to resolve all go-live-blocking errors in 45 days.
• 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.