Microsoft Insurance Claims Automation, powered by AI, handles claim processing through an intelligent agent with cognitive skills to handle image, ID, and documents with the goal to reduce claims processing time and manual effort in end-to-end claims processing for better customer experience.
git clone https://github.com/akshata29/digitalclaims.gitThe digitalclaims skill is an innovative AI automation tool designed to enhance the efficiency of insurance claims processing. By leveraging cognitive capabilities, this skill intelligently manages image, ID, and document processing, significantly reducing the time and manual effort required for end-to-end claims handling. With a focus on improving customer experience, digitalclaims allows organizations to streamline their workflows and minimize delays in claims resolution. One of the key benefits of implementing digitalclaims is the potential for substantial time savings in claims processing. Although the exact time savings are currently unknown, the automation of repetitive tasks typically leads to quicker turnaround times and reduced operational costs. This skill is particularly beneficial for insurance companies and claims adjusters who are looking to enhance their productivity and provide a more efficient service to their clients. This skill is ideally suited for product managers, developers, and AI practitioners within the insurance sector. By integrating digitalclaims into their existing workflows, these professionals can optimize their operations and create a more agile claims processing environment. Practical use cases include automating the verification of submitted claims documents, expediting the approval process, and improving the accuracy of claims assessments through intelligent data extraction. With an intermediate level of implementation difficulty, digitalclaims can be set up in approximately 30 minutes, making it accessible for teams looking to adopt AI-first workflows without extensive technical expertise. As organizations increasingly turn to AI automation to enhance their operational capabilities, digitalclaims stands out as a valuable asset for those aiming to modernize their claims processing systems.
["Gather all claim documents (emails, forms, images, PDFs) and save them in a single folder. Ensure filenames include claim type and date for easy reference.","Identify the specific policy rules and regulatory requirements that apply to this claim type using your company's compliance matrix. Note any state-specific workers' comp laws or auto insurance regulations.","Copy the prompt template and replace all [PLACEHOLDERS] with your specific claim details. For complex claims, break down the documents into sections (e.g., 'Medical reports', 'Incident reports', 'Policy documents').","Run the prompt in your AI Insurance claims automation system. Review the generated assessment report for accuracy, paying special attention to fraud indicators and validation warnings.","Use the recommended actions to guide your adjuster workflow. Update the claims management system with the assessment data and set follow-up reminders based on the estimated processing time."]
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/akshata29/digitalclaimsCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Process a new [CLAIM_TYPE] claim for [COMPANY_NAME] using their digital claims automation system. Extract all relevant data from the following documents: [CLAIM_DOCUMENTS]. Validate the claim against [COMPANY_POLICY_RULES] and [REGULATORY_REQUIREMENTS]. Identify any discrepancies, missing information, or potential fraud indicators. Generate a preliminary assessment report including: 1) Claim validity score (0-100%), 2) Required next steps for the adjuster, 3) Estimated processing time, and 4) Recommended fraud prevention measures. Format the output as a structured claim assessment report.
{
"claim_assessment_report": {
"claim_id": "CLM-2024-05892",
"company_name": "Greenway Manufacturing RRG",
"claim_type": "Workers' Compensation",
"policy_number": "WC-POL-78452",
"injured_party": {
"name": "Marcus Johnson",
"employee_id": "EMP-45872",
"injury_date": "2024-05-15",
"injury_description": "Lower back strain during warehouse equipment operation"
},
"validation_results": {
"document_completeness": 95,
"policy_coverage": "Valid",
"regulatory_compliance": "Compliant with state workers' comp regulations",
"fraud_indicators": [
{
"indicator": "Same-day filing after injury",
"severity": "Medium",
"notes": "Typical filing delay is 2-3 days for similar injuries"
},
{
"indicator": "No witness statements attached",
"severity": "Low",
"notes": "Supervisor report confirms incident but no independent witness"
}
]
},
"preliminary_assessment": {
"validity_score": 87,
"estimated_processing_time": "3-5 business days",
"recommended_actions": [
"Contact injured employee for additional witness details",
"Verify medical treatment records match injury description",
"Schedule independent medical examination if treatment exceeds 14 days"
],
"fraud_prevention_measures": [
"Flag claim for enhanced monitoring during initial treatment period",
"Cross-reference with previous claims history (no prior WC claims found)",
"Request supervisor's incident report within 48 hours"
]
},
"next_steps": {
"adjuster_responsibilities": [
"Review medical reports for consistency with injury timeline",
"Contact employer to verify equipment involved in incident",
"Schedule follow-up call with injured employee on 2024-05-22"
],
"system_actions": [
"Update claim status to 'Under Review' in claims management system",
"Send automated acknowledgment to injured party",
"Log fraud indicators in risk management dashboard"
]
}
}
}AI data extraction from clinical notes
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