Quick Wins

You are a senior insurance analyst reviewing an insurance policy document. I will provide the full text of a policy. Please produce a structured summary that includes:

1. **Policy Type & Number**: Identify the type of insurance and policy number.
2. **Insured & Insurer**: Identify all parties, their roles, and relevant details.
3. **Coverage Summary**: Summarize the core coverages in 2-3 sentences per coverage type.
4. **Policy Period**: State the effective date, expiration, and any renewal provisions.
5. **Key Limits & Deductibles**: List all coverage limits, sub-limits, and deductible amounts.
6. **Exclusions**: List the major exclusions and briefly explain each.
7. **Conditions & Obligations**: For the insured, list the key obligations (notice requirements, duties after loss, etc.).
8. **Endorsements & Riders**: Summarize any endorsements that modify standard coverage.
9. **Premium Structure**: Note the premium amount, payment schedule, and any applicable discounts or surcharges.
10. **Notable or Unusual Clauses**: Flag any provisions that are non-standard or potentially problematic, and briefly explain why.

Format the summary with clear headings. Use bullet points for readability. Keep the total summary under 800 words. After the summary, add a section titled "Coverage Gaps & Risk Flags" listing any areas where coverage may be insufficient or where the insured should be aware of potential gaps.

Here is the policy:

[PASTE THE FULL POLICY TEXT HERE]

Consejos

• If the policy exceeds the AI's context window, split it into sections (declarations, insuring agreement, exclusions, conditions, endorsements) and summarize each separately.
• For best results, include all endorsements and riders — they often materially modify the base coverage.
• After receiving the summary, follow up with questions like 'How does this policy compare to ISO standard forms?' or 'What additional endorsements would you recommend?'
• Use this summary as a starting point for your own analysis, not as the finished work product.

Precauciones

• Never rely on the AI summary without reading the original policy yourself. AI can misinterpret defined terms, miss cross-references between sections, or overlook endorsements that modify base coverage.
• Do not paste confidential client policy documents into consumer AI tools without understanding data retention policies. Use enterprise or API versions with appropriate data handling agreements.
• AI may not recognize jurisdiction-specific implications. Insurance regulation varies significantly by state and country.
• The 'Coverage Gaps' section is a helpful starting point, but it reflects pattern matching, not actuarial or legal judgment.

What This Quick Win Does

Policy review is one of the most time-consuming tasks in insurance practice. A comprehensive commercial policy can span 50+ pages with declarations, insuring agreements, exclusions, conditions, and multiple endorsements. With AI, you can generate a structured first-pass summary in approximately 2 minutes, freeing you to focus your expertise on coverage analysis and client advisory.

This Quick Win gives you a prompt that produces a comprehensive policy summary — the kind you would prepare for a client consultation, an underwriting review, or a claims coverage determination.

How to Use It

Step 1: Prepare the Policy

Open the policy document in a format where you can select and copy the full text. PDF documents may need to be converted to text first.

Make sure you include:

• The declarations page
• The insuring agreement
• All exclusions
• Conditions and definitions
• All endorsements and riders
• Any applicable schedules

Step 2: Open Your AI Tool

Navigate to ChatGPT or Claude. For confidential documents, ensure you are using an enterprise account with appropriate data handling agreements.

Step 3: Paste the Prompt and the Policy

Copy the prompt above, paste it into the AI chat, and replace [PASTE THE FULL POLICY TEXT HERE] with the full text of the policy. Submit the message.

Step 4: Review the Output

The AI will return a structured summary. Read it alongside the original policy, paying particular attention to:

• Defined terms: Verify that the AI correctly identified how key terms are defined throughout the policy.
• Exclusion scope: Check whether the AI caught all exclusions, including those embedded in endorsements.
• Coverage Gaps: Use the flagged items as a checklist for your deeper review.

Step 5: Iterate

Follow up with targeted questions:

• “Compare the exclusions in this policy to a standard ISO commercial general liability form.”
• “What endorsements would you recommend to close the coverage gaps you identified?”
• “Summarize the notice requirements and claims reporting obligations.”

Why This Works

Large language models excel at extracting structured information from document text. Insurance policies follow relatively predictable structures, making them well-suited for AI analysis. The prompt instructs the AI to organize its output in the framework an experienced analyst would use.

What This Does Not Replace

This Quick Win accelerates the first pass. It does not replace:

• Professional judgment about whether coverage is adequate for a specific risk
• Actuarial analysis of pricing adequacy
• Legal interpretation of ambiguous policy language
• Regulatory compliance review for jurisdiction-specific requirements

You are a senior claims adjuster drafting a claims denial letter. Based on the information I provide, draft a professional denial letter that includes:

1. **Header**: Insurer name, claim number, policy number, date of loss, and insured's name and address.
2. **Opening**: Acknowledge receipt of the claim and reference the investigation conducted.
3. **Coverage Analysis**: Cite the specific policy provisions (section numbers and exact language) that apply to this claim.
4. **Basis for Denial**: Clearly state why the claim is being denied, referencing specific exclusions, conditions, or coverage limitations.
5. **Supporting Facts**: Summarize the key facts from the investigation that support the denial.
6. **Regulatory Disclosures**: Include required disclosures about the insured's right to appeal, time limits for appeal, and contact information for the state insurance department.
7. **Closing**: Professional closing with adjuster's contact information for questions.

Tone: Professional, empathetic, and clear. Avoid jargon where possible. The letter should be understandable to a non-insurance professional.

Here is the claim information:

[PROVIDE: Claim number, policy number, insured name, date of loss, type of loss, investigation findings, applicable policy provisions, and reason for denial]

Consejos

• Always verify the denial reason against the actual policy language — do not rely solely on the AI's interpretation.
• Customize the regulatory disclosures for your specific state's requirements. Each jurisdiction has different notice obligations.
• Have the letter reviewed by a supervisor or legal team before sending, especially for complex or high-value claims.
• Use the AI output as a draft framework, then refine with case-specific details and your professional judgment.

Precauciones

• Claims denial letters have significant legal implications. Never send an AI-generated letter without thorough human review.
• Regulatory requirements for denial letters vary by state and line of business. The AI may not know your specific jurisdiction's requirements.
• Bad faith claims can result from poorly worded or inadequately reasoned denial letters. Ensure every denial is well-supported.
• Do not include confidential claim investigation details in consumer AI tools. Use enterprise versions with appropriate data protections.

What This Quick Win Does

Drafting claims denial letters is a routine but critical task. Each letter must be clear, compliant with regulations, properly cite policy language, and maintain a professional tone. AI can generate a well-structured draft in minutes, letting you focus on accuracy and compliance review.

How to Use It

Step 1: Gather Your Information

Before using the prompt, compile:

• Claim and policy numbers
• Insured’s information
• Date and description of loss
• Relevant policy provisions (copy the exact language)
• Investigation findings supporting the denial
• Applicable state regulatory requirements

Step 2: Generate the Draft

Paste the prompt and your claim information into your AI tool. Review the output carefully.

Step 3: Verify and Customize

• Cross-check every policy citation against the actual policy
• Verify regulatory disclosure requirements for your jurisdiction
• Adjust tone and language as appropriate
• Have the letter reviewed before sending

What This Does Not Replace

This does not replace claims adjuster judgment, legal review, or regulatory compliance expertise.

You are an insurance claims analyst reviewing a claims file. I will provide documents from a claim. Extract every date and deadline mentioned, and organize them into a structured timeline. For each entry, include:

1. **Date**: The specific date (or date range).
2. **Event**: What happened or is due on that date.
3. **Source**: Which document the date appears in (e.g., "Police Report," "Policy Declarations," "Claimant Statement").
4. **Significance**: Why this date matters for the claim (e.g., "Within 72-hour reporting window," "Statute of limitations expires," "Policy effective date").

After the timeline, add these sections:

**Critical Deadlines**: List any upcoming deadlines that require action, sorted by urgency.

**Potential Issues**: Flag any date-related concerns (e.g., late reporting, coverage gaps between policy periods, statute of limitations risks, inconsistencies between documents).

Format as a markdown table for the timeline, followed by bullet lists for deadlines and issues.

Here are the claims documents:

[PASTE CLAIMS FILE DOCUMENTS HERE]

Consejos

• For large claims files, process documents in batches by type (police reports, medical records, correspondence, etc.).
• Cross-reference the extracted dates against your claims management system to catch any discrepancies.
• Pay special attention to notice requirements — many policies have strict time limits for reporting claims.
• Use this timeline as the foundation for a claims diary and follow-up system.

Precauciones

• Verify all extracted dates against the original documents. AI can misread dates, especially in scanned or handwritten documents.
• Statute of limitations periods and notice deadlines vary by jurisdiction and coverage type. Confirm with your legal team.
• Do not paste medical records, Social Security numbers, or other sensitive PII into consumer AI tools.
• This extraction is a starting point — a claims professional must verify the significance and implications of each date.

What This Quick Win Does

Complex claims files can contain dozens of critical dates scattered across multiple documents — police reports, medical records, policy documents, correspondence, and legal filings. Missing a single deadline can have serious consequences. AI can scan an entire claims file and extract every date into an organized timeline in minutes.

How to Use It

Step 1: Compile Your Documents

Gather the text from all relevant claims documents. Redact sensitive PII before processing through AI tools.

Step 2: Generate the Timeline

Paste the prompt and documents into your AI tool.

Step 3: Verify and Act

• Cross-check every date against the original documents
• Enter critical deadlines into your claims management system
• Flag any date inconsistencies for investigation
• Set up reminders for upcoming deadlines

What This Does Not Replace

This does not replace a claims examiner’s responsibility to independently verify dates, calculate deadlines, or determine their legal significance.

You are a senior insurance analyst comparing two insurance policy documents. I will provide the full text of both policies. Please produce a comprehensive side-by-side comparison with the following structure:

**1. Executive Summary**
Provide a brief overview (5-8 bullet points) of the most significant differences between the two policies, listed in order of impact on the insured.

**2. Detailed Comparison Table**
Create a comparison table covering these categories:

| Category | Policy A | Policy B | Material Difference? |
|----------|----------|----------|---------------------|

Cover the following categories row by row:
- **Coverage Types & Limits**: Each coverage type, per-occurrence limits, aggregate limits, and sub-limits
- **Deductibles**: Per-claim and aggregate deductibles for each coverage
- **Exclusions**: Every exclusion, noting which are shared and which are unique to one policy
- **Conditions**: Notice requirements, duties after loss, cancellation provisions, subrogation clauses
- **Endorsements**: All endorsements and riders, noting how they modify base coverage
- **Premium Structure**: Premium amount, payment schedule, discounts, surcharges, audit provisions

**3. Material Differences Analysis**
For each row flagged as a material difference, provide:
- A plain-language explanation of the difference
- Which policy offers broader or more favorable coverage for that item
- The practical impact on the insured

**4. Overall Assessment**
- Which policy offers broader coverage overall, and why
- Any unique provisions in either policy that the other lacks
- Recommendations for what to negotiate or clarify before binding

Here are the two policies:

=== POLICY A ===
[PASTE POLICY A TEXT HERE]

=== POLICY B ===
[PASTE POLICY B TEXT HERE]

Consejos

• For best results, include the full text of both policies — declarations pages, insuring agreements, exclusions, conditions, and all endorsements.
• If the policies are too long for a single prompt, compare them section by section (e.g., exclusions from both policies first, then conditions, then endorsements).
• After receiving the comparison, follow up with: 'Based on these differences, what negotiation points would you recommend for Policy B to match or exceed Policy A's coverage?'
• Use this comparison as a structured reference during renewal discussions or competitive quoting, not as a standalone coverage opinion.

Precauciones

• AI may not detect subtle differences in defined terms that materially change coverage scope. Always verify defined terms manually.
• Policy language interpretation depends on applicable state law and case precedent. The AI comparison reflects plain-language reading, not legal analysis.
• Do not paste confidential client policy documents into consumer AI tools. Use enterprise or API versions with appropriate data handling agreements.
• The 'broader coverage' assessment is based on text analysis only — it does not account for insurer financial strength, claims handling reputation, or service quality.

What This Quick Win Does

Comparing two insurance policies is a routine but labor-intensive task. Whether you are evaluating a renewal quote against the expiring policy, comparing competing bids during a marketing exercise, or reviewing coverage in an M&A due diligence process, the work requires methodical section-by-section analysis. A commercial policy comparison that might take 45 minutes to an hour of manual review can be drafted in approximately 5 minutes with AI.

This Quick Win produces a structured comparison table that organizes the differences by category, flags material deviations, and provides a plain-language assessment of which policy offers broader coverage. It gives you a working analysis to refine with your professional judgment, not a finished coverage opinion.

The output is especially useful for renewal reviews where you need to show a client exactly what changed, competitive analyses where you are presenting options to an insured, and due diligence processes where you need to compare coverage across multiple entities.

How to Use It

Step 1: Prepare Both Policies

Extract clean text from both policy documents. For each policy, include:

• The declarations page
• The insuring agreement
• All exclusions
• Conditions and definitions
• All endorsements and riders
• Any applicable schedules

Remove headers, footers, and page numbers that may interfere with the analysis. If working from PDFs, convert to text first and verify the conversion is clean.

Step 2: Paste the Prompt and Both Policies

Copy the prompt into your AI tool. Replace the placeholders with the full text of each policy. Use the clear delimiters (=== POLICY A === and === POLICY B ===) so the AI can distinguish between the two documents.

If the combined text exceeds your AI tool’s context window, compare by section: run the exclusions from both policies first, then conditions, then endorsements, and compile the results.

Step 3: Review the Comparison Table

Start with the executive summary to understand the overall picture. Then review the detailed comparison table row by row, focusing on items flagged as material differences. Verify each difference against the original policy language — the AI may mischaracterize the scope of a defined term or miss a cross-reference to another section.

Step 4: Focus on Material Differences

For each material difference the AI identifies, determine:

• Is the difference accurately described?
• Does it affect the insured’s coverage for their specific risk profile?
• Is it a negotiable point, or a fundamental underwriting position?

Use the AI’s analysis as a starting framework for your own coverage comparison memo or client presentation.

What This Does Not Replace

This Quick Win accelerates the comparison process. It does not replace professional judgment about which policy is appropriate for a specific insured’s risk profile, legal interpretation of policy language under applicable state law, or an experienced underwriter’s assessment of insurer financial strength and claims handling quality.

You are an experienced insurance advisor preparing a coverage recommendation letter for a client. Based on the client profile and risk assessment I provide, draft a professional recommendation letter that includes:

1. **Header**: Your agency name, client name, date, and subject line referencing the coverage review.
2. **Current Coverage Summary**: Briefly summarize the client's existing coverages, limits, and deductibles.
3. **Risk Assessment**: Identify the key risks facing this client based on their industry, operations, and profile.
4. **Coverage Gap Analysis**: For each identified gap between the client's current coverage and their risk exposure, explain:
   - What the gap is
   - Why it matters for this client specifically
   - What could happen if the gap is not addressed (a brief, realistic scenario)
5. **Recommended Additional Coverages**: For each recommendation, provide:
   - The coverage type and suggested limits
   - Why this coverage is appropriate for the client's risk profile
   - Estimated premium impact (range, if possible, based on general market conditions)
   - Priority level (Critical, Recommended, or Optional)
6. **Summary Table**: A table listing all recommendations with coverage type, suggested limit, priority, and estimated annual premium range.
7. **Next Steps**: Suggest a meeting to discuss the recommendations and outline the process for binding additional coverage.

Tone: Professional, advisory, and client-focused. Explain insurance concepts in plain language.

Here is the client information:

Client name: [CLIENT NAME]
Industry: [INDUSTRY / BUSINESS TYPE]
Annual revenue: [REVENUE]
Number of employees: [NUMBER]
Locations: [LOCATIONS]
Current coverages: [LIST CURRENT POLICIES WITH LIMITS AND DEDUCTIBLES]
Recent claims history: [SUMMARY OF CLAIMS IN PAST 3-5 YEARS]
Known risk concerns: [ANY SPECIFIC RISKS THE CLIENT HAS MENTIONED]

Consejos

• The more detail you provide about the client's operations, the more targeted the recommendations will be. Include information about their industry, geography, employee count, and any unique exposures.
• After generating the letter, follow up with: 'What additional questions should I ask this client to refine these recommendations?' to identify information gaps.
• Use this output as a first draft for internal review. Customize premium estimates based on actual market quotes before sending to the client.
• Pair this Quick Win with the policy comparison prompt to show the client exactly how their current coverage compares to what you are recommending.

Precauciones

• Premium estimates generated by AI are approximations based on general knowledge. Always obtain actual quotes from carriers before presenting specific premium figures to clients.
• Coverage recommendations must reflect the client's specific risk profile and your professional assessment. Do not rely solely on AI-generated analysis for coverage adequacy opinions.
• Regulatory requirements for coverage recommendations vary by jurisdiction. Some states require specific disclosures when recommending or declining to recommend certain coverages.
• Do not include confidential client information in consumer AI tools. Use enterprise versions with appropriate data handling agreements.

What This Quick Win Does

A well-crafted coverage recommendation letter is one of the most valuable deliverables an insurance professional can provide to a client. It demonstrates expertise, builds trust, and helps clients understand why they need specific coverages. However, writing a thorough recommendation letter — one that analyzes current coverage, identifies gaps, and provides risk-based justifications — can take an hour or more per client.

AI can generate a structured first draft in approximately 5 minutes. The output includes a current coverage analysis, gap identification, specific recommendations with priority rankings, and estimated premium impacts. You then refine it with your professional knowledge of the client’s business, actual market quotes, and your advisory judgment.

This Quick Win is particularly useful during annual coverage reviews, when onboarding new commercial clients, or when a client’s risk profile changes due to growth, new operations, or acquisitions.

How to Use It

Step 1: Compile the Client Profile

Before using the prompt, gather:

• Current policy declarations pages (or a summary of all active coverages with limits and deductibles)
• Client’s industry, revenue, employee count, and locations
• Claims history for the past 3-5 years
• Any risk concerns the client has raised
• Notes from your most recent conversation about their business operations and plans

The more context you provide, the more tailored the recommendations will be.

Step 2: Input the Information

Paste the prompt into your AI tool and replace each placeholder with the client’s actual information. Be specific — instead of “manufacturing company,” write “custom metal fabrication shop with CNC equipment, handling steel and aluminum, with a spray painting booth.”

Step 3: Review the Recommendations

Read the output critically:

• Are the identified gaps genuine for this client’s risk profile?
• Are the recommended coverages available in the current market?
• Are the priority rankings appropriate given what you know about the client’s risk tolerance and budget?
• Do the premium estimates fall within a reasonable range based on your market experience?

Remove any recommendations that do not apply and add any that the AI missed based on your knowledge of the client.

Step 4: Customize and Finalize

Replace the AI’s estimated premium ranges with actual quotes from carriers. Add client-specific context that only you would know — for example, a planned expansion, a recent incident that did not result in a claim, or a specific contractual requirement from one of their customers. Have the letter reviewed internally before sending to the client.

What This Does Not Replace

This Quick Win accelerates the drafting process. It does not replace your professional judgment about what coverages a specific client needs, actual market quotes from carriers, or the relationship-based advisory that comes from knowing your client’s business personally.

You are an insurance data analyst specializing in loss analysis. I will provide a loss run report. Please analyze the data and produce a comprehensive report with the following sections:

1. **Executive Summary**: A 3-5 sentence overview of the loss history and key takeaways.
2. **Loss Frequency & Severity Trends**: Analyze the number of claims and average claim amounts over the reporting period. Identify any upward or downward trends.
3. **Top Causes of Loss**: Rank the causes of loss by total incurred amount and by frequency. Identify the top 3-5 drivers.
4. **Open vs. Closed Claims Summary**: Summarize the number and value of open claims versus closed claims. Flag any aging open claims that may need reserve review.
5. **Loss Ratio Calculation**: Calculate the loss ratio (total incurred losses / earned premium) for each year if premium data is available. Note the trend.
6. **Reserve Adequacy Assessment**: For open claims, assess whether reserves appear adequate based on the claim descriptions and current incurred amounts. Flag any claims where reserves may need adjustment.
7. **Year-Over-Year Comparison**: Compare each year's loss experience to the prior year. Highlight significant changes in frequency, severity, or loss causes.
8. **Risk Improvement Recommendations**: Based on the loss patterns identified, provide 5-7 specific, actionable recommendations to reduce future losses. Prioritize by expected impact.

Format with clear headings, tables where appropriate, and bullet points for readability. Include a summary table at the end.

Here is the loss run data:

[PASTE LOSS RUN REPORT HERE]

Consejos

• For best results, include all columns from the loss run: claim number, date of loss, report date, claimant, cause of loss, status, paid amounts, reserved amounts, and total incurred.
• If premium data is available, include it so the AI can calculate loss ratios. Without premium data, the analysis will focus on loss trends only.
• Follow up with: 'Based on this analysis, what underwriting questions would a carrier likely ask at renewal?' to prepare for renewal negotiations.
• Run this analysis annually and ask the AI to compare the current year's results to last year's analysis to track whether risk improvements are working.

Precauciones

• Loss run data may contain errors or inconsistencies from the carrier's system. Verify key figures against your own records before relying on the analysis.
• AI cannot assess reserve adequacy with the same precision as an experienced adjuster who knows the individual claim circumstances. Use reserve assessments as flags for further review, not as final determinations.
• Loss run reports may contain personally identifiable information. Redact claimant names and sensitive details before pasting into AI tools.
• Historical loss patterns do not guarantee future results. Use trend analysis as one input to risk management decisions, not the sole basis.

What This Quick Win Does

Loss run analysis is a cornerstone of risk management and renewal preparation. A loss run report — the detailed record of an insured’s claims history provided by their carrier — contains critical data about what is going wrong, how often, and at what cost. But raw loss run data is often delivered as dense spreadsheets or flat PDF tables that require significant manual effort to interpret.

AI can process a loss run report and produce a structured analysis in approximately 3 minutes. The output identifies frequency and severity trends, ranks the top causes of loss, calculates loss ratios, flags open claims that may need attention, and provides specific risk improvement recommendations. This gives you a working analysis to refine and present, rather than starting from a blank page.

This Quick Win is especially valuable when preparing for renewals, conducting stewardship reviews, or helping clients develop risk management programs based on their actual loss experience.

How to Use It

Step 1: Gather the Loss Run Data

Obtain the loss run report from the carrier. Ideally, request at least 3-5 years of data to enable meaningful trend analysis. Convert the report to text format if it is in PDF. Include all available data fields — claim number, date of loss, date reported, cause of loss, status, paid amounts, reserved amounts, and total incurred.

If premium data is available for the same period, include it so the AI can calculate loss ratios.

Step 2: Redact and Paste

Remove any personally identifiable information (claimant names, Social Security numbers, medical details) before pasting into your AI tool. Replace names with generic identifiers if needed (e.g., “Claimant 1,” “Claimant 2”).

Paste the prompt and the cleaned data into your AI tool.

Step 3: Review the Analysis

Read the output with a critical eye:

• Do the frequency and severity trends match your understanding of the account?
• Are the top causes of loss accurately identified?
• Do the loss ratio calculations align with what you would expect?
• Are the reserve adequacy flags reasonable given what you know about the open claims?

Correct any errors and add context that the AI cannot know — for example, that a spike in claims was due to a specific weather event, or that a particular open claim is in litigation.

Step 4: Apply the Recommendations

The risk improvement recommendations are based on the patterns in the data. Evaluate each one for feasibility and relevance to the client’s operations. Prioritize recommendations that address the top loss drivers and present them to the client as part of a risk management plan.

What This Does Not Replace

This Quick Win accelerates loss run analysis. It does not replace an experienced risk manager’s assessment of individual claim circumstances, actuarial analysis for reserve setting or loss projection, or the professional judgment required to translate data patterns into effective risk management strategies.

You are a senior underwriter reviewing an insurance application. Based on the application information I provide, generate a comprehensive set of supplemental underwriting questions organized into the following categories:

1. **Risk Characteristics Needing Clarification**: Questions about the applicant's operations, exposures, or risk profile that need further detail before a coverage decision can be made.
   - For each question, note: *Why it matters* — briefly explain how the answer affects the underwriting decision.

2. **Coverage Adequacy Concerns**: Questions about whether the requested limits, deductibles, and coverage structure are appropriate for the applicant's risk profile.
   - For each question, note: *Why it matters* — explain what coverage gap or over-insurance risk you are probing.

3. **Loss History Follow-Up**: Questions about the applicant's reported claims history that require clarification, such as open claims, trends, or missing details.
   - For each question, note: *Why it matters* — explain what the answer reveals about future loss potential.

4. **Safety & Risk Management Practices**: Questions about the applicant's risk control measures, safety programs, business continuity plans, and loss prevention efforts.
   - For each question, note: *Why it matters* — explain how the presence or absence of these practices affects risk quality.

5. **Regulatory & Compliance Considerations**: Questions about the applicant's compliance with industry regulations, licensing requirements, or contractual obligations that affect insurability.
   - For each question, note: *Why it matters* — explain the regulatory or contractual risk at stake.

For each category, provide 3-5 targeted questions. Prioritize questions that would meaningfully change the underwriting outcome — do not include generic questions that apply to every risk.

Here is the application information:

[PASTE THE INSURANCE APPLICATION OR SUMMARIZE THE KEY DETAILS: applicant name, business type, industry, revenue, employees, locations, requested coverages, limits, deductibles, loss history, and any notable risk factors]

Consejos

• The more detail you provide from the application, the more specific and useful the questions will be. Include industry, operations description, revenue, and any unusual risk factors.
• This is an excellent training tool for junior underwriters. Have them compare the AI-generated questions to their own list and discuss any differences.
• After receiving the questions, follow up with: 'Based on typical risks for this industry, what are the three most critical pieces of information I need before quoting this account?'
• Run this prompt for each new submission to ensure consistency in your underwriting process and to avoid overlooking important questions.

Precauciones

• AI-generated questions are based on general underwriting principles. They may miss industry-specific or jurisdiction-specific considerations that an experienced underwriter would catch.
• Do not paste confidential applicant information into consumer AI tools. Use enterprise or API versions with appropriate data handling agreements.
• Supplemental questions should be relevant and non-discriminatory. Review all questions to ensure compliance with fair underwriting practices and applicable regulations.

What This Quick Win Does

Reviewing an insurance application and identifying the right follow-up questions is a skill that takes years to develop. Experienced underwriters instinctively know what to ask — what gaps in the application signal elevated risk, what loss history patterns require explanation, and what operational details determine whether a risk is acceptable. For newer underwriters, or for experienced underwriters working outside their usual line of business, this pattern recognition takes time.

AI can analyze an application and generate a structured set of supplemental questions in approximately 2 minutes. Each question comes with an explanation of why it matters, making the output both a practical tool and a learning resource. For experienced underwriters, it serves as a quick checklist to ensure nothing is overlooked during a busy submission cycle.

How to Use It

Step 1: Prepare the Application Information

Copy the key details from the insurance application, or summarize them. At minimum, include:

• Applicant name and business description
• Industry and operations
• Revenue and employee count
• Locations and territory
• Requested coverages, limits, and deductibles
• Loss history for the past 3-5 years
• Any risk factors that stand out to you

The more context you provide, the more targeted the questions will be.

Step 2: Generate the Questions

Paste the prompt and the application information into your AI tool. The AI will return a categorized set of questions with explanations.

Step 3: Review and Prioritize

Not every generated question will be relevant to every submission. Review the list and:

• Keep questions that address genuine gaps in the application
• Remove questions that the application already answers
• Add any questions specific to your company’s underwriting guidelines or appetite that the AI would not know about
• Prioritize questions that would materially affect your pricing or coverage decision

Step 4: Send to the Agent or Broker

Compile your final list of supplemental questions and send them to the submitting agent or broker. The “Why it matters” explanations can help you articulate to the agent why you need the information, which often results in faster, more complete responses.

What This Does Not Replace

This Quick Win helps generate and organize underwriting questions. It does not replace an underwriter’s professional judgment about risk acceptability, your company’s specific underwriting guidelines and appetite, or the nuanced assessment that comes from experience with a particular line of business or industry segment.

You are an insurance compliance officer creating a regulatory compliance checklist. Based on the jurisdiction and line of business I specify, create a comprehensive checklist covering the following areas:

1. **Licensing Requirements**: What licenses and appointments are required to transact this line of business in this jurisdiction? Include producer, adjuster, and company-level requirements.

2. **Rate & Form Filing Obligations**: What are the filing requirements for policy forms and rates? Is this a prior approval, file-and-use, or use-and-file state for this line? What are the filing timelines and procedures?

3. **Market Conduct Standards**: What are the key market conduct requirements? Include advertising standards, producer supervision obligations, and prohibited practices.

4. **Claims Handling Requirements**: What are the regulatory requirements for claims handling? Include prompt payment laws, claims acknowledgment timelines, and required disclosures to claimants.

5. **Data Privacy Obligations**: What data privacy and security requirements apply? Include state-specific data breach notification laws, consumer data rights, and data retention requirements.

6. **Anti-Discrimination Requirements**: What are the prohibited underwriting and rating factors? Include fair lending crossovers, protected classes, and any specific guidance on proxy discrimination.

7. **Consumer Notification Requirements**: What notices must be provided to policyholders and applicants? Include adverse action notices, cancellation/non-renewal notices, and privacy notices.

8. **AI & Algorithmic Governance Requirements**: What requirements exist for the use of AI, predictive models, or algorithmic decision-making in underwriting, rating, or claims? Include any testing, validation, or disclosure obligations.

For each item in the checklist, provide:
- The specific requirement
- The applicable statute, regulation, or bulletin (cite by name and number where possible)
- The compliance deadline or frequency (e.g., "within 15 days," "annually," "prior to use")
- The consequence of non-compliance (e.g., fines, license action, private right of action)

Format as a structured checklist with checkboxes for each requirement.

Jurisdiction: [STATE OR JURISDICTION]
Line of business: [e.g., "Commercial General Liability," "Workers' Compensation," "Personal Auto," "Homeowners"]
Company type: [e.g., "Admitted carrier," "Surplus lines," "Managing General Agent," "Independent agency"]

Consejos

• Run this prompt separately for each state where you operate to build a jurisdiction-by-jurisdiction compliance matrix.
• After generating the checklist, follow up with: 'What are the most common compliance violations in [state] for [line of business], and how can we proactively avoid them?'
• Update the checklist quarterly by running the prompt again and asking the AI to identify any new regulations, bulletins, or enforcement actions since the last review.
• Use the output as a starting framework for your compliance management system, not as a finished compliance program.

Precauciones

• AI knowledge of specific state regulations may be outdated or incomplete. Every item on the checklist must be independently verified against current statutes, regulations, and department bulletins.
• Insurance regulation changes frequently. New bulletins, enforcement actions, and legislative amendments can alter compliance requirements at any time. This checklist is a snapshot, not a living document.
• AI governance requirements are evolving rapidly across jurisdictions. The NAIC and individual states are actively developing new requirements. Verify this section particularly carefully.
• This checklist does not constitute legal advice. Consult with compliance counsel for definitive guidance on regulatory obligations.

What This Quick Win Does

Insurance compliance is a complex, multi-jurisdictional challenge. A company operating in multiple states must track hundreds of regulatory requirements spanning licensing, rate filings, market conduct, claims handling, data privacy, and — increasingly — AI governance. Building and maintaining compliance checklists for each jurisdiction and line of business is a significant ongoing effort.

AI can generate a structured first-draft checklist in approximately 5 minutes, covering the major categories of regulatory requirements for a specific state and line of business. The output provides a framework that your compliance team can verify, refine, and incorporate into your compliance management program. It is especially useful when entering a new state, launching a new product line, or conducting an internal compliance audit.

This is an advanced Quick Win because the output requires substantial verification. Insurance regulation is detailed, jurisdiction-specific, and frequently changing. The AI-generated checklist is a starting point for research, not a finished compliance program.

How to Use It

Step 1: Define the Scope

Determine the jurisdiction, line of business, and company type you need to assess. The more specific you are, the more targeted the checklist will be. For example, “admitted carrier writing personal auto in California” will produce a more useful output than “auto insurance.”

If you operate in multiple states, run the prompt separately for each jurisdiction to build a comparative compliance matrix.

Step 2: Generate the Checklist

Paste the prompt into your AI tool with the specific jurisdiction and line of business details. The AI will return a structured checklist organized by regulatory category.

Step 3: Verify Every Item

This is the most critical step. For each item on the checklist:

• Confirm the cited statute or regulation exists and is current
• Verify the specific requirements match the actual regulatory text
• Check for recent bulletins, enforcement actions, or amendments that may modify the requirement
• Consult your compliance counsel for any items that are ambiguous or high-risk

Do not assume the AI’s citations are accurate. Cross-reference against official sources: state insurance department websites, the NAIC’s model law database, and your compliance counsel’s guidance.

Step 4: Integrate into Your Compliance Program

Once verified, incorporate the checklist into your compliance management system. Assign owners to each requirement, set monitoring frequencies, and establish a process for tracking regulatory changes that may affect the checklist.

What This Does Not Replace

This Quick Win generates a compliance research starting point. It does not replace a qualified compliance officer’s review of actual regulatory text, legal counsel’s interpretation of how requirements apply to your specific operations, or an ongoing regulatory monitoring program that tracks new legislation, regulations, and enforcement actions in real time.

You are a Special Investigations Unit (SIU) analyst at an insurance company. Based on the claim information and red flags I describe, create a structured fraud investigation outline with the following sections:

1. **Summary of Red Flags**: Organize the identified red flags by category (e.g., claim circumstances, claimant behavior, documentation inconsistencies, financial indicators). For each red flag, rate its significance as High, Medium, or Low.

2. **Investigation Plan**: Outline the specific steps to investigate each red flag, including:
   - **Interviews to conduct**: Who should be interviewed, what key questions to ask, and in what order
   - **Documents to obtain**: Specific records to request (police reports, medical records, financial documents, phone records, social media, etc.)
   - **Surveillance considerations**: Whether surveillance is warranted based on the red flags, what type, and what outcome would support or refute the fraud hypothesis
   - **Database searches**: Which industry databases to query (NICB, ISO ClaimSearch, LexisNexis, etc.) and what to look for

3. **Applicable Fraud Indicators**: List the recognized industry fraud indicators (from NICB, CAIF, or ISO) that match this claim's characteristics. Note how many indicators are present and what threshold typically triggers a referral.

4. **Relevant State Fraud Statutes**: Identify the applicable state insurance fraud statutes, including:
   - Criminal fraud statute (citation and elements of the offense)
   - Civil fraud remedies available to the insurer
   - Mandatory reporting obligations to the state fraud bureau
   - Immunity provisions for good-faith fraud reporting

5. **Evidence Preservation Requirements**: List the evidence that must be preserved, proper chain-of-custody procedures, and documentation standards for each type of evidence.

6. **Investigation Timeline**: Provide a suggested timeline with milestones:
   - Initial review and triage (days 1-3)
   - Document collection phase (days 3-14)
   - Interview phase (days 14-30)
   - Analysis and determination (days 30-45)
   - Reporting and referral (if warranted)

Format with clear headings, bullet points, and a priority matrix for investigation steps.

Here is the claim information:

Claim number: [CLAIM NUMBER]
Line of business: [e.g., "Auto," "Property," "Workers' Compensation," "Disability"]
Date of loss: [DATE]
Jurisdiction: [STATE]
Claim summary: [BRIEF DESCRIPTION OF THE CLAIMED LOSS]
Red flags identified: [LIST THE SPECIFIC RED FLAGS THAT TRIGGERED THE SIU REFERRAL]
Claimant information: [RELEVANT BACKGROUND — e.g., prior claims history, financial status if known, any prior fraud referrals]

Consejos

• Be specific about the red flags you have identified. The more detail you provide, the more targeted the investigation plan will be.
• After generating the outline, follow up with: 'What additional red flags should I look for in a [line of business] claim with these characteristics?' to identify indicators you may have missed.
• Use this outline as a case management framework. Update it as the investigation progresses and new information emerges.
• For complex or multi-party fraud schemes, run the prompt separately for each claimant or entity involved, then ask the AI to identify connections between them.

Precauciones

• Fraud investigations have significant legal implications. This outline is a planning tool — all investigation activities must comply with applicable laws, regulations, and your company's SIU protocols.
• State fraud statutes cited by the AI must be independently verified. Laws change, and the AI may not reflect the most current amendments or case law interpretations.
• Surveillance and recorded statements are subject to state-specific legal requirements. Verify that any planned surveillance or recording complies with your jurisdiction's laws before proceeding.
• Do not paste claimant personally identifiable information, medical records, or sensitive investigation details into consumer AI tools. Use enterprise versions with appropriate data protections and legal hold procedures.

What This Quick Win Does

When a claim is referred to the Special Investigations Unit, the SIU analyst must quickly organize a complex set of information — red flags, investigation leads, legal requirements, and evidence considerations — into a structured investigation plan. This planning phase is critical: a disorganized investigation can miss key evidence, violate legal requirements, or fail to build a case that withstands scrutiny.

AI can generate a structured investigation outline in approximately 5 minutes, organizing the red flags, mapping out investigation steps, identifying applicable fraud statutes, and creating an investigation timeline. This gives the SIU analyst a comprehensive framework to work from, ensuring that no major investigation avenue is overlooked.

This is an advanced Quick Win because fraud investigations carry significant legal and regulatory implications. The AI-generated outline is a planning tool that must be reviewed by experienced SIU professionals and, where appropriate, legal counsel before investigation activities begin.

How to Use It

Step 1: Document the Red Flags

Before using the prompt, compile all the red flags that triggered the SIU referral. Be specific:

• Instead of “suspicious timing,” write “claim filed 3 days after policy inception with no prior insurance history for 6 months”
• Instead of “documentation issues,” write “repair estimate from a shop 45 miles from claimant’s home, estimate prepared before the inspection appointment”
• Include any relevant background: prior claims history, financial indicators, and information from the adjuster’s file notes

Step 2: Generate the Investigation Outline

Paste the prompt and your claim information into your AI tool. The AI will produce a structured outline covering all major aspects of the investigation.

Step 3: Review and Customize

Review the outline against your company’s SIU protocols and the specific circumstances of the claim:

• Are the recommended investigation steps appropriate and proportional to the claim?
• Do the suggested interviews and document requests align with what is available and legally obtainable?
• Are the cited fraud statutes accurate for your jurisdiction?
• Does the timeline align with any applicable policy or regulatory deadlines?

Add any investigation steps specific to your company’s procedures or the unique facts of the case.

Step 4: Execute and Update

Use the outline as a living document throughout the investigation. Update it as new information emerges, new red flags are identified, or investigation steps are completed. The structured format makes it straightforward to track progress and document the investigation for regulatory reporting or litigation purposes.

What This Does Not Replace

This Quick Win helps organize an investigation. It does not replace the judgment of an experienced SIU analyst, legal counsel’s guidance on investigation procedures and evidence admissibility, or the regulatory requirements specific to your jurisdiction for fraud investigation and reporting.