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Fnol In Insurance information

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$26K

$48.4K

$73K

How much do fnol in insurance jobs pay per year?

As of Jul 18, 2026, the average yearly pay for fnol in insurance in the United States is $48,409.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,000.00 and $55,000.00 per year, depending on experience, location, and employer.

What is the difference between Fnol In Insurance vs Claims Adjuster?

AspectFnol In InsuranceClaims Adjuster
Required credentialsInsurance license, customer service skillsInsurance license, appraisal skills
Work environmentOffice, remote, or on-site customer interactionsFieldwork, office, or remote assessments
Employer & industry usageInsurance companies, claims departmentsInsurance companies, third-party claims firms
Search & comparison intentUnderstanding initial claim reportingEvaluating and settling claims

Fnol In Insurance involves the initial reporting of claims, focusing on customer communication and data collection. Claims Adjusters assess and settle claims, often requiring appraisal skills. While both roles require insurance licensing, Fnol agents handle early-stage claims, whereas Claims Adjusters handle detailed evaluations and settlements.

More about Fnol In Insurance jobs
What cities are hiring for Fnol In Insurance jobs? Cities with the most Fnol In Insurance job openings:
What states have the most Fnol In Insurance jobs? States with the most job openings for Fnol In Insurance jobs include:
What job categories do people searching Fnol In Insurance jobs look for? The top searched job categories for Fnol In Insurance jobs are:
Fnol In Insurance jobs near you
Infographic showing various Fnol In Insurance job openings in the United States as of July 2026, with employment types broken down into 11% Locum Tenens, 9% Internship, 61% As Needed, 18% Nights, and 1% Summer. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $48,409 per year, or $23.3 per hour.

Claims Processing Agent - Freelance AI Trainer

Mind Rift

Remote

$60/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Mindrift AI Project Opportunity

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.

What this opportunity involves:

  • Evaluate AI-generated auto insurance claims decisions for accuracy, coverage correctness, and regulatory compliance;
  • Design FNOL scenarios with deliberate contradictions, decoy files, and outdated documents to test agent robustness;
  • Write and grade fraud-flagging scenarios using structured reason codes (late reporting, recently purchased policy, inconsistent damage) for SIU referral;
  • Build subrogation test cases applying state-specific negligence rules (comparative vs. contributory) and assess likelihood of recovery;
  • Document test cases clearly with correct answers, policy citations, and payout calculations.

What we look for:

  • Degree in Insurance, Risk Management, Business Administration, Finance, Law, or any related field;
  • 3+ years of insurance, claims, legal, or financial services experience;
  • Current or recent experience in claims & adjusting or adjacent roles;
  • Familiarity with auto insurance coverage decisions, state-specific negligence rules, and adjuster authority-limit culture;
  • AIC, CPCU, CIFI, or SCLA credential is a strong positive signal, though not required if hands-on experience is solid;
  • Strong written English (C1+).

How it works:

Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid

Project time expectations:

For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.

Compensation:

On this project, contributors can earn up to $60 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

Apply