Applicant Authenticity Analyzer avatar

Applicant Authenticity Analyzer

Pricing

Pay per event

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Applicant Authenticity Analyzer

Applicant Authenticity Analyzer

Upload resumes, cover letters, or job application text to detect potential fraud. The actor extracts text from PDF/DOCX/TXT files, evaluates authenticity with OpenAI, and returns a verdict, score, and justification.

Pricing

Pay per event

Rating

5.0

(2)

Developer

ParseForge

ParseForge

Maintained by Community

Actor stats

0

Bookmarked

9

Total users

0

Monthly active users

16 hours ago

Last modified

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🔍 Applicant Authenticity Analyzer

Spot fraudulent job applications, AI-generated resumes, and inconsistent claims in seconds. This AI-powered analyzer cross-checks applicant credentials, work history, and skills against each other to flag red flags and score credibility. Perfect for recruiters screening high-volume applications, HR teams building fraud detection workflows, or hiring managers verifying applicants before phone screens. No spreadsheets, no manual verification, no guesswork.

The Applicant Authenticity Analyzer detects fraud and inconsistencies in job applications with AI analysis and a credibility score from 1-10, helping you identify trustworthy candidates and flag suspicious claims in seconds.

📋 How to Use

No technical skills required. Follow these simple steps:

  1. Sign Up - Create a free account with $5 credit
  2. Find the Tool - Search for "Applicant Authenticity Analyzer" in the Apify Store and configure your input
  3. Run It - Click "Start" and watch your results appear

That's it. No coding, no setup, no complicated configuration. Now you can export your analysis results in CSV, Excel, or JSON format.

📊 Data fields

Each record includes: aiModel, aiProvider, authenticityExplanation, authenticityScore, authenticityVerdict, candidateId, confidence, email, fullName, heuristicSignals, isAuthentic, jobContextCompany, jobContextTitle, location, phone, processedAt, profileImageUrl, recommendedActions, riskLevel, riskScore, riskThreshold, supportingEvidence, suspiciousIndicators. All 23 field names come from a real production run, so what you see here is what lands in your dataset.

🆘 Need Help?

If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.

For faster answers, join our Discord. It's the best place to get support and suggest new actors.