Inscribe GTM brain

category

market profile

• text: Financial institutions must detect fabricated or altered financial documents while moving legitimate applicants through underwriting quickly.
• text: Generative AI is changing document fraud and putting pressure on manual review processes.
• text: Vendors compete on forensic detection, financial data extraction, investigation and coverage of different document types.

personas

• title: Head of fraud or financial crime
  pains:

  • Fake bank statements and pay stubs escape manual review
  • Must reduce fraud losses while keeping false positives manageable
• title: Lending underwriting operations leader
  pains:

  • Manual document checks slow approval and increase cost per application
  • Inconsistent review decisions create operational and audit concerns
• title: Credit union risk or account protection manager
  pains:

  • Fraud rings target onboarding and lending workflows
  • Must demonstrate prevented losses and support investigators with usable evidence

icp

• text: US banks, credit unions, fintechs and lenders that review bank statements, pay stubs and tax documents in underwriting or onboarding.
• text: Financial institutions with material application volume, manual review queues and a dedicated fraud or risk team.
• text: Organizations seeking an API or web application for configurable fraud checks and risk decisions.

message pillars

• text: Detect AI-generated and altered financial documents.
• text: Reduce the labor of manual review.
• text: Improve decision speed while managing risk.
• text: Combine different detection methods for a fuller view.

objections

• objection: Will this create too many false positives or miss our fraud patterns?
  response: Use the complimentary pilot and representative documents to measure detection performance against agreed criteria.
• objection: Our team needs evidence for a fraud decision, not just a score.
  response: Review the product's detection signals and investigation workflow using real cases during the pilot.
• objection: We need to justify cost and integration effort.
  response: Scope document volume, API or web app requirements, and pilot results to build a business case.

competitors

• name: Ocrolus
  why: Lending document automation and fraud signals for US lenders.
• name: Resistant AI
  why: Document forensic fraud detection for financial institutions.
• name: Sphinx
  why: Document fraud checks and investigation casework.
• name: Fortiro
  why: Financial and income document verification and fraud detection.

influencers

• name: Ronan Burke
  url: https://www.inscribe.ai/authors/ronan-burke
  why: Co-founder and CEO writing on financial document fraud.
• name: Conor Burke
  url: https://www.inscribe.ai/authors/conor-burke
  why: Co-founder and CTO writing on fraud detection engineering.

keywords

• document fraud detection software
• fake bank statement detection
• AI generated pay stub detection
• loan application fraud prevention
• credit union document verification
• automated underwriting fraud detection
• financial document forensics

voice

• Direct and urgent
• Fraud expert and evidence-led
• Practical about operations

signals

• text: A lender is seeing rising forged or AI-generated income documents.
• text: A bank or credit union is hiring fraud investigators or automating underwriting and onboarding.
• text: A financial institution is evaluating manual review costs and turnaround times.

stack

• Amazon Bedrock
• Amazon SageMaker
• API
• SSO

pricing

motion

channels

• SEO
• LinkedIn
• fraud reports
• podcast
• partners
• webinars

confidence

Founders

• name: Ronan Burke
  title: Founder/CEO
  role: CEO
• name: Conor Burke
  title: Founder/CTO
  role: CTO