Business ConsultingInsurance Claim Analyzer & Fraud Detection
Vision and document analysis assess accident impact and claim eligibility to cut fraudulent payouts.
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Enterprise AI for banking, financial services and insuranceClaims. Credit. Customers. Handled.
Banks and insurers use flock3 teammates to read claims, score risk and resolve requests. An officer approves every high-risk call.
$3Mprojected annual saving, P2P exceptions
95%precision on insurance claim models
20–30%lower cost to process a case
The challenge
What's in the way
Exceptions handled by hand
ERPs miss a large share of matches. Teams fix them one by one.
Fraud found too late
Claims and payments are checked after payout, when leakage is already lost.
Fragmented customer signals
CSAT drivers, complaints and loan requests sit in separate systems, so service and credit teams react slowly.
Focus use cases
What we automate
Bill of Claims Automation (KFB)
Extract, validate and adjudicate claim line items; flag fraud and exceptions for an adjuster.
Employee Referral Intelligence
Match referred candidates to open roles, screen profiles and track referral outcomes.
CSAT & Loan Intelligence (Barclays)
Track CSAT drivers from every interaction and pre-qualify loan requests with risk scoring.
Purchase-to-Pay Exceptions
Classify invoice exceptions and the contributing factors the ERP fails to match.
Also in the libraryKYC ID extractionRegulatory compliance mappingResearch assistant
Teammate swarm
Bill-of-Claims Swarm
Intake AgentClassifies documents and opens the case
Extractor AgentPulls line items, IDs and amounts with OCR and NLP
Policy AgentChecks every item against policy terms (RAG)
Fraud AgentScores risk with Intelligent Machine Learning models and history
Claims ManagerPlans, delegates and drafts the settlement
Human gateAdjuster approves high-value or high-risk settlements
KPIsCycle time · cost per claim · leakage · fraud caught
From the IntelliMesh use-case lab
More, ready to go
KYC Document Verification
Computer vision and OCR extract key fields from customer documents for onboarding and audit.
Insurance Query Assistant
ML, OCR, chatbot and compliance tools handle insurance queries, claim analysis and routing.
Built on acceleratorsFraud & Risk Intelligence · Computer Vision & Document AI · Biometric Payments & Voice Biometrics · Enterprise RAG & Knowledge
Use cases and accelerators co-developed with our US partner Mintmore Inc. See mintmore.us.
Case study · BFSI
Purchase-to-pay exception handling
Enterprise shared-services centre
The ERP missed 20%+ of invoice matches. An invoice teammate now sorts every exception and hands resolved cases to RPA.
$250Ksavings opportunity per month
$6cost eliminated per exception
Inside the PDF (8 pages, 4.0 MB)3-page case study: problem, approach, impact and the teammate swarm5 slides from the IntelliMesh.si Platform Overview and Teammate Swarm decksHow we engage: the 10·20·30 Pathway
Start the 10·20·30 Pathway
Prove it on your BFSI data in 20 days
Other industries
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Questions
BFSI AI, answered.
How does AI automate insurance claims?
Vera's Claims Teammate reads every line of a bill of claims, validates it against policy and history, scores fraud risk and drafts the settlement. Adjusters approve high-value or high-risk items.
What can AI do for banks?
Credit and loan pre-qualification, CSAT and ticket intelligence, fraud and AML scoring with reason codes, KYC document AI, employee referral matching and purchase-to-pay exception handling.