Open Claims
284
Across all lines
Fraud Flags Active
7
Investigator review needed
Auto-Adjudicated Today
184
65% straight-through
Avg Settlement Time
3.2d
vs 21d industry avg
π€ AI Agent Status
14 insurance AI agents across claims, underwriting, fraud, and compliance
Fraud Detection Engine7 flags Β· investigating
Claims Triage AI284 claims classified
Underwriting AI47 policies reviewed
Document Intelligence847 docs processed
Actuarial IntelligencePortfolio risk updated
Regulatory ComplianceAll filings current
π‘ Live Claims Intelligence Feed
Real-time AI activity across all insurance operations
Priority Claims Requiring Attention
CLM-2024-08471
FRAUD SUSPECTEDCommercial Property β Β£284,000
AI: 3rd fire claim in 24 months Β· supplier link anomaly Β· 0.91 fraud score
CLM-2024-07823
COMPLEXEmployers Liability β Β£1.2M
AI: Liability disputed Β· medical evidence inconsistent Β· reserve Β£1.4M
CLM-2024-09102
AUTO-SETTLEMotor Own Damage β Β£4,200
AI: Liability clear Β· repair validated Β· recommend immediate settlement
Why InsuranceOS
π Insurance Fraud: Β£3.2B/Year
UK insurance fraud costs Β£3.2B annually. 80% of fraud is organised and cross-claim β invisible to per-claim manual review. InsuranceOS detects network patterns, supplier links, and behavioural anomalies across the entire claims portfolio simultaneously.
β± Claims: 21 Days Too Long
Industry average claims settlement: 21 days. InsuranceOS triages, validates, and auto-adjudicates 65% of straight-through claims in under 4 hours. Complex claims handled in 3.2 days. Customer satisfaction: 4.7/5 vs 3.1 industry average.
π Underwriting: Mispriced Risk
Manual underwriting misses signals visible only in aggregate data. AI underwriting combines real-time telematics, satellite imagery, social signals, and claims history to price risk with 34% lower combined ratio than traditional approaches.
Fraud Suspected
7
Complex / Disputed
34
Straight-Through
184
Under Review
59
Total Reserve
Β£8.4M
Active Claims Queue
CLM-2024-08471
FRAUD: 0.91Commercial Property Β· Β£284,000
CLM-2024-07341
FRAUD: 0.84Motor Theft Β· Β£28,000
CLM-2024-07823
COMPLEXEmployers Liability Β· Β£1.2M
CLM-2024-08904
REVIEWProfessional Indemnity Β· Β£180,000
CLM-2024-09102
AUTO-SETTLEMotor OD Β· Β£4,200
CLM-2024-09241
AUTO-SETTLEHome Contents Β· Β£2,800
Claim Detail β CLM-2024-08471
Commercial Property Fire β Β£284,000
Claimant: Meridian Holdings Ltd Β· Notified: 18 May 2026
Claim Value
Β£284,000
Prior Claims
2 fires in 24 months
Fraud Score
0.91 β VERY HIGH
Network Flag
Supplier link detected
β AI Fraud Intelligence
1. 3rd fire claim from same insured in 24 months β pattern anomaly flagged
2. Loss assessor (J. Connell & Associates) linked to 4 other suspicious fire claims in 18 months
3. Business financial distress signals: CCJs filed against Meridian in Q1 2026
4. Satellite imagery: no fire damage visible to neighbouring structures (inconsistent with claimed cause)
2. Loss assessor (J. Connell & Associates) linked to 4 other suspicious fire claims in 18 months
3. Business financial distress signals: CCJs filed against Meridian in Q1 2026
4. Satellite imagery: no fire damage visible to neighbouring structures (inconsistent with claimed cause)
Total Agents
14
Decisions Today
2,847
Fraud Flags
7
Auto-Settled
184
Claims Intelligence Agents
Fraud Detection Engine
Network analysis across claimants, suppliers, solicitors, and loss adjusters. Detects organised fraud rings invisible to per-claim review. Cross-references against industry fraud databases and internal claim history.
Running Β· 7 flags active
ReAct + Network GraphClaims Triage AI
Classifies every inbound claim into straight-through, complex, fraud-suspected, or manual-review paths within 60 seconds. Routes automatically to correct workflow. 65% straight-through rate.
Running Β· 284 classified
Sequential + MLDocument Intelligence
Extracts structured data from police reports, medical records, invoices, repair estimates, and correspondence. Validates internal consistency and cross-references against policy terms and prior claims.
Running Β· 847 docs
Reflection + VisionUnderwriting & Risk Agents
AI Underwriting Engine
Risk scoring from telematics, satellite imagery, social signals, and claims history. Recommends premium, terms, and exclusions for new and renewal business. Underwriter review and approval required.
Running Β· 47 policies
Reflection + QuantActuarial Intelligence
Continuous portfolio loss ratio monitoring, reserve adequacy analysis, emerging risk identification, and pricing adequacy signals. Actuarial sign-off required on all reserve recommendations.
Running Β· Portfolio live
Reflection + StatisticsCatastrophe Risk Monitor
Monitors natural catastrophe exposures, climate risk signals, and accumulation of correlated risks across the portfolio. PML estimates updated dynamically from weather and geological data.
Processing Β· Live data
ReAct + Geo DataOperations Agents
Customer Intelligence
Predicts churn risk, identifies cross-sell opportunities, personalises communication, and monitors customer satisfaction signals. Retention intervention triggered 90 days before renewal for at-risk customers.
Running Β· 12K policies
ReAct + SignalsSubrogation AI
Identifies subrogation and contribution opportunities in settled claims. Calculates recovery likelihood and value. Drafts letter of claim and coordinates with third-party insurers. Solicitor review required.
Running Β· Β£847K pipeline
Reflection + LegalRegulatory Compliance
Monitors FCA conduct requirements, Solvency II capital adequacy, GDPR for claims data, and Lloyd's reporting obligations. Flags compliance gaps before regulatory breach. All submissions FCA-standard.
Running Β· All compliant
Sequential + RulesActive Fraud Flags
7
Detected This Month
Β£2.1M
Fraud prevented
Detection Rate
97%
vs 34% manual
False Positive Rate
3.2%
vs 12% industry avg
Top Fraud Alerts
π Organised Fraud Ring β 4 Claims Β· Β£847,000 Total Exposure
RING: 0.94Network analysis identified 4 claims (CLM-08471, CLM-07341, CLM-06892, CLM-08124) connected via shared loss assessor (J. Connell & Associates), common solicitor (Avon Legal LLP), and financial distress signals across all claimants. CLM-07341 vehicle previously "stolen" and found β same garage as current theft claim. Ring confidence: 0.94.
CLM-08471 Β· Meridian Holdings Β· Fire Β£284K Β· Assessor: J.Connell
CLM-07341 Β· R. Hassan Β· Motor theft Β£28K Β· Garage: QuickFix Bristol
CLM-06892 Β· Delta Properties Β· Water damage Β£320K Β· Assessor: J.Connell
CLM-08124 Β· T. Associates Β· Burglary Β£215K Β· Solicitor: Avon Legal LLP
CLM-07341 Β· R. Hassan Β· Motor theft Β£28K Β· Garage: QuickFix Bristol
CLM-06892 Β· Delta Properties Β· Water damage Β£320K Β· Assessor: J.Connell
CLM-08124 Β· T. Associates Β· Burglary Β£215K Β· Solicitor: Avon Legal LLP
Fraud Detection β 5 Signal Types
πΈ Network Analysis
Maps connections between claimants, loss adjusters, solicitors, repair garages, and medical providers. Identifies rings and clusters invisible to individual claim review. Updates in real time as new claims arrive.
π Behavioural Signals
Claim timing patterns (e.g. claims filed shortly after premium increase), notification delays, inconsistent event narratives, and history of prior claims across the industry database (IFB cross-reference).
π° External Data
Satellite imagery, weather data, Companies House records, CCJ filings, DVLA data, and social media signals cross-referenced against claim circumstances to identify implausible or inconsistent claims.
Policies Reviewed
47
Combined Ratio (AI)
82%
vs 94% manual baseline
Pricing Accuracy
+34%
vs manual assessment
Declination Rate
12%
High-risk correctly declined
π AI Underwriting β Commercial Property
Risk 0847 Β· Riverside Industrial Estate Β· Β£4.2M TSI
INGEST β Survey, accounts, claims history parsed
GEO β Satellite: flood zone 2 Β· no recent damage
FIRE β Sprinkler system: confirmed Β· BAFE cert
CLAIMS β 1 minor claim Β£8K in 5yr Β· clean
PRICE β Rate: Β£0.12% of TSI Β· Β£5,040 premium
RECMD β ACCEPT Β· Standard terms Β· UW review
GEO β Satellite: flood zone 2 Β· no recent damage
FIRE β Sprinkler system: confirmed Β· BAFE cert
CLAIMS β 1 minor claim Β£8K in 5yr Β· clean
PRICE β Rate: Β£0.12% of TSI Β· Β£5,040 premium
RECMD β ACCEPT Β· Standard terms Β· UW review
AI Recommendation: Accept β Good risk. Sprinkler installed, clean claims history, flood zone acceptable. Recommended premium: Β£5,040 at 0.12% of TSI. Underwriter review and binding required.
π Underwriting Intelligence β Data Sources
7 data sources combined for every risk assessment
Claims history: Internal + IFB cross-industry database. 5-year loss pattern and frequency scoring.
Satellite & geo data: Flood zones, subsidence risk, crime rates, neighbouring hazards, building condition from aerial imagery.
Financial intelligence: Companies House, CCJ filings, credit signals β financial distress is a leading indicator of moral hazard.
Telematics (motor): Real-time driving behaviour data for motor risks β speed, braking, time-of-day, route risk.
Survey intelligence: AI reads survey reports, extracts defects, and scores risk quality β no manual summarisation needed.
Combined Ratio
84%
Portfolio YTD
Reserve Adequacy
101%
Emerging Risk Flags
3
Pricing Adequacy
+8%
Above required margin
π Actuarial Intelligence β What It Monitors
Actuarial Intelligence provides continuous portfolio analytics that previously required quarterly actuarial runs. Reserve adequacy is assessed daily against emerging claims development β flagging reserve deficiencies before they become material. Loss ratio monitoring by product line, geography, and distribution channel identifies adverse development early. Pricing adequacy analysis compares written premium rates against current loss cost trends β identifying lines where rates need adjustment before the underwriting cycle turns. Emerging risk signals: 3 currently flagged β climate-driven subsidence (South-East England), cyber supply chain (commercial lines), and electric vehicle battery fire claims frequency increase. All reserve and pricing recommendations require Chief Actuary review and sign-off.
Policies Monitored
12,847
Churn Risk Flags
384
Renewal in 90 days
Retention Rate (AI)
94%
vs 81% pre-AI
Customer Satisfaction
4.7/5
π¬ Customer Intelligence β Retention & Growth
Customer Intelligence monitors 12,847 policies for churn signals 90 days before renewal: price sensitivity (competitor quote requests), claim dissatisfaction scores, life event triggers (property purchase, new vehicle, business change), and engagement decline. Retention outreach is personalised β not a blanket renewal reminder. Cross-sell recommendations are generated from life event signals and coverage gap analysis (e.g. customer has home contents but no buildings β buildings cover recommended at renewal). NPS tracking and complaint root cause analysis feeds back into product and pricing development.
FCA Compliance
100%
Solvency II (SCR)
184%
Coverage ratio
Regulatory Filings
All current
Conduct Risk Flags
0
π Regulatory Compliance Intelligence
InsuranceOS maintains continuous compliance monitoring across all applicable regulatory frameworks. FCA Consumer Duty: all claims handling decisions monitored for fair customer outcomes β pricing, settlement, and communications reviewed for conduct risk. Solvency II: SCR and MCR calculations updated daily. GDPR: all claims data processing logged with purpose limitation and retention schedules enforced. Lloyd's reporting: bordereaux and premium accounts auto-generated. IDD compliance: all advice and recommendation processes documented for MiFID II equivalent insurance distribution standards. Regulatory examination readiness: evidence packs maintained and audit-ready at all times.
Recovery Pipeline
Β£847K
Recovery Rate (AI)
72%
vs 41% manual
Opportunities Found
47
This quarter
Avg Recovery Value
Β£18K
βοΈ Subrogation AI β Recovery Intelligence
Subrogation opportunities are often missed in manual claims processing because handlers are focused on settlement, not recovery. Subrogation AI reviews every settled claim for third-party liability β motor accidents, defective products, contractor negligence, and neighbour liability. It calculates recovery likelihood and estimated value, identifies the responsible third party and their insurer, drafts the letter of claim, and tracks the recovery process through to resolution. Solicitor review is required before any letter of claim is issued. Recovery rate with AI: 72% vs 41% manual. Average quarterly recovery uplift for a mid-size insurer: Β£340K.
Agents Active
14
Decisions/Day
2,847
Fraud Prevented
Β£2.1M
Compliance Events
0
π‘ Live Agent Trace
All AI decisions logged Β· FCA Β· Solvency II Β· GDPR compliant
π‘ Insurance AI Governance
Advisory intelligence β underwriters and adjusters decide
No autonomous claims decisions: All settlement, decline, and reserve decisions require authorised adjuster or underwriter approval. AI recommends and routes β humans decide and bind.
FCA Consumer Duty: All AI outputs monitored for fair customer outcomes. Explainability requirement met for every claims and underwriting decision β no black-box outputs.
Fraud referral protocol: All fraud flags presented as suspicions requiring investigation β never automated declines. IFB referral and SIU escalation follow defined protocols. Human judgment always governs outcome.
Actuarial sign-off: All reserve and pricing recommendations require Chief Actuary review. AI provides analysis β qualified actuaries certify reserves per regulatory requirements.