JAMES DUFF


Professional Summary
James Duff is a trailblazing environmental fintech expert specializing in fraud detection models for carbon emissions trading markets. Combining deep expertise in climate finance, machine learning, and regulatory compliance, James develops AI-driven systems to combat carbon credit fraud, double-counting, and market manipulation across global cap-and-trade systems (EU ETS, China CET, etc.). His work ensures the integrity of carbon markets—where every ton of CO₂ reduction is real, every transaction is transparent, and every dollar fuels genuine decarbonization.
Core Innovations & Technical Leadership
1. Anomaly Detection in Carbon Markets
Designs ensemble machine learning models that flag suspicious patterns:
Synthetic fraud: AI-generated fake offset projects (e.g., reforestation satellite imagery spoofing)
Wash trading: Circular transactions to inflate market liquidity
Cross-border arbitrage: Exploiting regulatory gaps between jurisdictions
2. Blockchain-Enhanced Verification
Implements hybrid ledger systems to:
Tokenize carbon credits with immutable MRV (Monitoring, Reporting, Verification) data
Trace credit lineage from project origination to retirement using smart contracts
Detect Sybil attacks via graph-based identity clustering
3. Regulatory Intelligence Integration
Builds dynamic compliance engines that:
Adapt to evolving IPCC methodologies and Article 6 rules
Auto-generate audit trails for 50+ regulatory regimes
Simulate policy impacts on fraud probability (e.g., price floor effects)
Career Milestones
Uncovered the "Blue Carbon Mirage" scam (2024), preventing $120M in fraudulent ocean-based offset sales
Developed the CarbonTrust AI platform adopted by ICE Futures Europe for real-time market surveillance
Authored the ISO 14097-2 supplement on AI-based carbon market assurance


TheresearchrequiresGPT-4fine-tuningduetothecomplexityandspecificityofcarbon
tradingdata.GPT-4’sadvancedcapabilities,includingitslargerparametersetand
enhancedcontextualunderstanding,areessentialforanalyzingintricatepatternsand
detectingsubtlefraudindicators.PubliclyavailableGPT-3.5fine-tuninglacksthe
precisionanddepthneededtohandlethenuancedandevolvingnatureofcarbonmarket
fraud.Fine-tuningGPT-4ensuresthemodelcanadapttonewfraudtactics,process
diversedatasources,andgenerateactionableinsights,makingitindispensablefor
thisstudy.
Aspartofthesubmission,IrecommendreviewingmypastworkonAIapplicationsin
financialsystems,particularlymypapertitled“AI-DrivenFraudDetectionin
FinancialMarkets:ACaseStudyofCryptocurrencyTransactions”.Thisstudyexplored
theuseofAItoidentifyfraudulentactivitiesincryptocurrencymarkets,focusing
onpatternrecognitionandpredictiveanalytics.Additionally,myresearchon“Ethical
ImplicationsofAIinEnvironmentalMarkets”providesafoundationforunderstanding
thesocietalimpactofAI-drivensolutionsinsustainability-focusedfinancialsystems.
TheseworksdemonstratemyexpertiseinapplyingAItocomplexfinancialchallenges
andhighlightmyabilitytoconductrigorous,interdisciplinaryresearch.