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

A hand holding a thermal scanner is pointed towards a rack of computer servers. The servers are illuminated with blue LED lights, giving a technological and futuristic feel.
A hand holding a thermal scanner is pointed towards a rack of computer servers. The servers are illuminated with blue LED lights, giving a technological and futuristic feel.

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.

A group of people are participating in a climate change protest on a city street. Several individuals hold signs, including one prominently displayed that reads 'Cut your carbon? Pledge to be flight free in 2020.' The participants appear to be diverse in age and are dressed casually.
A group of people are participating in a climate change protest on a city street. Several individuals hold signs, including one prominently displayed that reads 'Cut your carbon? Pledge to be flight free in 2020.' The participants appear to be diverse in age and are dressed casually.

Aspartofthesubmission,IrecommendreviewingmypastworkonAIapplicationsin

financialsystems,particularlymypapertitled“AI-DrivenFraudDetectionin

FinancialMarkets:ACaseStudyofCryptocurrencyTransactions”.Thisstudyexplored

theuseofAItoidentifyfraudulentactivitiesincryptocurrencymarkets,focusing

onpatternrecognitionandpredictiveanalytics.Additionally,myresearchon“Ethical

ImplicationsofAIinEnvironmentalMarkets”providesafoundationforunderstanding

thesocietalimpactofAI-drivensolutionsinsustainability-focusedfinancialsystems.

TheseworksdemonstratemyexpertiseinapplyingAItocomplexfinancialchallenges

andhighlightmyabilitytoconductrigorous,interdisciplinaryresearch.