Pioneering AI research in Financial Crime Compliance
We are pioneering the alignment of cutting-edge AI with the world’s most sensitive domain — financial crime compliance. By embedding explainability, oversight, and regulatory assurance, Arva helps ensure AI systems act safely, transparently, and in ways aligned with human and institutional values.
Pioneering AI research in Financial Crime Compliance
We are pioneering the alignment of cutting-edge AI with the world’s most sensitive domain — financial crime compliance. By embedding explainability, oversight, and regulatory assurance, Arva helps ensure AI systems act safely, transparently, and in ways aligned with human and institutional values.
Featured Customers
Featured Customers
Leading research at the forefront of innovation
Arva's Agent Lab is the research-first platform for deploying reliable, effective AI
1
Build
AI Agents, built on Arva Intel, our proprietary engine for deep
web intelligence
Entity Enrichment
Web Crawling
Data Intel
Custom Integrations
1
Build
AI Agents, built on Arva Intel, our proprietary engine for deep
web intelligence
Entity Enrichment
Web Crawling
Data Intel
Custom Integrations
2
Deploy
Test and deploy, ensuring robust AI that delivers every time,
at scale
Screening AI
TM AI
KYB / KYC AI
Custom
2
Deploy
Test and deploy, ensuring robust AI that delivers every time,
at scale
Screening AI
TM AI
KYB / KYC AI
Custom
3
Monitor
Monitor performance, with AI model risk governance
at heart
Benchmarks
Model Evalution
Risk Governance
3
Monitor
Monitor performance, with AI model risk governance
at heart
Benchmarks
Model Evalution
Risk Governance
Leading research at the forefront of innovation
Arva's Agent Lab is the research-first platform for deploying reliable, effective AI
1
Build
AI Agents, built on Arva Intel, our proprietary engine for deep
web intelligence
Entity Enrichment
Web Crawling
Data Intel
Custom Integrations
2
Deploy
Test and deploy, ensuring robust AI that delivers every time,
at scale
Screening AI
TM AI
KYB / KYC AI
Custom
3
Monitor
Monitor performance, with AI model risk governance
at heart
Benchmarks
Model Evalution
Risk Governance
Meet Arva Intel
Meet Arva Intel
Arva Intel is our proprietary engine for deep web intelligence, designed to uncover, enrich, and contextualize data sources that traditional screening tools miss. By scanning across the open web, dark web, and niche data ecosystems, Arva Intel surfaces risk signals that are invisible to conventional watchlists and databases.
Deep Web Coverage
Goes beyond standard adverse media to capture forums, blogs, and less structured sources where early indicators of financial crime often appear.
Deep Web Coverage
Goes beyond standard adverse media to capture forums, blogs, and less structured sources where early indicators of financial crime often appear.
Contextual Enrichment
Uses AI-driven entity resolution and semantic analysis to connect fragmented data points into coherent narratives.
Contextual Enrichment
Uses AI-driven entity resolution and semantic analysis to connect fragmented data points into coherent narratives.
Contextual Enrichment
Uses AI-driven entity resolution and semantic analysis to connect fragmented data points into coherent narratives.
Scalable
Handle cases perfectly in parallel, instantly scale up or down with volume, no need to outsource.
Scalable
Handle cases perfectly in parallel, instantly scale up or down with volume, no need to outsource.
Scalable
Handle cases perfectly in parallel, instantly scale up or down with volume, no need to outsource.
Adaptive Intelligence
Continuously learns from analyst feedback and evolving typologies, keeping pace with how criminal networks adapt.
Adaptive Intelligence
Continuously learns from analyst feedback and evolving typologies, keeping pace with how criminal networks adapt.
Audit-Ready Transparency
Every insight is logged with source citations and confidence scores, ensuring that intelligence remains defensible under regulatory review.
Audit-Ready Transparency
Every insight is logged with source citations and confidence scores, ensuring that intelligence remains defensible under regulatory review.
Audit-Ready Transparency
Every insight is logged with source citations and confidence scores, ensuring that intelligence remains defensible under regulatory review.
Multi-Layered Validation
Cross-verifies intelligence against structured data, reducing noise and false positives.
Multi-Layered Validation
Cross-verifies intelligence against structured data, reducing noise and false positives.
Multi-Layered Validation
Cross-verifies intelligence against structured data, reducing noise and false positives.
Key research pillars
Key research pillars
Transparency & Explainability
Every AI decision is accompanied by a plain-language rationale, confidence scores, and full audit trails to ensure regulatory readiness.
Transparency & Explainability
Every AI decision is accompanied by a plain-language rationale, confidence scores, and full audit trails to ensure regulatory readiness.
Evaluation & Benchmarking
Models are continuously monitored for drift, bias, and accuracy, and stress-tested against curated benchmarks for sanctions, PEPs, and adverse media
Evaluation & Benchmarking
Models are continuously monitored for drift, bias, and accuracy, and stress-tested against curated benchmarks for sanctions, PEPs, and adverse media
Governance & Accountability
Independent validators review every model before release, under the oversight of an AI Governance Board aligned with ISO 42001 and PRA SS1/23
Governance & Accountability
Independent validators review every model before release, under the oversight of an AI Governance Board aligned with ISO 42001 and PRA SS1/23
Fairness & Bias Mitigation
Structured testing before and after deployment ensures decisions remain equitable across demographic and geographic groups
Fairness & Bias Mitigation
Structured testing before and after deployment ensures decisions remain equitable across demographic and geographic groups
Human-in-the-Loop Safety
Uncertain cases are always flagged for manual review, with analyst overrides logged and fed back into model retraining
Human-in-the-Loop Safety
Uncertain cases are always flagged for manual review, with analyst overrides logged and fed back into model retraining
Post-training & Alignment Controls
Calibration methods where ambiguous cases are surfaced as “AI Recommended Verdicts” instead of automated actions.
Post-training & Alignment Controls
Calibration methods where ambiguous cases are surfaced as “AI Recommended Verdicts” instead of automated actions.
Uncertainty & Drift Detection
Bayesian-style thresholds and rare-event testing for detecting emerging laundering typologies
Uncertainty & Drift Detection
Bayesian-style thresholds and rare-event testing for detecting emerging laundering typologies
Systemic Risk & Security
We mitigate systemic risks through multi-source validation and protect data with GDPR-compliant privacy, retention, and encryption practices
Systemic Risk & Security
We mitigate systemic risks through multi-source validation and protect data with GDPR-compliant privacy, retention, and encryption practices
"At Arva, we don’t just build AI for compliance — we conduct deep research into how AI models behave, adapt, and align in high-stakes financial crime contexts. We see research not as a side effort, but as the foundation of trust in AI for the world’s most sensitive domains."
— Oli Wales, CTO at Arva AI
"At Arva, we don’t just build AI for compliance — we conduct deep research into how AI models behave, adapt, and align in high-stakes financial crime contexts. We see research not as a side effort, but as the foundation of trust in AI for the world’s most sensitive domains."
— Oli Wales, CTO at Arva AI
"At Arva, we don’t just build AI for compliance — we conduct deep research into how AI models behave, adapt, and align in high-stakes financial crime contexts. We see research not as a side effort, but as the foundation of trust in AI for the world’s most sensitive domains."
— Oli Wales, CTO at Arva AI
Our research goals
Arva combines hybrid AI models with external certification, delivers a 91% reduction in false positives, adapts through real-time drift detection and retraining, and ensures full auditability with every override, rationale, and action logged.
Our research goals
Arva combines hybrid AI models with external certification, delivers a 91% reduction in false positives, adapts through real-time drift detection and retraining, and ensures full auditability with every override, rationale, and action logged.
AI Research Aims
Prevent misaligned actions
Arva ensures no AI-driven compliance decision bypasses oversight in ways that could aid financial crime.
Design for safety-first AI
Our conservative philosophy and governance-first lifecycle mean agents never “attempt” unsafe behaviour — they default to human review.
Advance the science of AI governance
Arva operationalizes international standards into practical safeguards for financial institutions.
AI Research Aims
Prevent misaligned actions
Arva ensures no AI-driven compliance decision bypasses oversight in ways that could aid financial crime.
Design for safety-first AI
Our conservative philosophy and governance-first lifecycle mean agents never “attempt” unsafe behaviour — they default to human review.
Advance the science of AI governance
Arva operationalizes international standards into practical safeguards for financial institutions.
Deep research & AI models
Deep research & AI models
Hybrid Model Architecture
Proprietary agents combined with foundation models and deterministic rules create both domain-specific accuracy and general adaptability.
Hybrid Model Architecture
Proprietary agents combined with foundation models and deterministic rules create both domain-specific accuracy and general adaptability.
Learning Dynamics
We study how model training, feedback loops, and inductive biases affect generalisation in sanctions and adverse media tasks.
Learning Dynamics
We study how model training, feedback loops, and inductive biases affect generalisation in sanctions and adverse media tasks.
Behavioural Controls
Our calibration research ensures that models do not “attempt” unsafe actions. Ambiguous results are flagged for manual review.
Behavioural Controls
Our calibration research ensures that models do not “attempt” unsafe actions. Ambiguous results are flagged for manual review.
Interpretability Research
By probing internal mechanisms, rationales, and confidence thresholds, Arva advances methods to detect bias, misclassification, or potential deception.
Interpretability Research
By probing internal mechanisms, rationales, and confidence thresholds, Arva advances methods to detect bias, misclassification, or potential deception.
Benchmark Science
We design and maintain representative datasets and adversarial test cases for AML/fincrime.
Benchmark Science
We design and maintain representative datasets and adversarial test cases for AML/fincrime.
Deep Research
Arva’s research agenda goes beyond product engineering — we run deep investigations into how AI models behave, adapt, and align in financial crime contexts:
Deep Research
Arva’s research agenda goes beyond product engineering — we run deep investigations into how AI models behave, adapt, and align in financial crime contexts:
Leaders in AI model risk governance
Leaders in AI model risk governance
Every AI agent is developed, validated, and monitored under our AI Model Risk Governance framework
Transparent Model Governance Framework
Clear and certified documentation ensuring regulators and customers understand AI decisioning
Independent Validation & Benchmarking
External testing and auditing against industry standards highlight strengths, expose weaknesses, and drives trust
Continuous Monitoring & Drift Detection
Ongoing evaluation pipelines catch performance degradation early, ensuring models remain robust
Human-in-the-Loop Learning
HIL input with reinforcement learning, ensuring trust is built before automation
Transparent Model Governance Framework
Clear and certified documentation ensuring regulators and customers understand AI decisioning
Independent Validation & Benchmarking
External testing and auditing against industry standards highlight strengths, expose weaknesses, and drives trust
Continuous Monitoring & Drift Detection
Ongoing evaluation pipelines catch performance degradation early, ensuring models remain robust
Human-in-the-Loop Learning
HIL input with reinforcement learning, ensuring trust is built before automation
Transparent Model Governance Framework
Clear documentation ensures regulators, customers, and stakeholders understand how AI decisions are made.
Continuous Monitoring & Drift Detection
Ongoing evaluation pipelines catch performance degradation early, ensuring models remain reliable in dynamic real-world environments.
Human-in-the-Loop Risk Controls
Expert oversight and layered validation safeguard against errors, blending machine efficiency with human judgment.
Independent Validation & Benchmarking
External-grade testing and comparison against industry standards highlight strengths, expose weaknesses, and drive trust.
Automate 92% of your financial crime reviews with Arva AI
Power your AML financial crime compliance with an enterprise AI workforce
Automate 92% of your financial crime reviews with Arva AI
Power your AML financial crime compliance with an enterprise AI workforce
Automate 92% of your financial crime reviews with Arva AI
Power your AML financial crime compliance with an enterprise AI workforce
Arva AI is a platform to build, deploy, & monitor your AI workforce, automating 92% of all financial crime reviews
Product
Arva AI is a platform to build, deploy, & monitor your AI workforce, automating 92% of all financial crime reviews
Product
Arva AI is a platform to build, deploy, & monitor your AI workforce, automating 92% of all financial crime reviews
Product