Manage AI Regulation
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Regulativ AI Compliance Automation Platform

The EU AI Act is the world's first comprehensive legal framework regulating artificial intelligence, taking effect in 2024 with full compliance required by 2026. It uses a risk-based approach classifying AI systems into four categories: unacceptable risk (banned), high-risk (strict requirements), limited risk (transparency obligations), and minimal risk (unregulated). Financial services AI for credit scoring, fraud detection, and risk assessment are classified as high-risk. Regulativ helps financial institutions achieve EU AI Act compliance through automated risk assessments, governance frameworks, bias detection, explainability tools, and continuous monitoring—ensuring AI systems meet all regulatory requirements.

High-risk AI systems are those used in critical applications affecting safety or fundamental rights. In financial services, this includes credit scoring and loan approval, fraud detection and AML systems, risk assessment and underwriting, insurance pricing and claims processing, customer profiling and segmentation, and algorithmic trading systems. High-risk AI requires conformity assessments, CE marking, human oversight, bias testing, explainability, technical documentation, and post-market monitoring. Regulativ automates high-risk AI compliance by conducting gap assessments, implementing required controls, maintaining audit trails, and providing continuous monitoring to ensure ongoing compliance with EU AI Act requirements.

An AI governance framework is a set of policies, processes, and controls ensuring AI systems are developed, deployed, and monitored responsibly. Core components include: AI system inventory and classification, model risk management processes, bias detection and mitigation controls, explainability and transparency requirements, human oversight mechanisms, data governance and quality standards, security and privacy controls, and continuous monitoring and auditing. Regulativ provides comprehensive AI governance frameworks for financial institutions covering all EU AI Act, GDPR, DORA, and sector-specific requirements—with automated policy generation, risk assessments, and compliance monitoring reducing governance overhead by 80%.

AI compliance requirements for financial services include: EU AI Act high-risk system requirements (conformity assessments, documentation, transparency), model risk management per SR 11-7 guidance (US), GDPR data protection and privacy requirements, bias testing and fair lending compliance, explainability for automated decisions, human oversight and intervention capabilities, cybersecurity and DORA resilience requirements, continuous monitoring and validation, and incident reporting procedures. Penalties for non-compliance range from €7.5-35 million or 1-7% of global turnover under EU AI Act. Regulativ automates AI compliance across all frameworks, reducing compliance costs and ensuring continuous regulatory alignment.

EU AI Act penalties are severe and tiered by violation type. Prohibited AI practices result in fines up to €35 million or 7% of global annual turnover (whichever is higher). High-risk AI non-compliance results in fines up to €15 million or 3% of global turnover. Incorrect information to authorities results in fines up to €7.5 million or 1% of global turnover. Beyond fines, consequences include market access restrictions, reputational damage, loss of customer trust, and potential litigation. For SMEs, penalties are capped but still substantial. Regulativ helps avoid these penalties through automated compliance monitoring, early violation detection, and comprehensive audit trails demonstrating ongoing compliance.

AI explainability (or interpretability) is the ability to understand and articulate how an AI system makes decisions. Regulators require explainability because financial services AI affects critical decisions like credit approvals, fraud flags, and risk assessments. Under EU AI Act and GDPR Article 22, individuals have the right to explanation for automated decisions. Explainability requirements include: documenting model logic and decision factors, providing human-readable explanations, identifying which data influenced decisions, and enabling challenge and appeal processes. Regulativ provides AI explainability tools that automatically generate audit-ready explanations, document decision factors, detect unexplainable black-box risks, and ensure all AI systems meet transparency requirements.

AI bias detection involves testing whether AI systems produce discriminatory outcomes based on protected characteristics (race, gender, age, etc.). Detection methods include: disparate impact analysis comparing outcomes across demographic groups, fairness metric evaluation (equal opportunity, demographic parity), validation dataset testing with diverse populations, continuous monitoring for bias drift, and adverse action analysis reviewing rejected applications. EU AI Act requires regular bias testing for high-risk systems. Regulativ automates bias detection through continuous monitoring across all AI models, demographic disparity analysis, automated fairness testing, bias alert generation, and remediation tracking—ensuring AI systems remain fair and compliant throughout their lifecycle.

Yes, Regulativ provides comprehensive EU AI Act compliance solutions for financial institutions. Our platform automates high-risk AI system classification and inventory, conducts mandatory risk assessments and gap analysis, implements required governance frameworks and controls, performs bias testing and fairness evaluations, generates technical documentation and conformity evidence, enables human oversight and intervention workflows, monitors AI systems continuously for drift and violations, and maintains audit trails for regulatory examinations. Regulativ helps financial institutions achieve EU AI Act compliance within 8-12 weeks versus 6-12 months for manual approaches—reducing compliance costs by 80% while ensuring continuous regulatory alignment.

The EU AI Act implementation timeline has phased deadlines. February 2, 2025: Prohibited AI systems ban takes effect. August 2, 2025: General purpose AI (GPAI) obligations begin. August 2, 2026: High-risk AI system requirements fully applicable (24 months after entry into force). August 2, 2027: Obligations for AI systems in regulated products. Financial institutions using high-risk AI must achieve compliance by August 2026. This requires risk assessments, governance implementation, bias testing, documentation, and monitoring systems. Regulativ accelerates EU AI Act implementation to 8-12 weeks through automated assessments, pre-built frameworks, and continuous compliance monitoring.

AI model risk management is the framework for identifying, assessing, and mitigating risks from AI and machine learning models. Under Federal Reserve SR 11-7 guidance and EU AI Act, it includes: model development and validation, performance monitoring and testing, bias and fairness assessments, explainability and documentation, change management and version control, independent model validation, and governance oversight. Key risks include model drift (performance degradation), data quality issues, algorithmic bias, security vulnerabilities, and regulatory non-compliance. Regulativ automates AI model risk management through continuous validation, automated testing, drift detection, compliance monitoring, and comprehensive audit trails—reducing model risk while accelerating AI deployment.

GDPR applies to AI systems processing personal data with specific requirements: Article 22 right to not be subject to purely automated decision-making without human review, lawful basis for processing (consent, legitimate interest, contract), data minimization and purpose limitation, right to explanation for automated decisions, data protection impact assessments (DPIAs) for high-risk processing, security measures protecting training and inference data, and rights to access, correction, and deletion. AI systems must implement privacy by design, maintain processing records, and enable individual rights. Regulativ ensures GDPR-compliant AI through automated DPIAs, consent management, data governance controls, access controls, and audit trails documenting lawful processing.

AI governance best practices include: establishing board-level AI oversight with clear accountability, creating cross-functional governance teams (legal, compliance, risk, IT), implementing comprehensive AI inventory and classification systems, conducting regular risk assessments and audits, maintaining detailed documentation for all AI systems, implementing human-in-the-loop oversight for high-risk decisions, continuous bias and fairness monitoring, establishing clear AI development and deployment standards, vendor due diligence for third-party AI, and incident response procedures. Organizations with mature governance frameworks experience 40% fewer AI incidents and 31% faster deployment. Regulativ provides turnkey AI governance frameworks automating documentation, monitoring, and compliance—enabling responsible AI at scale.

EU AI Act and GDPR are complementary but different. GDPR regulates personal data processing (collection, storage, use) focusing on privacy, consent, and individual rights. EU AI Act regulates AI systems themselves (development, deployment, operation) focusing on safety, fairness, and transparency. Key differences: GDPR applies to any personal data processing; AI Act applies only to AI systems. GDPR focuses on data protection rights; AI Act focuses on AI-specific risks. GDPR penalties up to €20 million or 4% of turnover; AI Act penalties up to €35 million or 7% of turnover. Both apply simultaneously—AI systems processing personal data must comply with both regulations. Regulativ provides unified compliance across GDPR, EU AI Act, and all other regulations.

Regulativ automates AI bias testing through continuous monitoring across all demographic groups, disparate impact analysis measuring outcome differences, fairness metric calculation (equal opportunity, demographic parity, equalized odds), statistical significance testing, intersectional bias detection (multiple protected characteristics), validation dataset testing with diverse populations, adverse action pattern analysis, and automated alerting when bias thresholds exceeded. Our platform tests against protected characteristics (race, gender, age, disability, etc.), generates audit-ready bias reports, tracks remediation efforts, and ensures ongoing fairness monitoring. Regulativ reduces bias testing time from weeks to hours while providing continuous compliance with EU AI Act fairness requirements.

AI regulatory sandboxes are controlled testing environments where organizations can develop and test AI systems under regulatory supervision with reduced compliance burdens. Under EU AI Act Article 57, each member state must establish AI sandboxes by August 2026. Benefits include: testing innovative AI in realistic conditions, receiving regulatory guidance during development, reduced compliance requirements during testing, faster time to market for compliant AI, and building relationships with regulators. Sandboxes are particularly valuable for SMEs and startups. Eligibility typically requires innovative AI systems, clear testing plans, and commitment to compliance post-testing. Regulativ helps organizations prepare sandbox applications and maintain compliance throughout testing phases.

Third-party AI vendor risk management requires: due diligence before procurement (compliance documentation, security assessments, bias testing results), contractual protections (indemnification, audit rights, data governance), ongoing monitoring of vendor AI performance and compliance, independent validation of vendor AI outputs, incident notification and response procedures, exit strategies and data portability, and regulatory responsibility awareness (liability remains with deployer even when using vendor AI). EU AI Act explicitly addresses this—deployers cannot delegate compliance responsibility. Regulativ provides third-party AI risk management through automated vendor assessments, continuous monitoring of external AI systems, compliance verification, and audit trail maintenance—ensuring vendor AI meets all regulatory requirements.

AI compliance costs vary significantly by organization size and AI system complexity. Typical costs include: initial compliance assessment and gap analysis (€50,000-200,000), governance framework implementation (€100,000-500,000), annual compliance per high-risk AI system (€30,000-100,000), bias testing and validation (€25,000-75,000 per system), technical documentation and audits (€40,000-150,000), and ongoing monitoring and reporting (€50,000-200,000 annually). However, non-compliance costs more: EU AI Act fines up to €35 million or 7% of global turnover, plus reputational damage and market access restrictions. Regulativ reduces AI compliance costs by 80% through automation—achieving compliance within 8-12 weeks at a fraction of traditional consulting costs.

AI conformity assessment is the process proving high-risk AI systems meet EU AI Act requirements before market deployment. It includes: comprehensive technical documentation review, quality management system evaluation, risk management process assessment, data governance verification, bias and fairness testing, security and robustness evaluation, human oversight implementation review, and transparency and explainability validation. Providers must obtain CE marking demonstrating conformity. Assessment can be internal (self-assessment) or require notified body involvement depending on AI type. Non-compliant systems cannot be deployed in EU markets. Regulativ automates conformity assessment preparation by generating required documentation, conducting pre-assessment audits, identifying compliance gaps, and maintaining continuous conformity evidence.

Regulativ achieves AI compliance implementation within 8-12 weeks versus 6-12 months for traditional approaches. Our accelerated timeline includes: Week 1-2: AI system inventory and risk classification across your organization. Week 3-4: Automated gap assessment against EU AI Act, GDPR, and sector regulations. Week 5-6: Governance framework deployment and policy generation. Week 7-8: Bias testing, explainability implementation, and documentation generation. Week 9-10: Monitoring system configuration and integration. Week 11-12: Final validation, conformity preparation, and team training. Full implementation covers all high-risk AI systems, provides continuous monitoring, generates audit-ready documentation, and ensures ongoing compliance—helping financial institutions meet the August 2026 EU AI Act deadline with time to spare.

AI training data governance requirements under EU AI Act include: data quality standards (relevant, representative, complete, error-free), bias mitigation in training datasets (demographic diversity, balanced representation), data provenance and lineage documentation, privacy and security controls (GDPR compliance, anonymization), data minimization principles, consent and lawful basis for data use, validation dataset quality, and ongoing data monitoring for drift. Poor training data is a primary source of AI bias and errors. Financial institutions must document data sources, preprocessing steps, quality checks, and bias assessments. Regulativ automates training data governance through automated quality checks, bias detection in datasets, provenance tracking, compliance verification, and audit trail maintenance for all AI training data.