By Sukanya Ganesh in AI — Nov 20, 2024

AI in Regulatory Technology

RegTech uses AI, machine learning, and blockchain to simplify compliance, risk management, and reporting, helping businesses, especially in finance, adapt to evolving regulations efficiently.

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AI-powered regulatory technology (RegTech) has gained momentum across the financial sector, with prominent institutions and innovative startups implementing these technologies to meet stringent regulatory requirements.

Automated Compliance Monitoring and Fraud Detection

JPMorgan uses an AI tool called COiN (Contract Intelligence) to automate document review and compliance checks. COiN quickly scans and analyzes commercial loan agreements and other complex documents that would take employees hours to process manually. This enables the bank to identify compliance issues and mitigate risks more efficiently.
Darktrace known for its AI-driven cybersecurity solutions, it uses machine learning to detect anomalies and potential fraud in real-time by analyzing massive amounts of transactional and network data. Its technology is widely used by banks and financial institutions for both fraud prevention and regulatory compliance by detecting unusual behavior patterns in financial transactions.

Anti-Money Laundering (AML) and Know Your Customer (KYC)

HSBC has adopted AI to improve its AML and KYC processes, partnering with Google Cloud to develop machine learning models for AML. This AI system has improved HSBC’s ability to detect and report suspicious activities, reducing false positives and enabling more accurate reporting to regulators.
Onfido is a UK-based company specializing in AI-driven identity verification for KYC processes. Onfido uses AI to scan and verify customer documents, such as passports and IDs, to prevent identity fraud. The company’s technology is widely used in the financial industry to streamline onboarding while ensuring compliance with strict KYC regulations.

Enhanced Risk Management and Predictive Analytics

ING Bank leverages AI for predictive analytics in risk management. By analyzing past data on loan defaults and other credit risks, the bank’s AI models can predict future risks, helping the bank take proactive steps to mitigate them. This risk prediction capability helps ING comply with Basel III and other international banking regulations requiring risk transparency and management.
Feedzai is a RegTech company that provides AI-driven risk management platforms to banks and payment processors. Their platform detects suspicious transactions and behaviors, helping clients manage fraud and compliance risk in real time. Major banks, including Citibank and Lloyds Bank, use Feedzai for proactive fraud detection and regulatory risk management.

Audit and Transparency with Explainable AI

IBM Watson offers explainable AI solutions that enable financial institutions to generate compliance reports that regulators can easily audit. For example, IBM’s AI solutions for financial services include compliance-focused analytics that allow banks to trace and justify decisions in credit scoring and risk assessments, which are essential for compliance with Basel III regulations.
FICO known for its credit scoring, also provides explainable AI models for regulatory compliance in credit risk. Its AI tools help lenders provide transparent credit risk assessments to regulators and customers, ensuring that their credit decisions comply with transparency standards, particularly in the European Union under the GDPR.

These examples demonstrate how AI-powered RegTech solutions are actively helping financial institutions meet complex regulatory requirements while increasing operational efficiency, enhancing security, and reducing compliance costs. As AI technology continues to evolve, more companies are expected to adopt these RegTech solutions to stay competitive in an increasingly regulated landscape.