Risk Management Association of India
Global body dedicated to education, research and development on Risk Management
Artificial intelligence is creating value across KYC, sanctions screening, transaction monitoring, fraud detection and credit risk, but Deutsche Bank says speed of adoption must not come at the expense of testing and human oversight. Tsvetanka Nankova of Deutsche Bank describes Read More …
The NIST Artificial Intelligence Risk Management Framework (AI RMF) 1.0 provides organisations with a structured, voluntary approach to identifying, assessing and managing risks associated with artificial intelligence throughout its lifecycle. The framework is designed to help organisations incorporate trustworthiness considerations Read More …
Artificial intelligence is moving from experimental projects into customer-facing applications, underwriting, fraud detection and decision-making workflows, making AI risk an enterprise-level responsibility rather than a technology-only concern, according to an analysis published by Fortune India. The shift is particularly important Read More …
Corporate boards need to understand how artificial intelligence is changing their organisation’s overall risk profile, rather than receiving a technical list of potential AI threats, according to a recent analysis published by TechTarget. The analysis argues that AI does not Read More …
The UK Department for Science, Innovation and Technology (DSIT) has published an AI Risk Management Toolkit to help public-sector organisations identify, assess and manage risks associated with the design, procurement, deployment and use of artificial intelligence. The guidance was published Read More …
Artificial intelligence is becoming one of the most significant areas of uncertainty for insurers, creating opportunities for innovation while introducing new risks around governance, decision-making and operational control. Insurance leaders are highlighting that AI has the potential to transform areas Read More …
The country where an artificial intelligence (AI) model is developed provides limited insight into its actual risk profile, according to analysis highlighting the need for stronger AI governance, transparency and model evaluation frameworks. As organisations increasingly adopt AI systems, assessing Read More …
Banks and financial institutions increasingly rely on AI solutions from third-party vendors and FinTech partners. These collaborations enhance innovation and operational efficiency but also introduce operational, compliance, and reputational risks. Mismanaged AI systems can lead to failures, regulatory breaches, and Read More …
Financial regulators are undertaking a significant overhaul of model risk management (MRM) frameworks, reflecting the growing reliance on complex models and artificial intelligence (AI) in decision-making processes. According to the report, the updated regulatory focus aims to strengthen governance, validation, Read More …
The Monetary Authority of Singapore (MAS) is collaborating with industry stakeholders to develop a comprehensive artificial intelligence (AI) risk management toolkit for the financial sector, reflecting growing global focus on governing AI adoption in finance. The initiative aims to provide Read More …