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7 risk management rules every CIO should follow

CIO Business Intelligence

A PwC Global Risk Survey found that 75% of risk leaders claim that financial pressures limit their ability to invest in the advanced technology needed to assess and monitor risks. Yet failing to successfully address risk with an effective risk management program is courting disaster.

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Risk Management for AI Chatbots

O'Reilly on Data

Doing so means giving the general public a freeform text box for interacting with your AI model. Welcome to your company’s new AI risk management nightmare. ” ) With a chatbot, the web form passes an end-user’s freeform text input—a “prompt,” or a request to act—to a generative AI model.

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Why you should care about debugging machine learning models

O'Reilly on Data

Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]

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Where CIOs should place their 2025 AI bets

CIO Business Intelligence

As gen AI heads to Gartners trough of disillusionment , CIOs should consider how to realign their 2025 strategies and roadmaps. Even simple use cases had exceptions requiring business process outsourcing (BPO) or internal data processing teams to manage.

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Successful Change Management with Enterprise Risk Management

Speaker: William Hord, Vice President of ERM Services

Leveraging the data that your ERM program already contains is an effective way to help create and manage the overall change management process within your organization. It is the tangents of this data that are vital to a successful change management process. Organize ERM strategy, operations, and data.

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New regulation intensifies focus on IT risk management and operational resilience

CIO Business Intelligence

A comprehensive regulatory reach DORA addresses a broad range of ICT risks, including incident response, resilience testing, third-party risk management, and information sharing. One notable tool, BMC HelixGPT , uses a large language model (LLM) that drives a suite of AI-powered software agents.

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The trinity of errors in financial models: An introductory analysis using TensorFlow Probability

O'Reilly on Data

An exploration of three types of errors inherent in all financial models. At Hedged Capital , an AI-first financial trading and advisory firm, we use probabilistic models to trade the financial markets. All financial models are wrong. Clearly, a map will not be able to capture the richness of the terrain it models.

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