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Risk Management for AI Chatbots

O'Reilly on Data

Welcome to your company’s new AI risk management nightmare. Before you give up on your dreams of releasing an AI chatbot, remember: no risk, no reward. The core idea of risk management is that you don’t win by saying “no” to everything. Why not take the extra time to test for problems?

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CrowdStrike incident has CIOs rethinking their cloud strategies

CIO Business Intelligence

This has forced CIOs to question the resilience of their cloud environments and explore alternative strategies. The outcome of the review may still be the same decision but necessary to review,” Gupta said, adding that DishTV is already re-evaluating its cloud strategy in a phased manner after the Crowdstrike incident.

Strategy 143
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Is your disaster recovery a house of cards? Why BIA, BCP, and DRP are your foundation

CIO Business Intelligence

In fact, successful recovery from cyberattacks and other disasters hinges on an approach that integrates business impact assessments (BIA), business continuity planning (BCP), and disaster recovery planning (DRP) including rigorous testing. See also: How resilient CIOs future-proof to mitigate risks.)

Testing 64
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Why you should care about debugging machine learning models

O'Reilly on Data

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. While our analysis of each method may appear technical, we believe that understanding the tools available, and how to use them, is critical for all risk management teams.

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PODCAST: Making AI Real – Episode 2: AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower

bridgei2i

Episode 2: AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. Today the Chief Risk Officers(CROs) struggle with the critical task of monitoring and assessing key risks in real time and firefight to mitigate any critical issues that arise.

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How Big Data Impacts The Finance And Banking Industries

Smart Data Collective

Financial institutions such as banks have to adhere to such a practice, especially when laying the foundation for back-test trading strategies. There is significant competition in the industry, and emerging tactics and strategies must be accepted to survive the market competition. The Role of Big Data. Engaging the Workforce.

Big Data 145
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Managing machine learning in the enterprise: Lessons from banking and health care

O'Reilly on Data

A look at how guidelines from regulated industries can help shape your ML strategy. In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring.