article thumbnail

Managing risk in machine learning

O'Reilly on Data

As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. We recently conducted a survey which garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning. Let’s begin by looking at the state of adoption.

article thumbnail

Why you should care about debugging machine learning models

O'Reilly on Data

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. Currency amounts reported in Taiwan dollars. Sensitivity analysis.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

How to Leverage Machine Learning for AML Compliance

BizAcuity

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. AML regulations and procedures help organizations identify, monitor, and report suspicious transactions and provide an additional layer of protection against financial crime.

article thumbnail

What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

article thumbnail

How to Leverage Machine Learning for AML Compliance

BizAcuity

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. AML regulations and procedures help organizations identify, monitor, and report suspicious transactions and provide an additional layer of protection against financial crime.

article thumbnail

10 projects top of mind for IT leaders today

CIO Business Intelligence

Artificial intelligence and machine learning Unsurprisingly, AI and machine learning top the list of initiatives CIOs expect their involvement to increase in the coming year, with 80% of respondents to the State of the CIO survey saying so. Risk management came in at No. Other surveys offer similar findings.

IT 137
article thumbnail

3 key digital transformation priorities for 2024

CIO Business Intelligence

The analyst reports tell CIOs that generative AI should occupy the top slot on their digital transformation priorities in the coming year. Moreover, the CEOs and boards that CIOs report to don’t want to be left behind by generative AI, and many employees want to experiment with the latest generative AI capabilities in their workflows.