DataRobot Blog

APRIL 29, 2022

This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks.

Risk 111

Risk Modeling IT Risk Management 111

Domino Data Lab

AUGUST 6, 2021

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.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

DataRobot Blog

MAY 26, 2022

In this post, we will dive deeper into how members from both the first and second line of defense within a financial institution can adapt their model validation strategies in the context of modern ML methods. The decreasing default risk with increasing salary suggests that higher income applicants pose less credit risk to the bank.

Risk 52

Risk Modeling Metrics Business Objectives 52

CIO Business Intelligence

DECEMBER 15, 2022

To illustrate, from 2011 to 2021, IVL collected over 72 billion post-consumer PET bottles for recycling, which prevented 1.6 Additionally, striving for continuous improvement, we were looking for a solution to take our existing mechanical integrity program and strategies and integrate them with our maintenance and business processes.”

Risk 98

Risk Digital Transformation Software ROI 98

Domino Data Lab

APRIL 3, 2019

Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for Given those two, plus SQL gaining eminence as a database strategy, a decidedly relational picture coalesced throughout the decade. Andrew Ng later described this strategy as the “Virtuous Cycle of AI” – a.k.a.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

datapine

AUGUST 29, 2022

He founded the project Apache Storm in 2011, which turned to be “one of the world’s most popular stream processors and has been adopted by many of the world’s largest companies, including Yahoo!, Microsoft, Alibaba, Taobao, WebMD, Spotify, Yelp” according to Marz himself. It was lately revised and updated in January 2016.

Big Data 263

Big Data Data Analytics Analytics Data mining 263