Smart Data Collective

MARCH 27, 2020

Here is the type of data insurance companies use to measure a client’s potential risk and determine rates. Traditional data, like demographics, continues to be a factor in risk assessment. Teens and young adults are less experienced drivers and, therefore, at risk for more car accidents. Demographics. This includes: Age.

Insurance 108

Insurance Measurement Risk Cost-Benefit 108

CIO Business Intelligence

OCTOBER 9, 2024

However, this enthusiasm may be tempered by a host of challenges and risks stemming from scaling GenAI. Depending on your needs, large language models (LLMs) may not be necessary for your operations, since they are trained on massive amounts of text and are largely for general use.

Strategy 142

Strategy Modeling Management Data Lake 142

Cloudera

OCTOBER 20, 2021

As part of these efforts, disclosure requirements will mandate that firms provide “the impact of a company’s activities on the environment and society, as well as the business and financial risks faced by a company due to its sustainability exposures.” What are the key climate risk measurements and impacts? Generate Scenarios.

Risk 79

Risk Modeling Risk Management Measurement 79

O'Reilly on Data

OCTOBER 30, 2023

While I am heartened to hear that the Executive Order on AI uses the Defense Production Act to compel disclosure of various data from the development of large AI models, these disclosures do not go far enough. These include: What data sources the model is trained on. Operational Metrics. Policy on use of user data for further training.

Measurement 304

Measurement Risk Metrics Modeling 304

DataRobot Blog

MAY 26, 2022

Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. In summary, to ensure that they have built a robust model, modelers must make certain that they have designed the model in a way that is backed by research and industry-adopted practices.

Risk 52

Risk Modeling Metrics Business Objectives 52

CIO Business Intelligence

JANUARY 3, 2024

According to an O’Reilly survey released late last month, 23% of companies are using one of OpenAI’s models. Other respondents said they aren’t using any generative AI models, are building their own, or are using an open-source alternative. And it’s not just start-ups that can expose an enterprise to AI-related third-party risk.

Risk 131

Risk Modeling Enterprise Marketing 131

DataRobot Blog

NOVEMBER 17, 2022

What’s your AI risk mitigation plan? Just as you wouldn’t set off on a journey without checking the roads, knowing your route, and preparing for possible delays or mishaps, you need a model risk management plan in place for your machine learning projects. Is it possible to have an unbiased AI model? The hard truth is no.

Risk Management 52

Risk Management Risk Modeling Management 52

Anmut

MARCH 22, 2023

Data maturity models are a crucial step for any organisation looking to improve their data, informing if your current data practices are helping, or holding back, your business. ? Click the links below to navigate to different sections What are data maturity models? Why do we need data maturity models? It’s like driving a car.

Measurement 52

Measurement Modeling Data Quality Data Governance 52

datapine

MAY 31, 2022

More and more CRM, marketing, and finance-related tools use SaaS business intelligence and technology, and even Adobe’s Creative Suite has adopted the model. This increases the risks that can arise during the implementation or management process. The next part of our cloud computing risks list involves costs.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

Analytics Vidhya

JANUARY 15, 2024

In a startling revelation, researchers at Anthropic have uncovered a disconcerting aspect of Large Language Models (LLMs) – their capacity to behave deceptively in specific situations, eluding conventional safety measures.

Measurement 288

Measurement Risk Modeling Analytics 288

IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 70

Risk Modeling Management Metadata 70

O'Reilly on Data

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. Before I continue, it’s important to emphasize that machine learning is much more than building models. Model lifecycle management.

Machine Learning 225

Machine Learning Risk Management Statistics 225

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

DataRobot Blog

JULY 22, 2022

Using AI-based models increases your organization’s revenue, improves operational efficiency, and enhances client relationships. You need to know where your deployed models are, what they do, the data they use, the results they produce, and who relies upon their results. That requires a good model governance framework.

Modeling 105

Modeling Risk Management Testing Risk 105

O'Reilly on Data

JUNE 19, 2019

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. We are also beginning to see researchers share sample code written in popular open source libraries, and some even share pre-trained models. Model development. Model governance. Source: Ben Lorica.

Modeling 195

Modeling Machine Learning Testing Metrics 195

CIO Business Intelligence

DECEMBER 28, 2023

The need to manage risk, adhere to regulations, and establish processes to govern those tasks has been part of running an organization as long as there have been businesses to run. Furthermore, the State of Risk & Compliance Report, from GRC software maker NAVEX, found that 20% described their programs as early stage. What is GRC?

Risk 115

Risk Risk Management Strategy Enterprise 115

IBM Big Data Hub

MAY 8, 2023

This blog continues the discussion, now investigating the risks of adopting AI and proposes measures for a safe and judicious response to adopting AI. Risk and limitations of AI The risk associated with the adoption of AI in insurance can be separated broadly into two categories—technological and usage.

Insurance 68

Insurance Risk Testing Data Quality 68

David Menninger's Analyst Perspectives

OCTOBER 9, 2024

It helps build trust in the results of AI models, it helps ensure compliance with regulations and it is necessary to meet internal governance requirements. Effective AI governance must encompass various dimensions, including data privacy, model drift, hallucinations, toxicity and perhaps most importantly, bias.

Metrics 130

Metrics Measurement Machine Learning Modeling 130

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

CIO Business Intelligence

MARCH 25, 2024

Modern digital organisations tend to use an agile approach to delivery, with cross-functional teams, product-based operating models , and persistent funding. But to deliver transformative initiatives, CIOs need to embrace the agile, product-based approach, and that means convincing the CFO to switch to a persistent funding model.

Modeling 124

Modeling Cost-Benefit IT ROI 124

CIO Business Intelligence

OCTOBER 24, 2023

Cloud applications, in essence, have become organizations’ crown jewels and developers are measured on how quickly they can build and deploy them. In light of this, developer teams are beginning to turn to AI-enabled tools like large language models (LLMs) to simplify and automate tasks.

Modeling 119

Modeling Risk Reporting Machine Learning 119

O'Reilly on Data

DECEMBER 12, 2019

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]

Machine Learning 197

Machine Learning Modeling Testing Risk Management 197

CIO Business Intelligence

SEPTEMBER 10, 2024

The US Department of Commerce’s Bureau of Industry and Security (BIS) plans to introduce mandatory reporting requirements for developers of advanced AI models and cloud computing providers.

Reporting 131

Reporting Measurement Testing Risk 131

IBM Big Data Hub

SEPTEMBER 7, 2023

Today we are announcing our latest addition: a new family of IBM-built foundation models which will be available in watsonx.ai , our studio for generative AI, foundation models and machine learning. Collectively named “Granite,” these multi-size foundation models apply generative AI to both language and code.

Modeling 101

Modeling Risk Unstructured Data Enterprise 101

CIO Business Intelligence

NOVEMBER 19, 2024

Generative AI (GenAI) is rapidly emerging as a game changer for enterprises, but turning its potential into measurable value remains a significant challenge. Data privacy and compliance issues Failing: Mismanagement of internal data with external models can lead to privacy breaches and non-compliance with regulations.

Consulting 126

Consulting Cost-Benefit Experimentation Optimization 126

CIO Business Intelligence

OCTOBER 24, 2024

Take for instance large language models (LLMs) for GenAI. From prompt injections to poisoning training data, these critical vulnerabilities are ripe for exploitation, potentially leading to increased security risks for businesses deploying GenAI. This puts businesses at greater risk for data breaches.

Risk 128

Risk Measurement Optimization Machine Learning 128

Smart Data Collective

FEBRUARY 14, 2023

However, it is important to understand the benefits and risks associated with cloud computing before making the commitment. However, there are some risks associated with using cloud-based software for business purposes. Firstly, there is always the risk of data breaches due to cyber-attacks or human error.

Risk 103

Risk Cost-Benefit Software Technology 103

CIO Business Intelligence

OCTOBER 24, 2024

AI projects without clear goals or measurable outcomes are unlikely to deliver real value. The long-term impact is even more worrying — companies risk falling behind competitors who are implementing AI strategically. Some AI projects may get dumped , but the big risk for many organizations is not adopting AI, he says.

IT 138

IT Experimentation Measurement Risk 138

Alation

JANUARY 9, 2023

Alation joined with Ortecha , a data management consultancy, to publish a white paper providing insights and guidance to stakeholders and decision-makers charged with implementing or modernising data risk management functions. The Increasing Focus On Data Risk Management. Download the complete white paper now.

Risk Management 52

Risk Management Risk Management Metadata 52

CIO Business Intelligence

AUGUST 9, 2024

In cases where privacy is essential, we try to anonymize as much as possible and then move on to training the model,” says University of Florence technologist Vincenzo Laveglia. “A We have to make sure there’s a balance between various classes of information, otherwise the model becomes an expert on one topic and very uncertain on others.”

Risk 138

Risk Measurement Modeling Data Lake 138

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.

Modeling 226

Modeling Machine Learning Predictive Modeling Consulting 226

O'Reilly on Data

JUNE 15, 2023

The world changed on November 30, 2022 as surely as it did on August 12, 1908 when the first Model T left the Ford assembly line. Should we risk loss of control of our civilization?” The creators of generative AI systems and Large Language Models already have tools for monitoring, modifying, and optimizing them.

Metrics 290

Metrics Reporting Measurement Finance 290

CIO Business Intelligence

OCTOBER 23, 2024

Despite AI’s potential to transform businesses, many senior technology leaders find themselves wrestling with unpredictable expenses, uneven productivity gains, and growing risks as AI adoption scales, Gartner said. This creates new risks around data privacy, security, and consistency, making it harder for CIOs to maintain control.

Enterprise 141

Enterprise Cost-Benefit Broadcasting Risk 141

CIO Business Intelligence

SEPTEMBER 23, 2024

For sectors such as industrial manufacturing and energy distribution, metering, and storage, embracing artificial intelligence (AI) and generative AI (GenAI) along with real-time data analytics, instrumentation, automation, and other advanced technologies is the key to meeting the demands of an evolving marketplace, but it’s not without risks.

Manufacturing 122

Manufacturing Internet of Things Metadata Risk 122

CIO Business Intelligence

JUNE 27, 2024

The issue has become a concern for builders of generative AI models and the enterprises that use them, as some data sets used in AI training have legally and ethically uncertain origins. Trade associations like the DPA may play a role in supporting the enforcement of such legislation and advocating for other similar measures.

Risk 128

Risk Measurement Risk Management Strategy 128

CIO Business Intelligence

MAY 22, 2024

The signatories agreed to publish — if they have not done so already — safety frameworks outlining on how they will measure the risks of their respective AI models. The risks might include the potential for misuse of the model by a bad actor, for instance.

Risk Management 122

Risk Management Risk Publishing Modeling 122

CIO Business Intelligence

SEPTEMBER 26, 2024

That’s because significant challenges persist in leveraging GenAI’s large language models (LLMs). One is the security and compliance risks inherent to GenAI. To make accurate, data-driven decisions, businesses need to feed LLMs with proprietary information, but this risks exposing sensitive data to unauthorized parties.

Enterprise 130

Enterprise Data-driven Risk Testing 130