CIO Business Intelligence

NOVEMBER 27, 2023

Developing and deploying successful AI can be an expensive process with a high risk of failure. Six tips for deploying Gen AI with less risk and cost-effectively The ability to retrain generative AI for specific tasks is key to making it practical for business applications. The possibilities are endless, but so are the pitfalls.

Risk 121

Risk Cost-Benefit Modeling Optimization 121

DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States.

Risk 64

Risk Modeling Machine Learning Data Quality 64

CIO Business Intelligence

MARCH 18, 2024

There are a lot of risks and a lot of land mines to navigate,” says the analyst. Coming to grips with risk The first step in making any bet — or investment — is to understand your ability to withstand risk. We have been developing our own internal AI capability over the last few years using open-source models.

Risk 125

Risk Cost-Benefit Data Processing Testing 125

DataRobot Blog

JUNE 27, 2022

In our previous two posts, we discussed extensively how modelers are able to both develop and validate machine learning models while following the guidelines outlined by the Federal Reserve Board (FRB) in SR 11-7. Monitoring Model Metrics.

Risk 59

Risk Modeling Metrics Measurement 59

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 75

Risk Modeling Management Metadata 75

CIO Business Intelligence

FEBRUARY 20, 2024

While cloud risk analysis should be no different than any other third-party risk analysis, many enterprises treat the cloud more gently, taking a less thorough approach. Interrelations between these various partners further complicate the risk equation. That’s where the contract comes into play.

Risk 113

Risk Enterprise Strategy Snapshot 113

IBM Big Data Hub

MARCH 27, 2024

As businesses make plans to mitigate climate risks such as extreme weather events, they have an opportunity to innovate with new business models and demonstrate leadership by implementing more sustainable practices. What is climate risk? To best prepare, organizations need to develop a climate risk strategy.

Risk 65

Risk Forecasting Insurance Strategy 65

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

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

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? They need to understand;

Risk 80

Risk Modeling Risk Management Measurement 80

CIO Business Intelligence

JUNE 9, 2023

Elisabeth Stjernstoft, CIO at Swedish energy giant Ellevio, agrees that there’s a risk of using biased data that’s not representative of the customer group or population being looked at. “It We have to look at the data on which the model is trained, but also at how the algorithms are designed and the selection of functions. “We

Risk 98

Risk Machine Learning Modeling Technology 98

IBM Big Data Hub

FEBRUARY 22, 2024

The rise of foundation models that power the growth of generative AI and other AI use cases offers exciting possibilities—yet it also raises new questions and concerns about their ethical design, development, deployment, and use. Known risks from prior or earlier forms of AI systems.

Modeling 65

Modeling Risk Strategy Enterprise 65

CIO Business Intelligence

APRIL 11, 2023

Over the next five years, the healthcare industry is expected to go through dramatic changes as service providers expand value-based care models and equipment manufacturers strive to keep pace in a digital-first world. Everybody wants to have a business impact and business outcome,” she explains.

Modeling 98

Modeling IT Strategy Uncertainty 98

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 94

Risk Risk Management Strategy Enterprise 94

CIO Business Intelligence

AUGUST 25, 2022

About 41% of boards of directors in enterprises, according to a survey spanning 273 respondents across US, Europe and APAC, viewed geopolitical power shifts and turbulence as one of the biggest risks to performance. Data sovereignty will be a key focus area for CIOs. These policies can lead to CIOs being mandated to buy from certain vendors.

Risk 145

Risk Enterprise Reporting Technology 145

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 220

Machine Learning Risk Management Statistics 220

Analytics Vidhya

APRIL 4, 2024

Artificial intelligence (AI) researchers at Anthropic have uncovered a concerning vulnerability in large language models (LLMs), exposing them to manipulation by threat actors. Dubbed the “many-shot jailbreaking” technique, this exploit poses a significant risk of eliciting harmful or unethical responses from AI systems.

Risk 231

Risk Modeling Analytics IT 231

John Wheeler

NOVEMBER 24, 2020

However, for security and risk management professionals it can make a huge difference. Take for example the terms cyber risk, digital risk and the digitalization of risk management. Viewed together, the three terms represent key aspects of integrated risk management (IRM). For Shakespeare’s Juliet, not much.

Risk Management 85

Risk Management Risk Management Technology 85

CIO Business Intelligence

NOVEMBER 21, 2023

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT. Following are seven steps to guide this transformation for competitive advantage.

IT 130

IT Risk Cost-Benefit Risk Management 130

CIO Business Intelligence

NOVEMBER 7, 2023

What IT can do about generative AI hallucinations Fortunately, there are actions IT organizations can take to reduce the risk of generative AI hallucinations—either through decisions they make within their own environments or how internal users are trained to use existing tools. Here are a range of options IT can use to get started.

IT 114

IT Risk Modeling Strategy 114

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. This blog continues the discussion, now investigating the risks of adopting AI and proposes measures for a safe and judicious response to adopting AI.

Insurance 71

Insurance Risk Testing Data Quality 71

CIO Business Intelligence

MARCH 11, 2024

And yet, IT teams face significant challenges, including: • Addressing information overload • Predicting capacity planning • Assessing risks that are sometimes unknown • Meeting complicated regulatory standards Complexity is the common thread that runs through these challenges. IT professionals are already overwhelmed by alerts and tasks.

IT 93

IT Digital Transformation Reporting Predictive Analytics 93

IBM Big Data Hub

APRIL 9, 2024

Preparing and annotating data IBM watsonx.data helps organizations put their data to work, curating and preparing data for use in AI models and applications. “For the Masters we use 290 traditional AI models to project where golf balls will land,” says Baughman. ” Watsonx.ai ” Watsonx.ai

Management 84

Management IT Machine Learning Metrics 84

IBM Big Data Hub

MAY 1, 2023

This wave of AI is attributable to what are known as foundation models. What are foundation models? As the name suggests, foundation models can be the foundation for many kinds of AI systems. Using machine learning techniques, these models apply information learned about one situation to another situation.

Modeling 98

Modeling Risk Machine Learning Technology 98

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. This should include its proposed redress mechanisms.

Measurement 296

Measurement Risk Modeling Metrics 296

BA Learnings

OCTOBER 4, 2020

The Business Model canvas is the lighter and more agile version of a business plan that can help businesses define what they are about. Business theorist Alexander Osterwalder and Yves Pigneur in 2004, introduced an approach known as the Business Model Canvas. Key Resources These are the assets needed to execute a business model.

Modeling 147

Modeling Risk Sales Strategy 147

CIO Business Intelligence

NOVEMBER 16, 2023

A large language model (LLM) is a type of gen AI that focuses on text and code instead of images or audio, although some have begun to integrate different modalities. A large language model (LLM) is a type of gen AI that focuses on text and code instead of images or audio, although some have begun to integrate different modalities.

Modeling 132

Modeling Enterprise Marketing Sales 132

IBM Big Data Hub

JUNE 19, 2023

Companies can manufacture products closer to the consumer, reducing the risk of disruption caused by natural disasters and geopolitical instability. The European Union and China are investing trillions in their economies to rebuild local industries and create a less risk-prone supply chain.

Risk 81

Risk Manufacturing Reporting Modeling 81

Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. .

Risk 97

Risk Optimization Management Insurance 97

IBM Big Data Hub

JANUARY 28, 2020

Any financial services firm using AI must revisit its approach to model risk management. The reason is that AI models are evolving faster than the rules-based models that were standard previously. If AI models perform inadequately, major operational losses can grow quickly.

Risk 84

Risk Modeling Big Data Management 84

CIO Business Intelligence

MARCH 21, 2024

In 2018, the day after his employer publicly announced it was being acquired, Lynn Lovelady, then VP of IT at Energen, received a pivotal phone call that would reshape his career. The Birmingham, Ala.-based To address the growing pains, Lovelady reinforced the importance of strategic planning for IT.

IT 106

IT Manufacturing Risk Management Risk 106

CIO Business Intelligence

DECEMBER 19, 2023

Their steady income stream and relatively low risk compared to equities make them an especially important component of pension and retirement planning. Each type of issuer presents a different level of risk and tax treatment. Hexaware conducted extensive fine-tuning to adapt the model to different industries and company types. “We

Risk 52

Risk Cost-Benefit Unstructured Data Data-driven 52

Domino Data Lab

AUGUST 10, 2021

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. The process of creating models is called modeling.

Modeling 64

Modeling IT Risk Management Deep Learning 64

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 96

Risk Cost-Benefit Software Technology 96

CIO Business Intelligence

MAY 17, 2022

Even if the AI apocalypse doesn’t come to pass, shortchanging AI ethics poses big risks to society — and to the enterprises that deploy those AI systems. The following real-world implementation issues highlight prominent risks every IT leader must account for in putting together their company’s AI deployment strategy.

Risk 142

Risk Consulting Machine Learning Data Science 142

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 190

Machine Learning Modeling Testing Risk Management 190

Domino Data Lab

AUGUST 6, 2021

All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards. As such, model governance needs to be applied to each model for as long as it’s being used.

Machine Learning 145

Machine Learning Modeling Testing Risk 145