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

erwin

FEBRUARY 12, 2021

Managing an organization’s governance, risk and compliance (GRC) via its enterprise and business architectures means managing them against business processes (BP). Governance, risk and compliance are treated as isolated bubbles. Data-related risks are not connected with the data architects/data scientists.

Risk 98

Risk Slice and Dice Management Enterprise 98

IBM Big Data Hub

AUGUST 16, 2023

Nevertheless, I also understand the criticality of evaluating the inherent risks before embarking on its direct adoption within our organizations. In this discussion, I explore the risks and challenges associated with ChatGPT in an enterprise context, necessitating a careful approach to its implementation.

Risk 57

Risk Modeling Enterprise Interactive 57

CIO Business Intelligence

MAY 9, 2024

Companies want candidates who can drive innovation, deliver meaningful business results, and work closely with other leaders to manage risks. To that end, CAIOs must break down silos and interact with a multitude of leaders in both lines of business and supporting functions, Daly says.

Risk Management 133

Risk Management Risk Cost-Benefit Technology 133

bridgei2i

JUNE 2, 2020

Episode 7: The Impact of COVID-19 on Financial Services & Risk. The Impact of COVID-19 on Financial Services & Risk Management. As past data isn’t relevant anymore, current models aren’t going to work. Now, the first of those areas is definitely risk and portfolio management. Management.

Risk Management 128

Risk Management Risk Enterprise Management 128

erwin

MAY 2, 2022

How to create a solid foundation for data modeling of OLTP systems. As you undertake a cloud database migration , a best practice is to perform data modeling as the foundation for well-designed OLTP databases. This makes mastering basic data modeling techniques and avoiding common pitfalls imperative. Data modeling basics.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

CIO Business Intelligence

APRIL 5, 2024

California and Connecticut lead the pack One state to watch is California, partly because of its large population that interacts with businesses across the US, and partly because the state legislature there tends to be ahead of the pack on consumer protection issues. “There’s obviously going to be heightened scrutiny here across the board.”

Risk 108

Risk Interactive Insurance Strategy 108

IBM Big Data Hub

JUNE 14, 2023

And then you need highly specialized, expensive and difficult to find skills to work the magic of training an AI model. But that’s all changing thanks to pre-trained, open source foundation models. Sometimes, you don’t know what data a model was trained on because the creators of those models won’t tell you.

Modeling 93

Modeling Data Lake Enterprise Deep Learning 93

bridgei2i

NOVEMBER 20, 2020

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.

Risk Management 92

Risk Management Risk Management Metrics 92

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI in commerce—such as models trained on inadequate or inappropriate data—lead to bad experiences that alienate consumers and businesses. To take one example, AI-facilitated tools like voice navigation promise to upend the way users fundamentally interact with a system.

B2B 58

B2B Interactive Optimization Forecasting 58

Laminar Security

DECEMBER 1, 2023

As more organizations migrate their data to the cloud, they face an increasing range of risks and threats, including data breaches, data leakage, data loss, data misuse, data compliance violations, shadow data and more. As the quantity of shadow data grows, so does the potential risk for a data breach.

Modeling 52

Modeling Cost-Benefit Risk Data-driven 52

CIO Business Intelligence

APRIL 30, 2024

The law will also extend beyond the borders of the EU member nations, as any company interacting with residents of the EU will be subject to the regulations. They must conduct risk assessments, take steps to reduce risk, maintain use logs, comply with transparency requirements, and ensure human oversight.

IT 88

IT Risk Data-driven Modeling 88

DataKitchen

FEBRUARY 27, 2024

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure. Contextual Relevance: Ensuring the data fed into LLMs is contextually relevant is paramount.

Data Quality 117

Data Quality Unstructured Data Testing Modeling 117

IBM Big Data Hub

FEBRUARY 13, 2024

The compact design and touch-based interactivity seemed like a leap into the future. This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Generative adversarial networks (GANs) or variational autoencoders (VAEs) are used for images, videos, 3D models and music.

Enterprise 125

Enterprise Modeling Testing Data-driven 125

erwin

MAY 14, 2021

But even though speed is critical, businesses must take the time to model and document new applications for compliance and transparency. For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development.

Modeling 80

Modeling Digital Transformation Data-driven Optimization 80

CIO Business Intelligence

SEPTEMBER 20, 2023

Now Assist for IT Service Management, Customer Service Management, and HR Service Delivery add new text creation and summarization features and an interactive chatbot interface to help workers get to relevant information more quickly. Other pieces include staffing, skills training, partner involvement, legal exposure, and risk mitigation.”

Cost-Benefit 108

Cost-Benefit Software Finance Interactive 108

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

O'Reilly on Data

APRIL 23, 2024

Some of those innovations, like Amazon’s cloud computing business, represented enormous new markets and a new business model. Google, for example, invented the Large Language model architecture that underlies today’s disruptive AI startups. These companies did continue to innovate. I think not.

Advertising 270

Advertising Cost-Benefit Marketing Risk 270

CIO Business Intelligence

FEBRUARY 16, 2024

Banks are increasingly turning to AI to assist with a wide range of tasks, from customer onboarding to fraud detection and risk regulation. Copilot combines large language models (LLMs) with the bank’s data, providing staff access to a virtual PA, copywriter and analyst. For more information visit our new Copilot Banking site.

Interactive 105

Interactive Risk Modeling Reporting 105

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. As with the part 1 and part 2 of this data modeling blog series, the cloud is not nirvana. Data modeling basics. Data Modeling. So, let’s now begin to data model NoSQL databases.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

IBM Big Data Hub

MAY 6, 2024

But as AI transforms and redefines how businesses operate and how customers interact with them, trust in technology must be built. More than 50% of respondents are concerned about unpredictable risks impacting generative AI initiatives and fear they will create increased potential for business disruption.

Enterprise 73

Enterprise Risk Strategy ROI 73

CIO Business Intelligence

FEBRUARY 28, 2024

Essentially, the technology involves the replication of the human body in software models. Using these models, healthcare providers can test drugs and therapies with unprecedented speed and accuracy, reducing risks for both patients and physicians.

Informatics 99

Informatics Data-driven Digital Transformation Predictive Analytics 99

IBM Big Data Hub

MARCH 4, 2024

While many organizations have implemented AI, the need to keep a competitive edge and foster business growth demands new approaches: simultaneously evolving AI strategies, showcasing their value, enhancing risk postures and adopting new engineering capabilities. Consider the following: Do you need a public foundation model?

Enterprise 106

Enterprise ROI Risk Strategy 106

O'Reilly on Data

JANUARY 16, 2024

I recently chatted with ChatGPT, and I want to use that experience to reflect on the usability of voice interfaces for AI tools based on Large Language Models. These long solo drives were the perfect opportunity to test out ChatGPT’s voice feature because I couldn’t interact with the app using my hands for safety reasons.

Interactive 184

Interactive Recreation/Entertainment Visualization IT 184

CIO Business Intelligence

MAY 15, 2024

GenAI has the potential to transform digital operations, even as it introduces possible new risks and ethical quandaries. Those prepared to embrace the change with a robust plan for managing the risks will be best placed to take advantage. Large language models (LLMs) are only as good as the data they leverage.

Uncertainty 64

Uncertainty Risk Business Objectives Software 64

IBM Big Data Hub

OCTOBER 2, 2023

The recent rise of generative artificial intelligence (AI) including large language models (LLMs) has inspired organizations in every industry to consider how AI can drive innovation. Leaders are increasingly recognizing the power of AI as well as its potential limitations and risks.

Consulting 85

Consulting Risk Modeling Testing 85

O'Reilly on Data

JULY 28, 2020

You must detect when the model has become stale, and retrain it as necessary. This isn’t always simple, since it doesn’t just take into account technical risk; it also has to account for social risk and reputational damage. Fault Tolerant Versus Fault Intolerant AI Problems.

Marketing 362

Marketing Experimentation Metrics Testing 362

Jet Global

APRIL 27, 2020

Any company worth its salt uses financial modeling to guide its financial planning and strategic decision-making. Financial modeling offers data-driven, quantitative analysis that tells you where your company stands and where it’s heading. But one model can’t do it all. What Is Financial Modeling? Organic business growth.

Modeling 72

Modeling Forecasting Finance Visualization 72

CIO Business Intelligence

NOVEMBER 6, 2023

A Defense in Depth strategy is essential because it helps businesses stay ahead of these risks by implementing multiple lines of defense. By proactively addressing these vulnerabilities, you can dramatically reduce the risk of successful attacks and maintain a strong security stance.

Risk 122

Risk Measurement Cost-Benefit Strategy 122

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 95

Cost-Benefit Modeling Manufacturing Interactive 95

Laminar Security

DECEMBER 13, 2023

As we generate and interact with unprecedented volumes of data, the task of accurately identifying, categorizing, and utilizing this information becomes increasingly difficult. Close to 70% of respondents in an ISC report indicated that they believe their organization lacks requisite cybersecurity staff to handle cloud data risk effectively.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

O'Reilly on Data

MAY 25, 2021

GPT-3 is essentially an auto-complete bot whose underlying Machine Learning (ML) model has been trained on vast quantities of text available on the Internet. I’d like to share my thoughts on GPT-3 in terms of risks and countermeasures, and discuss real examples of how I have interacted with the model to support my learning journey.

Modeling 346

Modeling Marketing Testing Machine Learning 346

CIO Business Intelligence

FEBRUARY 8, 2024

AI is like the discovery of fire—it’s a great tool if you know how to use it, but if you don’t use it responsibly (or use a model built responsibly), it will burn you. Interacting with AI data or experiences in silos introduces risk and increases inefficiencies because it’s kept separate.

Cost-Benefit 107

Cost-Benefit Experimentation Interactive Risk 107

CIO Business Intelligence

SEPTEMBER 7, 2023

That’s why, around the world, governments and the defense industry as a whole are now investing and exploring generative artificial intelligence (AI), or large language models (LLMs), to better understand what’s possible. The second challenge is managing new risks, which stem primarily from the threat of misinformation.

Unstructured Data 102

Unstructured Data Cost-Benefit Risk Data-driven 102

IBM Big Data Hub

FEBRUARY 20, 2024

Climate models provide answers Human activities precipitated changes to the Earth’s climate in the 20th century and will largely determine the future climate. Global climate models have given climate scientists a set of expectations as to what the future could hold, both for the Earth at large and for specific regions.

Modeling 122

Modeling Forecasting Reporting Risk 122

IBM Big Data Hub

SEPTEMBER 6, 2023

According to the IBM survey, when CMOs were asked what they thought the primary challenges were in adopting generative AI, they listed three top concerns: managing the complexity of implementation, building the data set and brand and intellectual property (IP) risk. With the right generative AI strategy, marketers can mitigate these concerns.

Marketing 122

Marketing Strategy B2B Cost-Benefit 122

IBM Big Data Hub

NOVEMBER 6, 2023

Service providers need technology systems with a centralized customer journey log that can track interactions, sentiment and next steps across every touchpoint to deliver a seamless customer experience. Less than 15% of SMBs want to interact with providers through phone and automated voice systems.

Cost-Benefit 110

Cost-Benefit Enterprise ROI Data Warehouse 110