O'Reilly on Data

DECEMBER 12, 2019

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. While our analysis of each method may appear technical, we believe that understanding the tools available, and how to use them, is critical for all risk management teams.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

Smart Data Collective

SEPTEMBER 17, 2020

Financial institutions such as banks have to adhere to such a practice, especially when laying the foundation for back-test trading strategies. Here are a few of the advantages of Big Data in the banking and financial industry: Improvement in risk management operations. The Role of Big Data. Engaging the Workforce.

Big Data 141

Big Data Finance Risk Management Risk 141

IBM Big Data Hub

SEPTEMBER 6, 2023

A continuous vulnerability management process helps stop cyberattacks—and soften the blow of those that succeed—by finding and fixing flaws before threat actors can weaponize them. The vulnerability management lifecycle Corporate networks are not static. appeared first on IBM Blog.

Management 105

Management Metrics Risk Reporting 105

CDW Research Hub

MAY 24, 2021

Today’s digital risk and compliance profile requires developing an information security program based on a well-structured plan that includes people, processes and technologies, and focuses on the protection of information and information assets. Develop a security risk management program.

Risk Management 52

Risk Management Risk Unstructured Data Business Objectives 52

CIO Business Intelligence

APRIL 13, 2023

Gartner projects that spending on information security and risk management products and services will grow 11.3% To better focus security spend, some chief information security officers (CISOs) are shifting their risk assessments from IT systems to the data, applications, and processes that keep the business going.

IT 111

IT Cost-Benefit Risk Consulting 111

IBM Big Data Hub

JULY 12, 2023

For example, how you react to a disruptive technology or cope with a sudden change in the markets can be the difference between success and failure. Team members discuss possible risks, analyze the risk impact of each one and propose courses of action to increase their overall preparedness.

Risk 40

Risk Cost-Benefit Internet of Things Testing 40

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. However, because most institutions lack a modern data architecture , they struggle to manage, integrate and analyze financial data at pace.

Data Architecture 81

Data Architecture Risk Management Risk Management 81

CIO Business Intelligence

MARCH 5, 2024

CIOs must also partner with CISOs, legal, human resources, and business leaders to build awareness of policies and develop a generative AI risk management strategy. CIOs and IT leaders are at the center and must decide what copilots to test, who should receive access, and whether experiments are delivering business value.

Cost-Benefit 124

Cost-Benefit Advertising Experimentation Software 124

CIO Business Intelligence

JULY 11, 2023

The No-Sharing Principle Under the No Data Sharing Principle, it is crucial that organizations are not required to share sensitive data—whether their proprietary information or personal details—to use these advanced technologies.

Modeling 93

Modeling Testing Experimentation Risk Management 93

IBM Big Data Hub

DECEMBER 4, 2023

The platform has been used to modernize and unify the information technology (IT) ecosystem of major financial firms, simplify human capital management (HCM) across brands’ subsidiaries, and optimize reporting processes in complex healthcare settings.

Testing 77

Testing Consulting Digital Transformation Cost-Benefit 77

IBM Big Data Hub

APRIL 4, 2024

And while enterprise resource planning (ERP) integrates and manages all aspects of a business, BPM focuses on its individual functions—optimizing the organization’s existing, repeatable processes end-to-end. BPM can also provide real-time visibility into claim status and performance metrics.

Management 58

Management Cost-Benefit Metrics Consulting 58

Domino Data Lab

AUGUST 10, 2021

As an example, an image recognition model would be trained on one set of images and then tested on a fresh set of images to ensure it will perform as required. Model risk, whereby a model is used and fails to meet the desired outcome, can be exceptionally dangerous if safeguards are not implemented to manage it.

Modeling 64

Modeling IT Risk Management Deep Learning 64

IBM Big Data Hub

JULY 28, 2023

Every month, the National Institute of Standards and Technology (NIST) adds over 2,000 new security vulnerabilities to the National Vulnerability Database. That’s what the vulnerability management lifecycle is for. Explore IBM Security QRadar Suite The post What is the vulnerability management lifecycle?

Management 66

Management Metrics Risk Measurement 66

IBM Big Data Hub

FEBRUARY 22, 2024

Defense leaders focused on operationalizing the responsible curation of AI must first agree upon a shared vocabulary—a common culture that guides safe, responsible use of AI—before they implement technological solutions and guardrails that mitigate risk. But AI also supports other strategic goals of the DoD.

Metadata 99

Metadata Measurement Risk Modeling 99

CIO Business Intelligence

FEBRUARY 3, 2023

Now as group technology director at The Royal Mint, a limited company wholly owned by HM Treasury, Hobbs has looked to transform the technology landscape, modernise cybersecurity, and grow the IT function amid the organisation becoming, in his words, “more of a suite of businesses”. We’ve had to lift the language,” he adds.

IT 52

IT Experimentation Scorecard Digital Transformation 52

Cloudera

MARCH 18, 2021

A means of incorporating the risk of market illiquidity, including liquidity horizons that range from 10 to 250 days. Continuous monitoring will be required, and banks will need to conduct back-testing to ensure accuracy. A machine learning ops framework that supports regular backtesting and P&L on attribution testing.

Risk 55

Risk Machine Learning Risk Management Measurement 55

O'Reilly on Data

OCTOBER 18, 2022

As AI technologies are adopted more broadly in security and other high-risk applications, we’ll all need to know more about AI audit and risk management. applies external authoritative standards from laws, regulations, and AI risk management frameworks. The answer is simple—bad things and legal liabilities.

Risk Management 291

Risk Management Risk Testing Measurement 291

datapine

AUGUST 29, 2022

And with that understanding, you’ll be able to tap into the potential of data analysis to create strategic advantages, exploit your metrics to shape them into stunning business dashboards , and identify new opportunities or at least participate in the process. 2) Designing Data-Intensive Applications by Martin Kleppman.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

CIO Business Intelligence

MAY 17, 2022

The company is on a mission to revolutionize the banking industry through technology and data and serves as a model for harnessing the power of data for growth. . A few years ago, the leadership realized that the banking industry is going to be dominated by great tech companies that manage risk exceptionally well.

ROI 52

ROI Risk Marketing Modeling 52

AWS Big Data

JANUARY 31, 2024

LSEG’s capture technology ensures lossless data capture and uses a GPS time-source for nanosecond timestamp precision. The default is 20 DPUs, but we tested this calculation with 10, 20, and 40 DPUs to demonstrate how Athena Spark automatically scales to run our analysis.

Marketing 87

Marketing Analytics Visualization Strategy 87

Alation

FEBRUARY 8, 2022

The growing interest in data mesh signals an organizational (rather than technological) shift. Yet technology still plays a key enabling role in making this shift a reality. So how can you seize the data mesh, and up-level your data management and governance practices to catalyze business success? Self-describing.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

Grooper

OCTOBER 23, 2019

Can you see how information management will transform data into a legitimate asset that fuels enterprise-wide goals? To execute on strategy, you’ll need strong data and analytics leadership who understands that advances in technology will spur significant future economic growth. Want to test your governance level? Governance.

Metrics 59

Metrics Measurement Strategy Optimization 59

DataRobot Blog

MARCH 7, 2023

DataRobot identifies and recommends models that are ready to move into production by automatically testing and comparing thousands of models, while those already in production are continuously monitored to ensure performance and compliance. This generates reliable business insights and sustains AI-driven value across the enterprise.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

AWS Big Data

AUGUST 14, 2023

In the same way, organizations seeking to implement successful data mesh strategies must respect the nature and structure (legal, political, commercial, technology) of their organizations in their implementation. Approves changes to data product technology architecture. Approves changes to IAM procedures relating to data products.

Management 81

Management Risk Measurement Optimization 81

Andrew White

JANUARY 11, 2021

So the material is not designed for IT – but spans business and technology. How do you think Technology Business Management plays into this strategy? Value Management or monetization. Risk Management (most likely within context of governance). Product Management. Governance. Architecture.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52