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 191

Machine Learning Modeling Testing Risk Management 191

bridgei2i

JUNE 2, 2020

Episode 7: The Impact of COVID-19 on Financial Services & Risk. Management. The Impact of COVID-19 on Financial Services & Risk Management. As past data isn’t relevant anymore, current models aren’t going to work. PODCAST: COVID 19 | Redefining Digital Enterprises. Listening time: 12 minutes.

Risk Management 128

Risk Management Risk Enterprise Management 128

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

IBM Big Data Hub

FEBRUARY 13, 2024

For example, organizations can use generative AI to: Quickly turn mountains of unstructured text into specific and usable document summaries, paving the way for more informed decision-making. This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task.

Enterprise 127

Enterprise Modeling Testing Data-driven 127

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

CIO Business Intelligence

NOVEMBER 21, 2023

After all, 41% of employees acquire, modify, or create technology outside of IT’s visibility , and 52% of respondents to EY’s Global Third-Party Risk Management Survey had an outage — and 38% reported a data breach — caused by third parties over the past two years.

IT 137

IT Risk Cost-Benefit Risk Management 137

CIO Business Intelligence

DECEMBER 19, 2023

Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model. These workstreams require documenting a vision, assigning leaders, and empowering teams to experiment.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

O'Reilly on Data

JANUARY 22, 2019

An exploration of three types of errors inherent in all financial models. At Hedged Capital , an AI-first financial trading and advisory firm, we use probabilistic models to trade the financial markets. All financial models are wrong. Clearly, a map will not be able to capture the richness of the terrain it models.

Modeling 134

Modeling Finance Uncertainty Data mining 134

IBM Big Data Hub

OCTOBER 4, 2022

Manual processes that introduce risk and make it hard to scale. Multiple unsupported tools for building and deploying models. According to Gartner 54% of models are stuck in pre-production because there is not an automated process to manage these pipelines and there is a need to ensure the AI models can be trusted.”

Metadata 102

Metadata Risk Risk Management Experimentation 102

CIO Business Intelligence

SEPTEMBER 7, 2023

Additionally, it’s paramount within the financial services sector to ensure responsible AI and adherence to regulatory guidance for model risk. Keeping our AI approach interpretable and managing bias becomes crucial. Shaun has over 20 years of IT experience with specialization in information security and risk management.

Risk Management 98

Risk Management Risk Testing Digital Transformation 98

IBM Big Data Hub

DECEMBER 4, 2023

The most common insurance use cases include optimizing processes that require processing large documents and large blocks of text or images. Customer engagement Providing insurance coverage involves working with numerous documents. IBM works with several insurance companies to identify high-value opportunities for using generative AI.

Insurance 55

Insurance Digital Transformation Risk Management Risk 55

Smart Data Collective

SEPTEMBER 17, 2020

Some prominent banking institutions have gone the extra mile and introduced software to analyze every document while recording any crucial information that these documents may carry. Here are a few of the advantages of Big Data in the banking and financial industry: Improvement in risk management operations.

Big Data 141

Big Data Finance Risk Management Risk 141

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just

Risk 359

Risk Modeling Data Processing Software 359

erwin

SEPTEMBER 3, 2020

It documents your data assets from end to end for business understanding and clear data lineage with traceability. Data governance and EA also provide many of the same benefits of enterprise architecture or business process modeling projects: reducing risk, optimizing operations, and increasing the use of trusted data.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

IBM Big Data Hub

APRIL 4, 2024

Lots of innovation is happening, with new technologies emerging in areas such as data and AI, payments, cybersecurity and risk management, to name a few. A third-party risk management review, where the ISV needs to describe how it is complying to required controls. Most of these new technologies are born-in-cloud.

Cost-Benefit 60

Cost-Benefit Risk Management Risk Digital Transformation 60

CIO Business Intelligence

APRIL 14, 2023

Focusing on generative AI may be a useful approach since it addresses large language models (LLMs), including ChatGPT, without having to boil the ocean across the AI universe. Determine your policy scope – The first step to craft your corporate use policy is to consider the scope.

Risk 122

Risk Experimentation Marketing Risk Management 122

erwin

OCTOBER 17, 2019

At erwin, we’re definitely witnessing this EA evolution as more and more as organizations undertake digital transformation initiatives, including rearchitecting their business models and value streams, as well as responding to increasing regulatory pressures. The Regulatory Rationale for Integrating Data Management & Data Governance.

Enterprise 106

Enterprise Digital Transformation Data Governance Risk Management 106

DataRobot Blog

APRIL 11, 2022

An AI impact assessment will carefully document the harms for each stakeholder. It is designed by humans, built by humans, managed by humans, with the objective to serve human goals. Your documentation should describe how the AI system contributes to human values and human rights. Imperfection. Conclusion.

Risk 98

Risk Risk Management Software Consulting 98

John Wheeler

OCTOBER 20, 2020

We continue our “20 for 20” theme this year by highlighting the integrated risk management (IRM) critical capabilities and top 20 software functions / features. These five capabilities support both integrated view of strategic, operational and technology risk as well as the related business outcomes, processes and assets.

Risk Management 52

Risk Management Risk Predictive Modeling Insurance 52

erwin

APRIL 30, 2021

In a world where agility and innovation are highly valued, speed is a critical factor for success.COVID-19 forced many businesses to radically change their business models – or re-evaluate their business processes – shifting the focus of enterprise architects. Priority 3: Risk Management – Security and Compliance.

Enterprise 131

Enterprise Digital Transformation Risk Management Risk 131

Cloudera

AUGUST 12, 2021

In a 2021 white paper titled “Data Excellence: Transforming manufacturing and supply systems“ written by the World Economic Forum and the Boston Consulting Group, it documented that 75% of executives interviewed believed that advanced analytics in manufacturing was more important today than three years ago. Risk Management.

Data-driven 107

Data-driven Manufacturing Insurance Risk Management 107

CIO Business Intelligence

JUNE 12, 2023

In 2012, COBIT 5 was released and in 2013, the ISACA released an add-on to COBIT 5, which included more information for businesses regarding risk management and information governance. Other changes included minor edits to terminology and phrasing used throughout the documentation.

Risk Management 94

Risk Management Strategy Digital Transformation Enterprise 94

erwin

JULY 12, 2019

Modern, strategic data governance , which involves both IT and the business, enables organizations to plan and document how they will discover and understand their data within context, track its physical existence and lineage, and maximize its security, quality and value. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 59

Data mining Machine Learning Deep Learning Marketing 59

CIO Business Intelligence

NOVEMBER 23, 2022

Unlike other frameworks, EA doesn’t include a formal documentation structure; instead, it’s intended to offer a more holistic view of the enterprise. EA is also used in systems development, IT management and decision-making, and IT risk management to eliminate errors, system failures, and security breaches. Data modeling.

Enterprise 128

Enterprise Cost-Benefit Digital Transformation Strategy 128

CIO Business Intelligence

JUNE 8, 2023

Relevant skills include security architecture design, threat modeling, compliance and regulations, security operations, risk assessment and management, and security infrastructure implementation. Average salary: US$145,512 Increase since 2021: 7.7%

IT 140

IT Digital Transformation Software Risk 140

erwin

AUGUST 20, 2020

As a practice, EA involves the documentation, analysis, design and implementation of an organization’s assets and structure. With an enterprise architecture management suite (EAMS) , an organization can define and document its structure to more effectively determine how to achieve its goals. Innovation Management.

Enterprise 140

Enterprise Cost-Benefit Risk Data Governance 140

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In this case, once a customer’s documents are scanned and uploaded, the necessary data is extracted from the key documents and then converted to machine-readable form.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

CIO Business Intelligence

AUGUST 30, 2023

A CISO at a major marketing software firm worried about this explicitly, stating, “The real risk is that you have unintentional data leakage of confidential information. Maybe it gets used in modeling. So I think the real risk here is the exposure of sensitive information. Maybe it then winds up getting exposed.

Enterprise 132

Enterprise Risk Measurement Software 132

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In this case, once a customer’s documents are scanned and uploaded, the necessary data is extracted from the key documents and then converted to machine-readable form. Predictive Analytics. These include-.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. They all serve to answer the question, “How well can my model make predictions based on data?” How can identifying gaps or discrepancies in the training data help you build a more trustworthy model? Dimensions of Trust. How large is the data set?

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

CIO Business Intelligence

SEPTEMBER 20, 2023

The best way to address this gap is to draft a simple vision statement written by product managers and delivery leaders in collaboration with stakeholders and agile teams. The writing process builds trust, and a documented vision builds a shared understanding of priorities.

Digital Transformation 135

Digital Transformation Uncertainty Metrics Business Objectives 135

CIO Business Intelligence

JULY 6, 2023

From 1 January 2024, the provisions relating to supplier risk management will also apply to companies with more than 1,000 employees. CYVC offers the possibility to process large amounts of data (semi-) automatically in a short time frame and identifies risks based on different assessment methods.

Cost-Benefit 96

Cost-Benefit Risk Digital Transformation Risk Management 96

erwin

NOVEMBER 13, 2020

Data Security & Risk Management. Innovation Management. For example, a COVID response plan will use EA to document if employees work from home, what their roles are, the projects on which they’re working, and what their schedules are. Digital Transformation. Compliance/Legislation. Artificial Intelligence.

Enterprise 131

Enterprise Digital Transformation Key Performance Indicator Data-driven 131

IBM Big Data Hub

AUGUST 18, 2023

The Digital Operational Resilience Act , or DORA, is a European Union (EU) regulation that created a binding, comprehensive information and communication technology (ICT) risk-management framework for the EU financial sector.

Cost-Benefit 82

Cost-Benefit Testing Strategy Risk Management 82