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

MARCH 25, 2021

Usually we talk about benefits which are rather qualitative measures, but what we need for decision-making processes are values,” Pörschmann says. “We Risk Management and Regulatory Compliance. Risk management, specifically around regulatory compliance, is an important use case to demonstrate the true value of data governance.

Data Governance 109

Data Governance IT Cost-Benefit Risk 109

CIO Business Intelligence

JUNE 8, 2023

This role helps oversee the development of new systems, working alongside software developers and hardware engineers with an eye on quality control measures and maintaining a steady pace toward established milestone goals.

IT 140

IT Digital Transformation Software Risk 140

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

O'Reilly on Data

MAY 18, 2020

Materiality is a widely used concept in the world of model risk management , a regulatory field that governs how financial institutions document, test, and monitor the models they deploy. Data sensitivity also tends to be a helpful measure for the materiality of any incident. How Material Is the Threat?

Risk 359

Risk Modeling Data Processing Software 359

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

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

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. Entities will also be expected to put appropriate cybersecurity protection measures in place.

Cost-Benefit 85

Cost-Benefit Testing Strategy Risk Management 85

CIO Business Intelligence

MARCH 24, 2023

However, there are many other challenges as well, including regulatory requirements, human capital, stakeholder engagement, alignment of materiality and performance, and the need to embed ESG into an existing ERM (Enterprise Risk Management) framework. “The

Risk Management 52

Risk Management Consulting Metrics Data Quality 52

Alation

AUGUST 17, 2022

Constellation Analyst Dion Hinchcliffe suggests that functions should be loosely integrated into the following streams: Governance, risk, compliance. Enterprise risk management. Data management. Risk, however, is a different challenge. While risk may be defined, it might not be well addressed.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

CIO Business Intelligence

MARCH 24, 2023

They must be accompanied by documentation to support compliance-based and operational auditing requirements. Key features include a collaborative business glossary, the ability to visualize data lineage, and generate data quality measurements based on business definitions.

Data Governance 142

Data Governance Management Metadata Data Quality 142

DataRobot

JANUARY 18, 2022

The purpose of these checklists is to avoid complacency and to ensure conscious observation of risk management. AI governance should be proportionate to the risk. But when there is material risk, it helps to list, then consciously investigate these risks. The Need For Documentation. Describing an AI System.

Risk Management 52

Risk Management Risk Data-driven Metrics 52

Octopai

JULY 9, 2020

It required banks to develop a data architecture that could support risk-management tools. Not only did the banks need to implement these risk-measurement systems (which depend on metrics arriving from distinct data dictionary tools), they also needed to produce reports documenting their use.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86

Smart Data Collective

MAY 25, 2023

Fortunately, there are a number of measures that small businesses can take to protect their sensitive information from unauthorized access. Cybercriminals target these businesses primarily due to their resource inadequacy and often lack of progressive cyber security measures. Additionally, cybercrime costs SMEs over $2.2

Internet of Things 89

Internet of Things Cost-Benefit Risk Software 89

DataRobot

JULY 16, 2021

Accuracy — this refers to a subset of model performance indicators that measure a model’s aggregated errors in different ways. Robust documentation throughout the end- to-end modeling workflow is one of the strongest enablers of compliance. Security — large amounts of sensitive data are analyzed or transmitted with AI systems.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

CIO Business Intelligence

MARCH 13, 2024

So when on-boarding potential vendors, productivity has increased by 70 to 80% as a result of using gen AI to help analyze masses of documents. “We Still, he urges companies to look beyond measurements of coding speed. We did side-by-side testing,” he says. What if writing code wasn’t the real issue?”

IT 128

IT Consulting Testing Cost-Benefit 128

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. The study of security in ML is a growing field—and a growing problem, as we documented in a recent Future of Privacy Forum report. [8]. That’s where model debugging comes in. Residual analysis.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

Smart Data Collective

MAY 17, 2023

Since so many companies use Office 365, they need to make sure the documents stored on it are safe from hackers. While Office 365 offers built-in security features, it is essential to understand that these measures alone may not be sufficient to safeguard your business data. This entails shielding applications from cyberattacks.

Risk 87

Risk Measurement Software Management 87

CDW Research Hub

FEBRUARY 14, 2020

Let’s take a closer look at the options, tools and documentation involved with choosing a CSP. As a prerequisite, your organization must already have governance and risk management teams, which will define the company policies and set compliance standards from which you can establish procedures. NIST, HIPAA, FIPS and ENISA).

Risk 52

Risk Reporting Measurement Insurance 52

DataRobot Blog

JUNE 27, 2022

A prerequisite in measuring a deployed model’s evolving performance is to collect both its input data and business outcomes in a deployed setting. With this data in hand, we are able to measure both the data drift and model performance, both of which are essential metrics in measuring the health of the deployed model.

Risk 59

Risk Modeling Metrics Measurement 59

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

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. REFERENCES. [1]

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

CIO Business Intelligence

DECEMBER 5, 2022

Quality management: Identify quality requirements. Human resource management: Plan and identify human resource needs. Communications management: Plan stakeholder communications. Risk management: Perform qualitative and quantitative risk analysis, plan risk mitigation strategies.

Management 134

Management Cost-Benefit Key Performance Indicator Software 134

erwin

MARCH 12, 2020

It also highlights select enterprise architecture management suite (EAMS) vendors based on size and functionality, including erwin. The report notes six primary EA competencies in which we excel in the large vendor category: modeling, strategy translation, risk management, financial management, insights and change management.

Enterprise 85

Enterprise Reporting Management ROI 85

O'Reilly on Data

JULY 15, 2019

After the 2008 financial crisis, the Federal Reserve issued a new set of guidelines governing models— SR 11-7 : Guidance on Model Risk Management. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk. Model risk management. AI projects in financial services and health care.

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

Alation

MARCH 14, 2023

Creating a clear process with documented steps will help. Govern Data governance models should be flexible and dynamic while proactively addressing risk management and compliance with local and global regulations.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

DataRobot

AUGUST 9, 2021

General Data Protection Regulation, California Consumer Privacy Act, SR 11-7 Guidance on Model Risk Management, etc). It empowers enterprises to measure, monitor, and manage AI-introduced risks at scale. C-level buyers in compliance, audit, and risk use the AI governance solution to reduce regulatory risks.

Machine Learning 52

Machine Learning Risk Testing Insurance 52

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. Document Design and Deployment For Regulations and Clarity.

Risk Management 52

Risk Management Risk Modeling Management 52

erwin

DECEMBER 20, 2018

Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. The driving factors behind data governance adoption vary. The Top Five Data Governance Use Cases and Drivers.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

Smart Data Collective

APRIL 19, 2021

From conversing on personal devices (BYODs) to sending documents to the wrong recipient, or using unsecured applications for transfers, the risk for potential leaks is high. By putting the correct technical measures in place, you can ensure that any confidential data is protected in the best possible and most efficient manner.

Risk 120

Risk Management Measurement Optimization 120

bridgei2i

APRIL 23, 2020

The banking sector globally is definitely going to see impact, some more grave than the others and most of them are announcing short to mid term measure both from a customer and business risk mitigation standpoint. Using recommendation engines, banks could digitize Customer Acquisition. Even onboarding has gone digital. Learn MORE. “We

Risk 52

Risk Management Scorecard Forecasting 52

IBM Big Data Hub

JULY 7, 2023

Here are some data security measures that every organization should strongly consider implementing. Create an incident response plan , a written document that details how you will respond before, during and after a suspected or confirmed security threat. Manage third-party-related risks. Define sensitive data.

Risk 40

Risk Data Governance Data Lake Data-driven 40

John Wheeler

NOVEMBER 25, 2020

Integrated risk management (IRM) technology is uniquely suited to address the myriad of risks arising from the current crisis and future COVID-19 recovery. Provide a full view of business operations by delivering forward-looking measures of related risk to help customers successfully navigate the COVID-19 recovery.

Marketing 110

Marketing Risk Management Risk Digital Transformation 110

DataRobot Blog

JULY 22, 2022

At many organizations, the current framework focuses on the validation and testing of new models, but risk managers and regulators are coming to realize that what happens after model deployment is at least as important. They may not have been documented, tested, or actively monitored and maintained. Legacy Models. White Paper.

Modeling 105

Modeling Risk Management Testing Risk 105

erwin

APRIL 21, 2020

By combining physical system catalogs, critical data elements, and key performance measures with clearly defined product and sales goals, you can manage the effectiveness of your business and ensure you understand what critical systems are for business continuity and measuring corporate performance.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

As COVID-19 continues to spread, organizations are evaluating and adjusting their operations in terms of both risk management and business continuity. One example is the European Union (EU) Open Data Portal , which is used to document, catalog and govern EU data related to the pandemic.

Measurement 96

Measurement Sales Data Governance Metadata 96

DataRobot Blog

JULY 21, 2022

Outline clear metrics to measure success. Document assumptions and risks to develop a risk management strategy. dashes and parentheses in telephone numbers) Inconsistent units of measure (e.g., Create model compliance documentation for regulated industries. Define project scope.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98