DataRobot Blog

APRIL 29, 2022

The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks. However, after the financial crisis, financial regulators around the world stepped up to the challenge of reigning in model risk across the financial industry.

Risk 111

Risk Modeling IT Risk Management 111

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. 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.

Big Data 141

Big Data Finance Risk Management Risk 141

CIO Business Intelligence

SEPTEMBER 17, 2024

Sponsor for operational and risk management solutions While many business risk areas will find sponsors in operations, finance, and risk management functions, finding sponsors and prioritizing investments to reduce IT risks can be challenging.

Enterprise 145

Enterprise Digital Transformation Cost-Benefit Risk 145

CIO Business Intelligence

OCTOBER 3, 2023

They enable greater efficiency and accuracy and error reduction, better decision making, better compliance and risk management, process optimisation and greater agility. Process optimisation: processes are examined, re-engineered, standardised and carefully tested prior to being automated processes.

Cost-Benefit 118

Cost-Benefit Machine Learning Interactive Software 118

CIO Business Intelligence

AUGUST 30, 2024

Qualifications: High school diploma or equivalent Cost: $300 plus a $100 application fee PHR The Professional in Human Resources (PHR) demonstrates mastery of the technical and operational aspects of HR management, including US laws and regulations.

Cost-Benefit 110

Cost-Benefit Risk Management Strategy Testing 110

CIO Business Intelligence

SEPTEMBER 7, 2023

Established risk management framework to evaluate the use cases and validate the controls to manage relevant risks Continuous authentication and authorization to maintain the principles of least privilege and context of user entitlement.

Risk Management 92

Risk Management Risk Testing Digital Transformation 92

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.

Advertising 122

Advertising Cost-Benefit Experimentation Software 122

CIO Business Intelligence

MAY 15, 2024

And bad actors can download these models for free and run them in their own environments in order to test potential hacks. Europe’s AI Act will require some of this documentation, but most of its provisions won’t go into effect until 2026, she says. “I But that might not always be the case. Take bias, for example. “We

Modeling 136

Modeling Risk Software Enterprise 136

CIO Business Intelligence

APRIL 14, 2023

But it doesn’t always work, so don’t forget to test ChatGPT’s output before pasting it somewhere that matters.” Make it a living document – As with all policy documents, you’ll want to make this a living document and update it at a suitable cadence as your emerging use cases, external market conditions, and developments dictate.

Risk 122

Risk Experimentation Marketing Risk Management 122

CIO Business Intelligence

JUNE 8, 2023

These IT pros also have a hand in system testing, ensuring that the final product meets expectations, and analyze test results to identify issues or discrepancies. It’s a role that requires a wide set of technical skills, including knowledge of network design, implementation, maintenance, security, documentation, and monitoring.

IT 139

IT Digital Transformation Software Risk 139

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. The primary focus of model governance involves tracking, testing and auditing. How Model Governance Works.

Machine Learning 145

Machine Learning Modeling Testing Data Science 145

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 53

Insurance Digital Transformation Risk Management Interactive 53

DataRobot Blog

JULY 21, 2022

Document assumptions and risks to develop a risk management strategy. Define the exact calculation for the target variable or create a couple options to test. Test for bias to ensure fairness. Testing, monitoring, and mitigating bias helps ensure models align with company ethics and culture.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

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. It offers more control and flexibility for comprehensive testing and validation.

Cost-Benefit 74

Cost-Benefit Testing Strategy Risk Management 74

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]. Sensitivity analysis.

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Machine Learning Modeling Testing Risk Management 196

CIO Business Intelligence

JULY 25, 2024

The approach I would recommend is to begin by identifying and documenting all your business-critical operations. It’s at this stage that organizations can begin testing and identifying single points of failure in the process that may require further treatment or redundancy.

Risk 142

Risk Cost-Benefit Strategy Enterprise 142

CIO Business Intelligence

OCTOBER 2, 2024

Risk management Imagine if you had to evacuate a six-mile radius due to a toxic substance being released into the air from one of your plants, such as what happened in 2020 at a well-known company’s food plant in Camilla, GA. Innovation & product development. Human resources & talent acquisition.

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Gap analysis Risk Manufacturing Data Governance 119

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 55

Cost-Benefit Risk Management Risk Digital Transformation 55

Smart Data Collective

APRIL 22, 2020

The development team codes and builds the software by breaking it into different units that are tested individually. In the end, it is compiled and kept ready for testing as a whole. Testing: The most important stage of the development process is the testing stage. Engineering: Here the development and testing take place.

Data-driven 93

Data-driven Software Big Data Testing 93

IBM Big Data Hub

MAY 28, 2024

Data risk management To protect their data, organizations first need to know their risks. Data risk management involves conducting a full audit/risk assessment of an organization’s data to understand what types of data it has, where it’s stored and who has access to it.

Strategy 81

Strategy Measurement Risk Cost-Benefit 81

CIO Business Intelligence

MARCH 24, 2023

They must be accompanied by documentation to support compliance-based and operational auditing requirements. It must be clear to all participants and auditors how and when data-related decisions and controls were introduced into the processes. Data-related decisions, processes, and controls subject to data governance must be auditable.

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Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

OCTOBER 13, 2023

The role of algorithm engineer requires knowledge of programming languages, testing and debugging, documentation, and of course algorithm design. They help direct customers to the right associates, connect users with important documentation, and can alleviate some of the load on customer service representatives.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Cloudera

NOVEMBER 18, 2021

This allows for an omni-channel view of the customer and enables real-time data streaming and a safe zone to test machine learning models using Cloudera Data Science Workbench (CDSW). The variety of formats, unstructured nature, and dispersed location of these documents present several challenges for critical business decisions.

Data Lake 76

Data Lake Cost-Benefit Digital Transformation Risk 76

DataRobot

AUGUST 9, 2021

General Data Protection Regulation, California Consumer Privacy Act, SR 11-7 Guidance on Model Risk Management, etc). MLOps governance is a comprehensive AI audit solution for machine learning testing and governance. It empowers enterprises to measure, monitor, and manage AI-introduced risks at scale.

Machine Learning 52

Machine Learning Testing Risk Insurance 52

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

CIO Business Intelligence

APRIL 22, 2022

The exam covers topics including Scrum, Kanban, Lean, extreme programming (XP), and test-driven development (TDD). Candidates can also take a self-test to benchmark their knowledge. The exam covers project basics, project constraints, communication and change management, and project tools and documentation.

Management 111

Management Cost-Benefit Testing Risk 111

CIO Business Intelligence

JULY 25, 2024

Offered by the ISACA, the CRISC certification validates your ability to understand and mitigate enterprise IT risk using the latest best practices to identify, analyze, evaluate, assess, prioritize, and respond to risks. It covers Scrum, Kanban, Lean, extreme programming (XP), and test-driven development (TDD).

IT 130

IT Management Risk Risk Management 130

CIO Business Intelligence

JULY 31, 2023

As vendors add generative AI to their enterprise software offerings, and as employees test out the tech, CIOs must advise their colleagues on the pros and cons of gen AI’s use as well as the potential consequences of banning or limiting it. Douglas Merrill, a partner at management consulting firm McKinsey & Co.,

Strategy 98

Strategy Risk Enterprise Risk Management 98

IBM Big Data Hub

APRIL 4, 2024

Document-centric BPM is for efficiently managing documents and content—such as contracts—within processes. Also, BPM provides real-time insights into compliance metrics and risk exposure, enabling proactive risk management and regulatory reporting.

Management 54

Management Cost-Benefit Metrics Consulting 54

DataRobot

NOVEMBER 12, 2021

This may be an internal Model Risk Management or compliance team or even the individual consumer that must rationalize an algorithmic decision applied to them. Despite some of the hype around organizational data maturity, the time tested tenets of Total Quality Management (TQM) Systems hold true today.

Insurance 69

Insurance Risk Risk Management Manufacturing 69

IBM Big Data Hub

JANUARY 29, 2024

Business continuity and disaster recovery plans are risk management strategies that businesses rely on to prepare for unexpected incidents. This step must document expectations and consider how individuals will communicate during an unplanned incident. Here is a widely used four-step process for creating DRPs.

Cost-Benefit 84

Cost-Benefit Risk Enterprise Advertising 84

DataRobot

JULY 16, 2021

Testing your model to assess its reproducibility, stability, and robustness forms an essential part of its overall evaluation. Robust documentation throughout the end- to-end modeling workflow is one of the strongest enablers of compliance. All of these variables play a role in determining the prioritization of speed and accuracy.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

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

FineReport

FEBRUARY 17, 2021

Document all the resources: financial, personnel, and other resources required to reach project goals. Risk management. Here, project managers should summarize all predicted risks so that stakeholders can obtain a clear risk assessment and prepare plan B. Report any quality testing and any issues found.

Reporting 98

Reporting Management Dashboards Risk 98

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.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

DataRobot

SEPTEMBER 16, 2021

Pricing actuaries can test various advanced algorithms with minimal setup, including XGBoost, GBM, ENET, and GAM. No tools can eliminate the important work performed by pricing actuaries when it comes to explaining model results and preparing supporting documents for filing. Compliance documentation. Feature Impact.

Modeling 52

Modeling Insurance Cost-Benefit Machine Learning 52

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