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 82

Cost-Benefit Testing Strategy Risk Management 82

CIO Business Intelligence

MARCH 13, 2024

We did side-by-side testing,” he says. AI models are able to present best practice code systems to help junior developers learn and hone their skills.” In testing, gen AI was also particularly good at generating test cases and creating dummy data for testing. What if writing code wasn’t the real issue?”

IT 128

IT Consulting Testing Cost-Benefit 128

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

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 139

IT Digital Transformation Software Risk 139

DataRobot

AUGUST 9, 2021

However, many organizations don’t implement any feedback loop to monitor and control their models after they’re out in production. General Data Protection Regulation, California Consumer Privacy Act, SR 11-7 Guidance on Model Risk Management, etc).

Machine Learning 52

Machine Learning Risk Testing Insurance 52

Decision Management Solutions

APRIL 23, 2019

Predictive analytics streamlines the decision to maximize efficiency and accuracy, enabling carriers to be smarter about risk while automating more decisions. Predictive analytic models can also address complex interrelationships between data elements that contribute to risk and may be too subtle to be recognized by an underwriter.

Insurance 69

Insurance Risk Technology Management 69

CIO Business Intelligence

APRIL 27, 2023

They’re required to work closely with upper management, executives, and key stakeholders to identify business needs and requirements. Relevant skills for a systems architect include risk management, performance optimization, security, leadership, and a strong knowledge of complex computer systems.

IT 116

IT Software Risk Management 116

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

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. The algorithms can detect anomalies in the transactional data and helps to identify high-risk customers and transactions that may be linked to money laundering activities.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

CDW Research Hub

JUNE 10, 2021

These allow us to take a vendor-neutral stance to help clients consider, compare, test and select the right solution for their environment, requirements and desired business outcomes. Advancing your security posture requires effectively managing these common challenges: Shifting compliance and threat landscape. Discovery Workshops.

Enterprise 52

Enterprise Consulting Risk Business Objectives 52

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. The algorithms can detect anomalies in the transactional data and helps to identify high-risk customers and transactions that may be linked to money laundering activities. These include-.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

CIO Business Intelligence

SEPTEMBER 2, 2022

Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications. Part of the role also includes continually improving the organization’s technology stack, while maintaining a priority for business continuity and risk management.

Finance 98

Finance IT Software Reporting 98

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

CIO Business Intelligence

AUGUST 31, 2022

Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications. Part of the role also includes continually improving the organization’s technology stack, while maintaining a priority for business continuity and risk management.

Finance 98

Finance IT Software Reporting 98

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

DataRobot Blog

JULY 22, 2022

Using AI-based models increases your organization’s revenue, improves operational efficiency, and enhances client relationships. You need to know where your deployed models are, what they do, the data they use, the results they produce, and who relies upon their results. That requires a good model governance framework.

Modeling 105

Modeling Risk Management Testing Risk 105

O'Reilly on Data

JULY 15, 2019

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Note that the emphasis of SR 11-7 is on risk management.).

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

IBM Big Data Hub

JULY 12, 2023

Team members discuss possible risks, analyze the risk impact of each one and propose courses of action to increase their overall preparedness. Plans should be tested at least once annually, and new risk assessments performed. RTO is usually measured with a simple time metric, such as days, hours or minutes.

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. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 84

Data Architecture Risk Management Risk Management 84

DataRobot Blog

JULY 21, 2022

Outline clear metrics to measure success. Document assumptions and risks to develop a risk management strategy. Machine learning models created in silos are rarely implemented. Models could also be deployed into multiple environments at once. Decide who owns monitoring and who owns model redevelopment.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

DataRobot

SEPTEMBER 16, 2021

The later introduction of Generalized Linear Models (GLM) significantly expanded the pricing actuary’s toolbox. When it comes to insurance and loss cost modeling, DataRobot enforces best practices by automating model setup and incorporating various preprocessing and modeling approaches. Claim Count.

Modeling 52

Modeling Insurance Cost-Benefit Machine Learning 52

Cloudera

SEPTEMBER 7, 2023

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. But these measures alone may not be sufficient to protect proprietary information.

Insurance 81

Insurance Risk Data-driven Finance 81

Domino Data Lab

APRIL 3, 2019

Instead, we must build robust ML models which take into account inherent limitations in our data and embrace the responsibility for the outcomes. Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for There are models everywhere. In other words, #adulting.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

FEBRUARY 22, 2024

Earning trust in the outputs of AI models is a sociotechnical challenge that requires a sociotechnical solution. But it’s equally important that they have a deep understanding of the risks and limitations of AI and how to implement the appropriate security measures and ethics guardrails. The CRISP-DM model is useful here.

Metadata 103

Metadata Measurement Risk Modeling 103

CIO Business Intelligence

MAY 13, 2024

But where the puck is moving to is really around business use cases and identifying use cases where they will see value from their AI investments,” says Dera Nevin, a data lawyer, information risk management expert, and managing director in the technology segment at FTI Consulting. Such expectations fit squarely with the No.

IT 123

IT Digital Transformation ROI Strategy 123

Cloudera

MARCH 18, 2021

The Fundamental Review of the Trading Book (FRTB), introduced by the Basel Committee on Banking Supervision (BCBS), will transform how banks measure risk. In order to help make banks more resilient to drastic market changes, it will impose capital requirements that are more closely aligned with the market’s actual risk factors.

Risk 55

Risk Machine Learning Risk Management Measurement 55

Cloudera

MAY 18, 2021

In this article, we will be using synthetic market data generated by an agent-based model (ABM) developed by Simudyne. Rather than a top-down approach, ABMs model autonomous actors (or agents) within a complex system — for example, different kinds of buyers and sellers in financial markets. Intraday VaR. Image Source: [link].

Risk 97

Risk Marketing Risk Management Data-driven 97

O'Reilly on Data

OCTOBER 18, 2022

What if a named entity recognition (NER) system, based on a cutting-edge large language model (LLM), fails for Chinese, Cyrillic, or Arabic text? 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. For our audits, BNH.AI

Risk Management 291

Risk Management Risk Testing Measurement 291

CIO Business Intelligence

APRIL 22, 2022

The exam covers topics including Scrum, Kanban, Lean, extreme programming (XP), and test-driven development (TDD). It’s designed for those who aspire to have a career in project management and doesn’t require prior experience in the field. Candidates can also take a self-test to benchmark their knowledge.

Management 111

Management Cost-Benefit Testing Risk 111

IBM Big Data Hub

JULY 28, 2023

In response, enterprises have made vulnerability management a key component of their cyber risk management strategies. The vulnerability management lifecycle offers a formal model for effective vulnerability management programs in an ever-changing cyberthreat landscape.

Management 70

Management Metrics Risk Measurement 70

Insight

FEBRUARY 19, 2020

My goal here is not to improve upon the current prediction algorithms but rather to describe a model I devised, called ReelRisk , that uses random resampling to generate a range of predictions which can then be used as a risk assessment tool to determine early on whether to fund a movie.

Risk 67

Risk ROI Modeling Metrics 67

IBM Big Data Hub

JANUARY 30, 2024

To overcome various challenges associated with multicloud , organizations need to map out a comprehensive multicloud management strategy to achieve overall success. A multicloud is a cloud computing model that incorporates multiple cloud services from more than one of the major cloud service providers (CSPs)—e.g.,

Strategy 102

Strategy Cost-Benefit Risk Optimization 102

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

CIO Business Intelligence

MARCH 25, 2022

Policy makers around the world have been recognizing this heightened risk, which has been further amplified by the recent geopolitical tensions. The European Union (EU) has pulled together a proposal for a unified framework to regulate risk management for financial institutions. Cybersecurity threats are real.

Finance 93

Finance KPI Risk IoT 93

Grooper

OCTOBER 23, 2019

With the increasing value of data and more tools to process and analyze information than ever before, companies with information governance and master data model programs are outpacing their peers. By measuring performance, they drive improvements through necessary process and workflow changes. How does data benefit the entire company?

Metrics 59

Metrics Measurement Strategy Optimization 59

datapine

AUGUST 29, 2022

are using big data to their advantage, including: Progressive Insurance’s use of GPS trackers/accelerometers which determine customer safety ratings Google’s ability to predict local flu outbreaks by measuring spikes in flu-related local searches The government of Boston fixing potholes using data that residents enter into their smartphones.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

AWS Big Data

AUGUST 14, 2023

Taken together, the posts in this series lay out some possible operating models for data mesh within an organization. How do we define “risk” and “value” in the context of data products, and how can we measure this? Strategies for measuring value and prioritizing data products are explored later in this post.

Management 79

Management Risk Measurement Optimization 79