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

CIO Business Intelligence

DECEMBER 14, 2023

AI and machine learning (ML) can do this by automating the design cycle to improve efficiency and output; AI can analyze previous designs, generate novel design ideas, and test prototypes, assisting engineers with rapid, agile design practices. Generative AI can help mitigate these often serious risks.

Manufacturing 143

Manufacturing Cost-Benefit Unstructured Data Optimization 143

CIO Business Intelligence

OCTOBER 13, 2023

Machine learning engineer Machine learning engineers are tasked with transforming business needs into clearly scoped machine learning projects, along with guiding the design and implementation of machine learning solutions.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Cloudera

FEBRUARY 4, 2021

Cloudera comprehensively supports the demanding risk and compliance requirements of financial services and insurance organizations globally and it is an honor to receive this recognition. Supporting the industry’s risk data depository and data management needs. Risk management and models in a COVID-19 world.

Risk 90

Risk Marketing Technology Management 90

CIO Business Intelligence

OCTOBER 4, 2023

There’s also strong demand for non-certified security skills, with DevSecOps, security architecture and models, security testing, and threat detection/modelling/management attracting the highest pay premiums. AI skills more valuable than certifications There were a couple of stand-outs among those.

Prescriptive Analytics 135

Prescriptive Analytics IT Machine Learning Risk 135

CIO Business Intelligence

AUGUST 23, 2023

Because of quantum’s abilities the Ally team could create 50 separate scenarios and back-test the models. But quantum also holds the promise to make machine learning more efficient as well, says Vishal Shete, managing director UK and head of commercialization at Terra Quantum AG.

IT 97

IT Machine Learning Risk Optimization 97

O'Reilly on Data

JULY 15, 2019

As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. What cultural and organizational changes will be needed to accommodate the rise of machine and learning and AI?

Machine Learning 37

Machine Learning Management Enterprise Risk Management 37

CIO Business Intelligence

OCTOBER 3, 2023

However since then great strides have been made in machine learning and artificial intelligence. Mordor Intelligence sees the increasing incorporation of machine learning tools into hyperautomation products as being one of the main drivers of market growth. It’s been around since the early 2000s. This is hyperautomation.

Cost-Benefit 120

Cost-Benefit Machine Learning Interactive Software 120

IBM Big Data Hub

FEBRUARY 13, 2024

Like diligent students, these generative models soak up information and identify patterns, structures and relationships between data points, which is how they learn the grammar of poetry, artistic brushstrokes and musical melodies. Imagine each data point as a glowing orb placed on a vast, multi-dimensional landscape.

Enterprise 118

Enterprise Modeling Testing Data-driven 118

Smart Data Collective

OCTOBER 13, 2021

It also allows companies to experiment with new concepts and ideas in different ways without relying only on lab tests. Choose the right artificial intelligence tools such as System Innovation to help you manage innovation and confront the challenges of technological advancements. Use machine learning.

Technology 120

Technology Cost-Benefit Experimentation Machine Learning 120

DataRobot

AUGUST 9, 2021

Across the globe, governments and enterprises have put in place regulatory requirements, standards, certifications, and audits to oversee machine learning and AI applications, especially with autonomous decision-making systems (e.g., AI governance and auditability will affect all sectors that utilize machine learning.

Machine Learning 52

Machine Learning Risk Testing Insurance 52

Cloudera

JULY 15, 2021

For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. . Attendees included senior risk managers and analytics experts from financial institutions and insurance companies.

Risk 102

Risk Optimization Management Insurance 102

CIO Business Intelligence

MARCH 13, 2024

L’analisi dei dati attraverso l’apprendimento automatico (machine learning, deep learning, reti neurali) è la tecnologia maggiormente utilizzata dalle grandi imprese che utilizzano l’IA (51,9%). Le reti neurali sono il modello di machine learning più utilizzato oggi.

Machine Learning 104

Machine Learning Deep Learning Big Data Testing 104

IBM Big Data Hub

JANUARY 30, 2024

Finance: Optimized for high-speed transactions and can assist in providing robust security, harnessing AI for fraud detection and real-time risk management. Retail: Manage e-commerce platforms, customer data analytics and supply chain logistics, where data analysis often must occur at the edge.

Manufacturing 72

Manufacturing Business Objectives Optimization Risk Management 72

Cloudera

FEBRUARY 24, 2021

Trend #1: The Crossroads of Risk Management and Emerging Technology. One shift the financial services industry will have to come to terms with is the fact that 2020 may have made risk management models of the past outdated or obsolete , particularly credit risk models.

Risk Management 61

Risk Management Risk Recreation/Entertainment Machine Learning 61

CIO Business Intelligence

OCTOBER 20, 2023

The vendor-neutral certification covers topics such as organizational structure, security and risk management, asset security, security operations, identity and access management (IAM), security assessment and testing, and security architecture and engineering.

IT 137

IT Consulting Testing IoT 137

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. In performance, the trust dimensions are the following: Data quality — the performance of any machine learning model is intimately tied to the data it was trained on and validated against. Dimensions of Trust. Operations.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

Smart Data Collective

APRIL 21, 2022

Due to the growing importance of AI , many companies are using application that can utilize sophisticated machine learning algorithms. Tracking work progress becomes much easier with new management software technologies. Application development consulting services are a newer service.

Consulting 95

Consulting Cost-Benefit Software Machine Learning 95

Smart Data Collective

APRIL 22, 2020

They use unique machine learning tools and big data platforms to streamline the process as much as possible. 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.

Data-driven 91

Data-driven Software Big Data Testing 91

Smart Data Collective

OCTOBER 26, 2023

Machine learning algorithms can adapt and improve over time, enabling them to recognize new, previously unseen attack patterns. Cybersecurity professionals often perform penetration testing and vulnerability assessments to identify security flaws in systems and networks.

Technology 91

Technology Risk Measurement IoT 91

DataRobot Blog

MAY 26, 2022

Validating Modern Machine Learning (ML) Methods Prior to Productionization. Validating Machine Learning Models. This may be accomplished through a wide variety of tests, to develop a deeper introspection into how the model behaves.

Risk 52

Risk Modeling Metrics Business Objectives 52

DataRobot Blog

JULY 21, 2022

Download the Machine Learning Project Checklist. Planning Machine Learning Projects. Machine learning and AI empower organizations to analyze data, discover insights, and drive decision making from troves of data. More organizations are investing in machine learning than ever before.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

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

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

Cloudera

AUGUST 25, 2020

Richard Harmon, Managing Director of Financial Services at Cloudera, to find out more about how the industry is adopting new technology. Thank you for joining us for part two of our discussion around data, analytics and machine learning within the Financial Service Sector Dr. Harmon.

Prescriptive Analytics 74

Prescriptive Analytics Technology Machine Learning Risk 74

IBM Big Data Hub

SEPTEMBER 20, 2022

Organizations are increasingly depending upon artificial intelligence (AI) and Machine Learning (ML) to assist humans in decision making. Consider these three crucial steps in the lifecycle of building out your next AI or machine learning model or improving a current one. Comprehensive, trusted data sets.

Metadata 56

Metadata Machine Learning Data-driven Modeling 56

Cloudera

MARCH 28, 2019

For all the advances in big data, machine learning and computational simulation in the decade since the global financial crisis, incumbent banks, still preoccupied with the twin imperatives of ever-tougher regulatory compliance and boosting shareholder returns, are playing catch-up in their adoption of new technologies.

Risk 75

Risk Management Risk Management Machine Learning 75

CIO Business Intelligence

JULY 18, 2023

With the entry of ChatGPT and other generative AI, we expect the demand for data science, AI, and machine learning to further surge in the coming time,” says Aamir Khan, senior analyst at Everest Group. We have learned to think and act quickly in our efforts to attract and retain top talent in these areas,” says Jeanine L.

IT 98

IT Data Science IoT Digital Transformation 98

O'Reilly on Data

MAY 18, 2020

And last is the probabilistic nature of statistics and machine learning (ML). Most AI models decay overtime: This phenomenon, known more widely as model decay , refers to the declining quality of AI system results over time, as patterns in new data drift away from patterns learned in training data. How Material Is the Threat?

Risk 359

Risk Modeling Data Processing Software 359

Cloudera

MAY 15, 2018

Cloudera Enterprise is the market leader in this space and working closely with the wider open source community to integrate the latest innovations in machine learning and artificial intelligence (AI). They can consist of simple rules, machine learning derived models or even AI-based models such as reinforcement learning models.

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

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

CIO Business Intelligence

MARCH 24, 2023

Varonis Data Governance Suite Varonis’s solution automates data protection and management tasks leveraging a scalable Metadata Framework that enables organizations to manage data access, view audit trails of every file and email event, identify data ownership across different business units, and find and classify sensitive data and documents.

Data Governance 142

Data Governance Management Metadata Data Quality 142

FineReport

MARCH 24, 2024

Jupyter Notebooks: Simplifies code testing and collaboration for data analysis tasks. Columbia University Certification of Professional Achievement in Data Sciences , offering foundational skills in algorithms, probability, statistics, machine learning, and exploratory data analysis. JPMorgan Chase & Co.:

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

MAY 20, 2024

Artificial intelligence and machine learning Unsurprisingly, AI and machine learning top the list of initiatives CIOs expect their involvement to increase in the coming year, with 80% of respondents to the State of the CIO survey saying so. Risk management came in at No. Foundry / CIO.com 3. For Rev.io

IT 142

IT Risk Management Machine Learning Risk 142

Cloudera

APRIL 18, 2024

In the financial sector, regulations are essential for financial institutions to maintain stability by preventing excessive risk-taking, ensuring adequate capitalization and reducing the likelihood of failures or financial crises.

Risk Management 79

Risk Management Risk Testing Management 79

Domino Data Lab

APRIL 3, 2019

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations. for DG adoption in the enterprise.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

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 88

Data Architecture Risk Management Risk Management 88