Smart Data Collective

AUGUST 27, 2020

One of the areas where cloud technology has had a large impact is with supply chain management. It’s important to know how to protect your own firm from spend risk, supply chain disruption while enhancing the company’s ability to thrive. Moving your supply chain model to the cloud could be one of the best ways to reduce these concerns.

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Risk Management Risk Management Software 105

John Wheeler

NOVEMBER 24, 2020

However, for security and risk management professionals it can make a huge difference. Take for example the terms cyber risk, digital risk and the digitalization of risk management. Viewed together, the three terms represent key aspects of integrated risk management (IRM).

Risk Management 85

Risk Management Risk Management Technology 85

IBM Big Data Hub

MAY 4, 2020

Many financial firms are increasing their use of AI models because they can represent the real world more accurately, and they can deliver better projections than traditional, rule-based models. But some AI models can add complexity and risk.

Risk Management 85

Risk Management Risk Modeling Management 85

IBM Big Data Hub

APRIL 19, 2024

This blog series discusses the complex tasks energy utility companies face as they shift to holistic grid asset management to manage through the energy transition. Asset performance management (APM) processes, such as risk-based and predictive maintenance and asset investment planning (AIP), enable health monitoring technologies.

Management 91

Management Internet of Things Risk IoT 91

Domino Data Lab

JULY 14, 2022

The financial services industries are starting to realize the full import of the fact that, like household chores like dishwashing and garden work, ML models are never really done. Rather, AI and ML models need to be monitored for validity, and often, they also need to be re-explained and re-documented for regulators.

Insurance 98

Insurance Modeling Management Risk Management 98

bridgei2i

SEPTEMBER 24, 2020

However, risk management is no way lagging. ERM or Enterprise Risk Management is being used to identify crises long before it blows up into a huge problem. AI is being used to assess, prioritize, and mitigate risks in the enterprise so that the business operations do not take a hit. Risk Management Model.

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IBM Big Data Hub

OCTOBER 16, 2023

AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models can use language, vision and more to affect the real world.

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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. Now, the first of those areas is definitely risk and portfolio management.

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bridgei2i

NOVEMBER 20, 2020

Episode 2: AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. Today the Chief Risk Officers(CROs) struggle with the critical task of monitoring and assessing key risks in real time and firefight to mitigate any critical issues that arise.

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DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. What is a model?

Risk 111

Risk Modeling IT Risk Management 111

IBM Big Data Hub

MARCH 3, 2020

Many financial institutions are rapidly developing and adopting AI models. They’re using the models to achieve new competitive advantages such as being able to make faster and more successful underwriting decisions. However, AI models introduce new risks.

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Domino Data Lab

AUGUST 6, 2021

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IBM Big Data Hub

JANUARY 28, 2020

Any financial services firm using AI must revisit its approach to model risk management. The reason is that AI models are evolving faster than the rules-based models that were standard previously. If AI models perform inadequately, major operational losses can grow quickly.

Risk 84

Risk Modeling Big Data Management 84

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]

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DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States.

Risk 64

Risk Modeling Machine Learning Data Quality 64

Dataiku

SEPTEMBER 8, 2021

This article presents how financial modeling can be done inside Dataiku. Let’s begin with the context: spreadsheet-based tools like Microsoft Excel are some of the most popular tools for financial modeling and are used for all kinds of tasks including investment analysis, P&L modeling, and risk management.

Modeling 105

Modeling Risk Management Risk Management 105

O'Reilly on Data

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. Before I continue, it’s important to emphasize that machine learning is much more than building models. Model lifecycle management.

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Machine Learning Risk Management Statistics 220

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

CIO Business Intelligence

MARCH 8, 2023

As organizations shape the contours of a secure edge-to-cloud strategy, it’s important to align with partners that prioritize both cybersecurity and risk management, with clear boundaries of shared responsibility. The security-shared-responsibility model provides a clear definition of the roles and responsibilities for security.”

Modeling 76

Modeling Risk Management Internet of Things Risk 76

Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. 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. .

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Risk Optimization Management Insurance 96

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.”

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IBM Big Data Hub

MAY 1, 2024

Unlocking the full potential of supply chain management has long been a goal for businesses that seek efficiency, resilience and sustainability. From demand forecasting to route optimization, inventory management and risk mitigation, the applications of generative AI are limitless.

Forecasting 77

Forecasting Optimization Digital Transformation Risk 77

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.

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Risk Modeling Metrics Measurement 59

Cloudera

OCTOBER 20, 2021

As governments gather to push forward climate and renewable energy initiatives aligned with the Paris Agreement and the UN Framework Convention on Climate Change, financial institutions and asset managers will monitor the event with keen interest. Transition : the changes in asset values, business models, etc. (ex. Assess Variables.

Risk 78

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Cloudera

FEBRUARY 4, 2021

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. Cloudera is that platform.

Risk 86

Risk Marketing Technology Management 86

erwin

JULY 12, 2019

In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. Creating and automating a curated enterprise data catalog , complete with physical assets, data models, data movement, data quality and on-demand lineage. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

John Wheeler

MARCH 5, 2021

Now that we are recovering from the COVID-19 pandemic crisis, our clients are now looking forward to deploy new ways of managing risk. They can no longer look to the past as an exclusive indicator of what risks may lie ahead. Simply put, business leaders need a better way to manage risks.

Risk Management 105

Risk Management Risk Technology Management 105

DataRobot Blog

MAY 26, 2022

Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. In summary, to ensure that they have built a robust model, modelers must make certain that they have designed the model in a way that is backed by research and industry-adopted practices.

Risk 52

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CIO Business Intelligence

DECEMBER 28, 2023

The need to manage risk, adhere to regulations, and establish processes to govern those tasks has been part of running an organization as long as there have been businesses to run. Furthermore, the State of Risk & Compliance Report, from GRC software maker NAVEX, found that 20% described their programs as early stage.

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Smart Data Collective

JUNE 3, 2021

Analytics is particularly important for developing strategic financial management policies. Strategic Financial Management or strategic finance is a process to help a company’s finances. I will detail the role of analytics in strategic financial management and how mosaic finance can help you throughout the process!

Management 91

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Smart Data Collective

JULY 16, 2023

The Imperative of Risk Mitigation A crucial element in the world of financial investments is effective hedge fund management. Optimizing hedge fund performance requires the implementation of intelligent strategies, from managing risks to maximizing returns, improving investor relations, and adapting to shifting market conditions.

ROI 71

ROI Data Analytics Analytics Risk Management 71

AWS Big Data

MARCH 27, 2023

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. You can define your own key and value for your resource tag, so that you can easily manage and filter your resources. Tags allows you to assign metadata to your AWS resources. View and edit tags.

Data Warehouse 81

Data Warehouse Management Snapshot Data Lake 81

Decision Management Solutions

APRIL 23, 2019

, in which he states there are only three levers of value in insurance: Sell More, Manage Risk Better (aka underwriting and adjusting), and Cost Less to Operate. Let’s dive into greater detail on the second lever – Manage Risk Better. Insurers can also manage risk more effectively through continuous improvement.

Insurance 69

Insurance Risk Technology Management 69

CIO Business Intelligence

JUNE 23, 2023

Other focus areas include data and content management (60%), DevOps (58%), infrastructure and application modernization (58%), automation (57%), and enterprise storage (35%). Risk Management: Risk management is a critical focus for technology professionals.

IT 97

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DataRobot Blog

DECEMBER 6, 2022

Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results. Taking a Multi-Tiered Approach to Model Risk Management. How Model Observability Provides a 360° View of Models in Production. Read the blog. Read the blog.

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IBM Big Data Hub

FEBRUARY 13, 2024

This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Generative adversarial networks (GANs) or variational autoencoders (VAEs) are used for images, videos, 3D models and music. Autoregressive models or large language models (LLMs) are used for text and language.

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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. CIOs should look for other operational and risk management practices to complement transformation programs.

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