Smart Data Collective

AUGUST 27, 2020

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. It’s difficult to mitigate supply chain risk in the best of times.

Risk Management 103

Risk Management Risk Management Software 103

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

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

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

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.

Risk 115

Risk Risk Management Strategy Enterprise 115

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

IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 77

Risk Modeling Management Metadata 77

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.

Risk Management 52

Risk Management Risk Enterprise Management 52

CIO Business Intelligence

MARCH 18, 2024

There are a lot of risks and a lot of land mines to navigate,” says the analyst. Coming to grips with risk The first step in making any bet — or investment — is to understand your ability to withstand risk. We have been developing our own internal AI capability over the last few years using open-source models.

Risk 133

Risk Cost-Benefit Data Processing Testing 133

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.

Risk Management 128

Risk Management Risk Enterprise Management 128

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.

Risk 59

Risk Modeling Metrics Measurement 59

Cloudera

OCTOBER 20, 2021

As part of these efforts, disclosure requirements will mandate that firms provide “the impact of a company’s activities on the environment and society, as well as the business and financial risks faced by a company due to its sustainability exposures.” What are the key climate risk measurements and impacts? They need to understand;

Risk 78

Risk Modeling Risk Management Measurement 78

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.

Risk Management 92

Risk Management Risk Management Metrics 92

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

Risk Modeling Metrics Business Objectives 52

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.

Risk Management 72

Risk Management Risk Modeling Management 72

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

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.

Machine Learning 220

Machine Learning Risk Management Statistics 220

Domino Data Lab

AUGUST 6, 2021

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Risk Management 64

Risk Management Risk Enterprise Modeling 64

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. .

Risk 96

Risk Optimization Management Insurance 96

DataRobot

OCTOBER 22, 2021

Their increased usage has also led to new challenges related to compliance, misuse, and fraud risk. This can be accomplished by providing stronger accountability, increased productivity, and transparency into spending and risk management. Additionally, more than 1000 hours can be saved on risk transaction reviews each year.

Risk 98

Risk Risk Management Data-driven Management 98

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]

Machine Learning 192

Machine Learning Modeling Testing Risk Management 192

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 95

Modeling Risk Management Internet of Things Risk 95

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

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

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

Teradata

JANUARY 27, 2022

The prevalence of new business models, emerging global risks & modernization of data processing in the cloud is ushering in a new era for credit risk management & the transformation of risk analytics.

Risk 52

Risk Risk Management Data Processing Modeling 52

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

John Wheeler

OCTOBER 21, 2019

Over the past month, I’ve been speaking to various groups to help them prepare for the onslaught of digital risks in their organizations. A common theme is the need for greater risk quantification beyond the realm of traditional, qualitative governance, risk and compliance (GRC) approaches.

Risk 53

Risk Risk Management Digital Transformation Insurance 53

Dataiku

DECEMBER 28, 2021

However, the use of AI, like any other technology, comes with a certain amount of risk. Effectively implemented oversight, management, and clear, value-driven organizational priorities are therefore crucial for safe scaling.

Risk 59

Risk Risk Management Data-driven Modeling 59

IBM Big Data Hub

APRIL 19, 2024

Asset management and technological innovation Advancements in technology underpin the need for holistic grid asset management, making the assets in the grid smarter and equipping the workforce with smart tools. Cybersecurity reduces risk exposure for cyberattacks on digitally connected assets.

Management 94

Management Internet of Things Risk IoT 94

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

IBM Big Data Hub

MAY 1, 2024

From demand forecasting to route optimization, inventory management and risk mitigation, the applications of generative AI are limitless. Inventory management Generative AI models can continuously generate optimized replenishment plans based on real-time demand signals, supplier lead times and inventory levels.

Forecasting 62

Forecasting Optimization Digital Transformation Risk 62

Cloudera

MARCH 28, 2019

The trouble is, mortgage lenders persist in relying on historical macro-economic assumptions in their models so they risk repeating the errors of a decade ago when banks – and their regulators – failed to recognize the warning signs from a far richer source: low-level micro-economic data. Risk management 3.0.

Risk 72

Risk Management Risk Management Machine Learning 72

CIO Business Intelligence

APRIL 5, 2024

Senate Bill 1047 , introduced in the California State Legislature in February, would require safety testing of AI products before they’re released, and would require AI developers to prevent others from creating derivative models of their products that are used to cause critical harms.

Risk 132

Risk Interactive Insurance Strategy 132

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

It helps reduce risk, increase efficiency, optimize resources, and improve both the customer and employee experience. When asked what keeps them up at night, IT leaders noted the need to improve overall IT performance (60%), followed by data security (50%), process risk and compliance (46%), and the need to improve agility (41%).

IT 98

IT Risk Management Risk Optimization 98

CIO Business Intelligence

NOVEMBER 21, 2023

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT.

IT 137

IT Risk Cost-Benefit Risk Management 137