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With a goal to help data science teams learn about the application of AI and ML, DataRobot shares helpful, educational blogs based on work with the world’s most strategic companies. Explore these 10 popular blogs that help data scientists drive better data decisions. Taking a Multi-Tiered Approach to Model RiskManagement.
Unified endpoint management (UEM) and medical device riskmanagement concepts go side-by-side to create a robust cybersecurity posture that streamlines device management and ensures the safety and reliability of medical devices used by doctors and nurses at their everyday jobs.
Environmental, Social, and Governance (ESG) riskmanagement has emerged as a critical aspect of business strategy for companies worldwide. Focusing on ESG RiskManagement can help your organization become more profitable, and your organization can start on this journey today.
This week, we kicked-off a major research effort to explore current innovations in the rapidly expanding integrated riskmanagement (IRM) market. This represents a great opportunity for organizations to utilize riskmanagement technology (RiskTech) to bridge the gap between these seemingly disconnected transformation efforts.
Alation joined with Ortecha , a data management consultancy, to publish a white paper providing insights and guidance to stakeholders and decision-makers charged with implementing or modernising data riskmanagement functions. The Increasing Focus On Data RiskManagement. Download the complete white paper now.
Riskmanagement is trending through the roof here at Gartner as we strive to help our clients emerge from the COVID-19 crisis. What’s also trending is the readership of my RiskTech blog posts. What’s So Cool About RiskManagement? What’s So Cool About RiskManagement?
Model RiskManagement 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 RiskManagement.
However, riskmanagement is no way lagging. ERM or Enterprise RiskManagement 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. RiskManagement Model.
As the recovery efforts fully take hold in 2021, a deep understanding of the integrated nature of risks associated with business operations will take center stage. Those businesses that employ a “PRACtical” approach utilizing integrated riskmanagement (IRM) will be in the best position to recover quicker and more successfully.
Last week, I had the distinct privilege to join my Gartner colleagues from our RiskManagement Leadership Council in presenting the Q4 2018 Emerging Risk Report. We hosted more than 500 risk leaders across the globe in our exploration of the most critical risks.
As businesses adapt to the pandemic and shift to new norms, risk mitigation strategies have become as normal and ubiquitous as having a fire escape in the office. Smarter, AI-driven learning and development initiatives will help mitigate risk in our rapidly evolving world. Minimising risk by ‘infusing’ AI.
Integrated riskmanagement (IRM) technology is uniquely suited to address the myriad of risks arising from the current crisis and future COVID-19 recovery. IRM technology product leaders will need to develop IRM capabilities that are capable of addressing the IRM market insights outlined in this blog post. Key Findings.
What’s your AI risk mitigation plan? Just as you wouldn’t set off on a journey without checking the roads, knowing your route, and preparing for possible delays or mishaps, you need a model riskmanagement plan in place for your machine learning projects. Enterprise Ready AI: Managing Governance and Risk.
As a result, third-party riskmanagement (TPRM) has become a crucial aspect of enterprise riskmanagement. These steps can help reduce the risks of data breaches. This blog post delves into the various elements of vendor security and discusses best practices to maintain robust security in vendor relationships.
Gartner clients are consistently searching for ways to improve their riskmanagement programs to deliver greater value to the enterprise. That’s why Gartner has been promoting integrated riskmanagement (IRM) solutions for the past 4 years. Competitive Landscape: Integrated RiskManagement Solutions.
Whether implemented as preventative measures (riskmanagement and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. With that in mind, we’ve compiled a list of the very best, best-practice blog posts from the erwin Experts in 2018.
In my previous blog post, I shared examples of how data provides the foundation for a modern organization to understand and exceed customers’ expectations. RiskManagement. A 2019 HBR article mentioned how organizational decisions backed by data have instilled more confidence and reduced risk. Conclusion.
Riskmanagement and real-time fraud analysis for IT and finance teams. The post Cloudera acquires Eventador to accelerate Stream Processing in Public & Hybrid Clouds appeared first on Cloudera Blog. Personalized promotions and customer 360 use cases for sales and marketing teams.
This all-round view, which has been christened IBM Concert 360 view, contains a single unified view of an enterprise’s applications along with their dependencies, information about risks around applications, and a view of common flows between applications.
Improved riskmanagement: Another great benefit from implementing a strategy for BI is riskmanagement. However, it is possible to identify some potential drawbacks and apply riskmanagement practices in advance. Pursue a phased approach. Rome wasn’t built in a day: neither will your BI.
While we are proud to build and release models that are industry-leading on both capabilities and safety, we welcome a robust debate at this important moment,” it said in the blog post. Therefore, it is essential to integrate security measures, riskmanagement, and ethical considerations from the design stage, rather than as an afterthought.”
In part one of our “Five Ways AI Can Help States Solve Their Hardest Problems” blog series, we reviewed the ramifications of crisis response management—or lack thereof—and how AI can help. This can be accomplished by providing stronger accountability, increased productivity, and transparency into spending and riskmanagement.
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.
1] Managing complex business operations across a hybrid multicloud environment presents leaders with unique challenges, not least of which are cyberthreats that can bring essential business functions to a halt—potentially for days, weeks or months. And they do so at scale across hybrid cloud and on-premises infrastructure.
In this blog post, we explore three types of errors inherent in all financial models, with a simple example of a model in TensorFlow Probability (TFP). We thank the TensorFlow Probability team, especially Mike Shwe and Josh Dillon, for their help in earlier drafts of this blog post. Finance is not physics. References. Thompson, L.S.
At many organizations, the current framework focuses on the validation and testing of new models, but riskmanagers and regulators are coming to realize that what happens after model deployment is at least as important. Now is the time to address the gaps in your organization’s model management by adopting a robust new system.
This blog post will provide an in-depth exploration of these strategies, equipping fund managers with the knowledge to boost their fund performance and investor confidence. We will talk about some of the biggest ways that big data is changing the future of riskmanagement among hedge funds.
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. Riskmanagement and models in a COVID-19 world.
This week, Gartner hosted its annual Security & RiskManagement Summit in London and the buzz at the event centered on the new risks associated with the General Data Protection Regulation (GDPR). It’s no wonder that CEOs consider riskmanagement as one of their top priorities in 2018 (see figure below).
Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs. However, because most institutions lack a modern data architecture , they struggle to manage, integrate and analyze financial data at pace.
Credit risk may result in everything from late payment penalties to huge financial losses, especially if the borrower fails on a considerable sum or if a large number of borrowers default at the same time. The World Bank Blog has an entire post dedicated to this topic. Big data technology is making these processes easier than ever.
Last week, I attended the annual Gartner® Security and RiskManagement Summit. The event gave Chief Information Security Officers (CISOs) and other security professionals the opportunity to share concerns and insights about today’s most pressing issues in cybersecurity and riskmanagement. See you there.
In this context, Cloudera and TAI Solutions have partnered to help financial services customers accelerate their data-driven transformation, improve customer centricity, ensure compliance with regulations, enhance riskmanagement, and drive innovation.
With more detailed information about each transaction, analysts can develop deeper insights, which can help to improve riskmanagement, fraud detection and compliance with regulatory requirements. Enhanced RiskManagement: better identify and managerisks, such as fraud, credit risk and operational risk.
At both gatherings, participants emphasized the importance of effective governance and riskmanagement. Current risk mitigation strategies (including having human-in-system roles and robust training data) are not necessarily enough. What’s next? Learn more about how watsonx can help usher in governments into the future.
RiskManagement and Regulatory Compliance. Riskmanagement, specifically around regulatory compliance, is an important use case to demonstrate the true value of data governance. According to Pörschmann, riskmanagement asks two main questions. How likely is a specific event to happen? “You
Gartner continues to receive high client demand for integrated riskmanagement (IRM) insights and what IRM offers beyond the typical governance, risk and compliance (GRC) technology deployments. That’s exactly what we hear from organizations who look to GRC as a solution for their riskmanagement challenges.
DORA has several objectives, including to comprehensively address information and communications technology (ICT) riskmanagement in the financial services sector and harmonize the ICT riskmanagement regulations that already exist in individual EU member states.
It’s similar to corporate governance, except that it applies specifically to ML/AI models and should be viewed as a subset of model riskmanagement. It’s purpose is to improve efficiency as well as to mitigate risks, and to either reduce or eliminate the financial impact of any hazards that can occur.
OCBC Bank optimizes customer experience & riskmanagement with multi-phased data initiative. The company recently migrated to Cloudera Data Platform (CDP ) and CDP Machine Learning to power a number of solutions that have increased operational efficiency, enabled new revenue streams and improved riskmanagement.
From stringent data protection measures to complex riskmanagement protocols, institutions must not only adapt to regulatory shifts but also proactively anticipate emerging requirements, as well as predict negative outcomes. The post Back to the Financial Regulatory Future appeared first on Cloudera Blog.
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.
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. Cybersecurity reduces risk exposure for cyberattacks on digitally connected assets.
Since then, a further update has been made to the BIS stress testing principles that continues to emphasize the importance of scenarios in better understanding risk. . When it comes to measuring climate risk, generating scenarios will be a critical tactic for financial institutions and asset managers. Assess Variables.
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