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 100

Risk Optimization Management Insurance 100

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 85

Data Architecture Risk Management Risk Management 85

CIO Business Intelligence

AUGUST 7, 2023

Organizations big and small, across every industry, need to manage IT risk. based IT directors and vice presidents in companies with more than 1,000 employees to determine what keeps them up at night—and it comes as no surprise that one of their biggest nightmares is managing IT risk. trillion annually by 2025.

Risk 98

Risk IT Management Risk Management 98

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. To reference SR 11-7: .

Risk 64

Risk Modeling Machine Learning Data Quality 64

CIO Business Intelligence

FEBRUARY 20, 2025

However, it is often unclear where the data needed for reporting is stored and what quality it is in. Often the data quality is insufficient to make reliable statements. Insufficient or incorrect data can even lead to wrong decisions, says Kastrati.

Big Data 84

Big Data Measurement Visualization Machine Learning 84

erwin

MARCH 25, 2021

Risk Management and Regulatory Compliance. Risk management, specifically around regulatory compliance, is an important use case to demonstrate the true value of data governance. According to Pörschmann, risk management asks two main questions. Strengthen data security. erwin DG Webinar Series.

Data Governance 109

Data Governance Cost-Benefit IT Risk 109

erwin

JULY 12, 2019

It also helps enterprises put these strategic capabilities into action by: Understanding their business, technology and data architectures and their inter-relationships, aligning them with their goals and defining the people, processes and technologies required to achieve compliance. Strengthen data security. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

CIO Business Intelligence

SEPTEMBER 17, 2024

All this while CIOs are under increased pressure to deliver more competitive capabilities, reduce security risks, connect AI with enterprise data, and automate more workflows — all areas where architecture disciplines have a direct role in influencing outcomes.

Enterprise 145

Enterprise Digital Transformation Cost-Benefit Risk 145

CIO Business Intelligence

SEPTEMBER 24, 2024

Chief data and analytics officers need to reinvent themselves in the age of AI or risk their responsibilities being assimilated by their organizations’ IT teams, according to a new Gartner report. And with data quality tied directly to successful AI projects, CDAOs must also increase their visibility and show how they can help. “Gen

Data Governance 115

Data Governance Risk Management Risk Data Quality 115

CIO Business Intelligence

DECEMBER 19, 2023

Third, in the CDO Agenda: 2024: Navigating Data and Generative AI Frontiers , 57% of respondents haven’t changed their data environments to support generative AI. CIOs should look for other operational and risk management practices to complement transformation programs.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. Clean data in, clean analytics out. Cleaning your data may not be quite as simple, but it will ensure the success of your BI. Indeed, every year low-quality data is estimated to cost over $9.7

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

erwin

APRIL 29, 2020

Regulatory compliance places greater transparency demands on firms when it comes to tracing and auditing data. For example, capital markets trading firms must understand their data’s origins and history to support risk management, data governance and reporting for various regulations such as BCBS 239 and MiFID II.

Key Performance Indicator 111

Key Performance Indicator Data Governance Metadata Data Quality 111

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. The document, first published in 2013, outlines best practices for global and domestic banks to identify, manage, and report risks, including credit, market, liquidity, and operational risks.

Metadata 89

Metadata Risk Management Business Intelligence Data Governance 89

erwin

FEBRUARY 4, 2021

However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. Overcoming Data Governance Bottlenecks. Put data quality first : Users must have confidence in the data they use for analytics.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

erwin

OCTOBER 24, 2019

Addressing the Complexities of Metadata Management. The complexities of metadata management can be addressed with a strong data management strategy coupled with metadata management software to enable the data quality the business requires. With erwin, organizations can: 1.

Metadata 104

Metadata Management Data-driven Data Architecture 104

CIO Business Intelligence

MAY 15, 2024

“If you have a data center that happens to have capacity, why pay someone else?” According to Synopsys’ open source security and risk analysis released in February, 96% of all commercial code bases contained open source components. It also focuses largely on risk and governance issues. It’s almost a way to mitigate risk.”

Modeling 137

Modeling Risk Software Enterprise 137

erwin

JANUARY 23, 2025

Data intelligence software is continuously evolving to enable organizations to efficiently and effectively advance new data initiatives. With a variety of providers and offerings addressing data intelligence and governance needs, it can be easy to feel overwhelmed in selecting the right solution for your enterprise.

Metadata 52

Metadata Data Quality Data Governance Software 52

erwin

APRIL 4, 2019

Some other common data governance obstacles include: Questions about where to begin and how to prioritize which data streams to govern first. Issues regarding data quality and ownership. Concerns about data lineage. Competing project and resources (time, people and funding).

Data Governance 75

Data Governance Data Quality Risk Management Data-driven 75

DataRobot Blog

MAY 26, 2022

To start with, SR 11-7 lays out the criticality of model validation in an effective model risk management practice: Model validation is the set of processes and activities intended to verify that models are performing as expected, in line with their design objectives and business uses.

Risk 52

Risk Modeling Metrics Business Objectives 52

erwin

SEPTEMBER 17, 2020

Here are six benefits of automating end-to-end data lineage: Reduced Errors and Operational Costs. Data quality is crucial to every organization. Automated data capture can significantly reduce errors when compared to manual entry.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Alation

AUGUST 17, 2022

We’ve seen the emergence of new, less invasive approaches, yet the question remains: What do CIOs think is most required to deliver a successful data governance program? The Risks of Early Data Governance Programs. The biggest risk was a lack of ownership. If your definitions are bad, so is your governance/risk/security.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

DataRobot Blog

JULY 21, 2022

Inquire whether there is sufficient data to support machine learning. Document assumptions and risks to develop a risk management strategy. For a credit risk model, the target could be defined as “fully repays loan” or “payments in first 2 years are current” or or “collateral is repossessed.”. Define project scope.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

CIO Business Intelligence

APRIL 29, 2022

From a policy perspective, the organization needs to mature beyond a basic awareness and definition of data compliance requirements (which typically holds that local operations make data “sovereign” by default) to a more refined, data-first model that incorporates corporate risk management, regulatory and reporting issues, and compliance frameworks.

Digital Transformation 132

Digital Transformation Data-driven Strategy Data Strategy 132

IBM Big Data Hub

APRIL 20, 2023

When consumers lose trust in a bank’s ability to manage risk, the system stops working. Banks and their employees place trust in their risk models to help ensure the bank maintains liquidity even in the worst of times. This can ensure that the decisions made are reliable and of high quality.

Risk 68

Risk Risk Management Reporting Metadata 68

CIO Business Intelligence

APRIL 28, 2022

Right from the start, auxmoney leveraged cloud-enabled analytics for its unique risk models and digital processes to further its mission. Particularly in Asia Pacific , revenues for big data and analytics solutions providers hit US$22.6bn in 2020 , with financial services companies ranking among their biggest clients.

Analytics 98

Analytics Insurance Big Data Uncertainty 98

IBM Big Data Hub

FEBRUARY 28, 2024

Successful strategic sourcing often results in process optimization, cost management, customer satisfaction, risk management , increased sustainability and other benefits. Sourcing teams are automating processes like data analysis as well as supplier relationship management and transaction management.

Strategy 94

Strategy Technology Cost-Benefit Risk Management 94

Cloudera

SEPTEMBER 7, 2023

But it’s also fraught with risk. This June, for example, the European Union (EU) passed the world’s first regulatory framework for AI, the AI Act , which categorizes AI applications into “banned practices,” “high-risk systems,” and “other AI systems,” with stringent assessment requirements for “high-risk” AI systems.

Insurance 83

Insurance Risk Data-driven Finance 83

CIO Business Intelligence

SEPTEMBER 2, 2022

As more financial companies embrace the cloud, there’s been an increase in demand for data engineers to help manage AWS and Azure services in the organization. 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

As more financial companies embrace the cloud, there’s been an increase in demand for data engineers to help manage AWS and Azure services in the organization. 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

DataRobot

JULY 16, 2021

They all serve to answer the question, “How well can my model make predictions based on data?” 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.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

Jet Global

AUGUST 28, 2023

We are eager to offer this additional support to insightsoftware customers, advancing our own capabilities that improve data quality and visibility, and enhance performance.” “This acquisition seamlessly connects insightsoftware’s expertise and product offerings with our extensive visualization library.

Dashboards 75

Dashboards Visualization Finance Data Quality 75

Octopai

JULY 12, 2020

An enormous amount of time was being wasted performing manual searches, as the BI team needed to frequently comb through the enterprise data warehouse’s fields to determine how each was calculated or to find their sources. We now get the benefit of proliferated data quality.” – Andrew Stewardson, Data Risk Manager, FCSA.

Data Warehouse 84

Data Warehouse Data Quality Metadata Risk Management 84

IBM Big Data Hub

NOVEMBER 28, 2022

Provide early indicators of data quality. Poor data quality is one of the top barriers faced by organizations aspiring to be data-driven. Most data quality management approaches are reactive, triggered only when consumers complain to data teams about the integrity of datasets.

Metadata 56

Metadata Data Quality Data-driven Data Governance 56

Octopai

JUNE 19, 2023

Everyone has access to the same data and the same understanding of what the data represents, reducing miscommunications and discrepancies. Catalogs also allow for better Risk Management; data catalogs help businesses maintain regulatory compliance by providing a clear record of what data is stored and how it’s used.

Metadata 98

Metadata Data Governance Measurement Risk Management 98

Smart Data Collective

SEPTEMBER 25, 2019

However, according to a 2018 North American report published by Shred-It, the majority of business leaders believe data breach risks are higher when people work remotely. Whether you work remotely all the time or just occasionally, data encryption helps you stop information from falling into the wrong hands.

Technology 102

Technology Statistics Strategy Insurance 102

IBM Big Data Hub

SEPTEMBER 15, 2023

These requirements will likely mandate publicly traded companies to disclose their greenhouse gas (GHG) emissions footprint, climate-related goals, and progress, as well as climate-risk related financial impact and expenditures. Furthermore, companies would need to disclose the price and rationale for internal carbon prices.

Reporting 72

Reporting Risk Data-driven Publishing 72