Smart Data Collective

JULY 16, 2023

Big data is the most important business trend of the 21st century. The usage, volume, and types of data have increased significantly. In fact, big data keeps gaining momentum. We mentioned that data analytics is vital to marketing , but it is affecting many other industries as well.

ROI 72

ROI Data Analytics Analytics Risk Management 72

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. It encompasses risk management and regulatory compliance and guides how AI is managed within an organization. Foundation models can use language, vision and more to affect the real world.

Risk 70

Risk Modeling Management Metadata 70

IBM Big Data Hub

MAY 31, 2024

At both gatherings, participants emphasized the importance of effective governance and risk management. However, these advanced AI and generative AI applications come with risks, and agencies must address concerns around data privacy and protection, reliability, tax rights and hallucinations from generative models.

Cost-Benefit 98

Cost-Benefit Risk Risk Management Reporting 98

IBM Big Data Hub

OCTOBER 4, 2022

Furthermore, 59% of executives claim AI can improve the use of big data in their organizations, facts about artificial intelligence show. ( Manual processes that introduce risk and make it hard to scale. Multiple unsupported tools for building and deploying models. Challenges around managing risk.

Metadata 97

Metadata Risk Risk Management Experimentation 97

Smart Data Collective

SEPTEMBER 21, 2021

Retailers around the world are discovering that big data can be incredibly valuable to their bottom lines. A growing number of businesses are starting to look for new data-driven approaches to streamline their business models. Targeting the Right Variables for Your Data-Driven Retail Business Model.

Data-driven 108

Data-driven Metrics Big Data Sales 108

IBM Big Data Hub

JUNE 10, 2024

As organizations strive to harness the power of AI while controlling costs, leveraging anything as a service (XaaS) models emerges as a strategic approach. Embracing the power of XaaS XaaS encompasses a broad spectrum of cloud-based and on-premises service models that offer scalable and cost-effective solutions to businesses.

Experimentation 63

Experimentation Optimization Risk Management Modeling 63

Smart Data Collective

APRIL 22, 2020

Big data has turned the software industry on its head. The relationship between software development and big data is a two-way street. While many software developers are looking to create new applications that use big data, they are also using big data to streamline development.

Data-driven 92

Data-driven Software Big Data Testing 92

IBM Big Data Hub

MAY 1, 2024

For example, combining generative AI with technologies such as blockchain helps to keep data about the material-to-product transformation unchangeable across different entities, providing clear visibility into products’ origin and carbon footprint.

Forecasting 78

Forecasting Optimization Digital Transformation Risk 78

IBM Big Data Hub

FEBRUARY 13, 2024

Demystifying generative AI At the heart of Generative AI lie massive databases of texts, images, code and other data types. This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Imagine training a generative AI model on a dataset of only romance novels.

Enterprise 119

Enterprise Modeling Testing Data-driven 119

IBM Big Data Hub

APRIL 19, 2024

Mobile-connected technicians experience improved safety through measures such as access control, gas detection, warning messages or fall recognition, which reduces risk exposure and enhances operational risk management (ORM) during work execution. Risk-based asset strategies align maintenance efforts to balance costs and risks.

Management 85

Management Internet of Things Risk IoT 85

Cloudera

AUGUST 12, 2021

By using Cloudera’s big data platform to harness IoT data in real-time to drive predictive maintenance and improve operational efficiency, the company has realized about US$25 million annually in new profit resulting from better efficiency of working sites. . Risk Management. Conclusion.

Data-driven 111

Data-driven Manufacturing Insurance Risk Management 111

IBM Big Data Hub

MARCH 4, 2024

Figure 2: ROI potential by transforming into an AI+ enterprise Organizations with high data maturity that embed an AI+ transformation model into the enterprise fabric and culture can generate up to 2.6 Consider the following: Do you need a public foundation model? times higher ROI. Should you build your own?

Enterprise 96

Enterprise ROI Risk Strategy 96

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

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 84

Analytics Insurance Big Data Uncertainty 84

IBM Big Data Hub

APRIL 20, 2023

Banks and their employees place trust in their risk models to help ensure the bank maintains liquidity even in the worst of times. This trust depends on an understanding of the data that inform risk models: where does it come from, where is it being used, and what are the ripple effects of a change?

Risk 68

Risk Risk Management Reporting Metadata 68

IBM Big Data Hub

APRIL 4, 2024

Lots of innovation is happening, with new technologies emerging in areas such as data and AI, payments, cybersecurity and risk management, to name a few. A third-party risk management review, where the ISV needs to describe how it is complying to required controls. Most of these new technologies are born-in-cloud.

Cost-Benefit 55

Cost-Benefit Risk Management Risk Digital Transformation 55

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI in commerce—such as models trained on inadequate or inappropriate data—lead to bad experiences that alienate consumers and businesses. AI models analyze vast amounts of data quickly and accurately.

B2B 64

B2B Interactive Optimization Forecasting 64

IBM Big Data Hub

APRIL 18, 2023

ISO 20022 data improves payment efficiency The impact of ISO 20022 on payment systems data is significant, as it allows for more detailed information in payment messages. ISO 20022 drives improved analytics and new revenue opportunities ISO 20022 enables more sophisticated payment analytics by providing a richer data set for analysis.

Risk Management 110

Risk Management Cost-Benefit Risk Data-driven 110

IBM Big Data Hub

MARCH 25, 2024

Developing a risk management strategy for insurance and other financial services In recent years, financial services firms have realized that they need a decision-making strategy that accounts for the implications of climate change. As a result, pension funds and other stock market investments might suffer adverse effects.

Insurance 86

Insurance Forecasting Risk Risk Management 86

IBM Big Data Hub

JANUARY 16, 2024

New technology and the growth of AI bring into question personal data and privacy concerns, which will ultimately change the regulatory requirements in financial services. More organizations will likely be transitioning to hybrid cloud models for their workloads and to further manage and conduct compliance tasks.

Risk Management 48

Risk Management Insurance Cost-Benefit Risk 48

erwin

OCTOBER 31, 2019

While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, introducing governance, manageability and risk issues that must be managed. So being prepared means you can minimize your risk exposure and the damage to your reputation.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

IBM Big Data Hub

DECEMBER 4, 2023

The Board recently published its point of view on foundation models addressing the risks that generative AI poses. Its toolkit automates risk management, monitors models for bias and drift, captures model metadata and facilitates collaborative, organization-wide compliance.

Consulting 74

Consulting Risk Metadata Risk Management 74

IBM Big Data Hub

MAY 9, 2023

According to Gartner , 54% of models are stuck in pre-production because there is not an automated process to manage these pipelines and there is a need to ensure the AI models can be trusted. This solution is designed to include everything needed to develop a consistent transparent model management process.

Metadata 72

Metadata Risk Experimentation Dashboards 72

Cloudera

MARCH 28, 2019

The threat posed by new market entrants, unconstrained by the legacy IT systems of big banks, is as obvious as their appeal to a generation of digital natives. The feedback loops may not have been obvious because they were either too complicated to model or the computing power and capacity did not exist. Risk management 3.0.

Risk 74

Risk Management Risk Management Machine Learning 74

erwin

AUGUST 20, 2020

As organization’s become increasingly complex, agile enterprise architecture can help organizations avoid over-analysis – often dubbed “analysis paralysis” – and take a “just-in-time”, “just-enough” approach to modeling. Data Security & Risk Management.

Enterprise 140

Enterprise Cost-Benefit Risk Data Governance 140

IBM Big Data Hub

DECEMBER 4, 2023

As part of our generative AI initiatives, we can demonstrate the ability to use a foundation model with prompt tuning to review the structured and unstructured data within the insurance documents (data associated with the customer query) and provide tailored recommendations concerning the product, contract or general insurance inquiry.

Insurance 53

Insurance Digital Transformation Risk Management Interactive 53

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. 1] With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

IBM Big Data Hub

DECEMBER 15, 2023

When AI algorithms, pre-trained models, and data sets are available for public use and experimentation, creative AI applications emerge as a community of volunteer enthusiasts builds upon existing work and accelerates the development of practical AI solutions.

Deep Learning 64

Deep Learning Experimentation Machine Learning Risk 64

Cloudera

MAY 15, 2018

Over the past decade, we have observed open source powered big data and analytics platforms evolve from large data storage containers to massively scalable advanced modeling platforms that seamlessly operate on-premises and in a multi-cloud environment. These examples are well covered by many others (e.g.,

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

IBM Big Data Hub

JANUARY 30, 2024

For inspiration, look across industries to uncover examples of data center success. Finance: Optimized for high-speed transactions and can assist in providing robust security, harnessing AI for fraud detection and real-time risk management.

Manufacturing 71

Manufacturing Business Objectives Optimization Risk Management 71

IBM Big Data Hub

AUGUST 15, 2022

Sometimes as data scientists, we are often so determined to build a perfect model that we can unintentionally include human bias into our models. Often the bias creeps in through training data and then is amplified and embedded in the model. Model risk management.

Data mining 60

Data mining Risk Modeling Risk Management 60

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 53

Data mining Machine Learning Deep Learning Marketing 53

IBM Big Data Hub

MAY 28, 2024

Virtually every organization recognizes the power of data to enhance customer and employee experiences and drive better business decisions. Yet, as data becomes more valuable, it’s also becoming harder to protect. Data risk management To protect their data, organizations first need to know their risks.

Strategy 82

Strategy Measurement Risk Cost-Benefit 82

IBM Big Data Hub

JUNE 23, 2023

Generative AI empowers faster and better data-driven decisions based on historical data, market trends and the use of AI foundation models that identify patterns and anomalies often missed by traditional analysis methods. What is generative AI, what are foundation models, and why do they matter?

Finance 56

Finance Consulting Data-driven Risk 56

Smart Data Collective

SEPTEMBER 21, 2022

Unfortunately, they also have challenges, such as choosing the right business model for their AI startup. As far as Data Analysis is concerned, potential employees should have an extensive knowledge of quantitative research, quantitative reporting, compiling statistics, statistical analysis, data mining, and big data.

Statistics 85

Statistics Software Data mining Marketing 85

IBM Big Data Hub

SEPTEMBER 20, 2022

But these organizations need to be able to trust their AI/ML models before they can be operationalized and used in crucial business processes. These days, if an AI model makes a biased, unfair decision involving the health, wealth or well-being of humans, an organization can hit the news for the wrong reasons. Is it scalable?

Metadata 56

Metadata Machine Learning Data-driven Modeling 56