IBM Big Data Hub

JANUARY 25, 2024

The math demonstrates a powerful truth All predictive models, including AI, are more accurate when they incorporate diverse human intelligence and experience. Consider the diversity prediction theorem. . Typical questions include: What is your model’s use case? What are the risks for disparate impact?

Predictive Modeling 90

Predictive Modeling Modeling Risk Statistics 90

FineReport

APRIL 9, 2024

From advanced analytics to predictive modeling, the evolving landscape of business intelligence is revolutionizing how data is processed and leveraged for actionable insights. Proactive Risk Management : BI tools enable organizations to proactively identify potential risks through predictive modeling and trend analysis.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

CIO Business Intelligence

DECEMBER 11, 2023

Traditionally, the work of the CFO and the finance team was focused on protecting the company’s assets and reputation and guarding against risk. They can even optimize capital allocation decisions, such as dividend distribution versus share buy-back, by rapidly modeling multiple scenarios and market conditions.

Finance 105

Finance Forecasting IoT Predictive Modeling 105

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. With the exponential growth of large datasets, predictive analytics is being leveraged by enterprises across industries.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. With the exponential growth of large datasets, predictive analytics is being leveraged by enterprises across industries.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just

Risk 359

Risk Modeling Data Processing Software 359

Smarten

SEPTEMBER 28, 2022

In order to understand how businesses might use assisted predictive modeling and predictive analytics, let’s look at some business use cases and how analytical techniques can help the enterprise derive concise, clear information to support decisions and strategies. Quality Control. Demand Planning. Plan and forecast accurately.

Predictive Analytics 52

Predictive Analytics Analytics Predictive Modeling Forecasting 52

Smarten

MAY 31, 2022

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ It is meant to identify crucial relationships and opportunities and risks and help the organization to accurately predict: Growth.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

Smart Data Collective

MARCH 3, 2021

When the risk of recurrence for a malpractice case is high, for example, they can convince the judge to be more generous in rewarding the client. The impact of predictive modelling on personal injury cases. Predictive modelling is a technology that evolved together with big data analytics.

Analytics 129

Analytics Big Data Predictive Modeling Insurance 129

Smart Data Collective

SEPTEMBER 17, 2020

Here are a few of the advantages of Big Data in the banking and financial industry: Improvement in risk management operations. Big Data can efficiently enhance the ways firms utilize predictive models in the risk management discipline. Big Data provides financial and banking organizations with better risk coverage.

Big Data 142

Big Data Finance Risk Management Risk 142

John Wheeler

OCTOBER 20, 2020

We continue our “20 for 20” theme this year by highlighting the integrated risk management (IRM) critical capabilities and top 20 software functions / features. These five capabilities support both integrated view of strategic, operational and technology risk as well as the related business outcomes, processes and assets.

Risk Management 52

Risk Management Risk Predictive Modeling Insurance 52

Cloudera

JUNE 27, 2023

Adopting an MDA is more efficient and cost effective than legacy data architectures which are siloed, poorly governed, with vast redundant data sets and data processes that are expensive and expose the company to risk. Modernize data flows. Most telcos rely on legacy applications that create data silos and limit interoperability.

Data Architecture 63

Data Architecture Predictive Modeling Data Governance Data-driven 63

IBM Big Data Hub

MAY 1, 2023

The early versions of AI were capable of predictive modelling (e.g., The four categories of predictive modelling, robotics, speech and image recognition are collectively known as algorithm-based AI or Discriminative AI. recommending similar Netflix shows based on your previous choices) or robotics (e.g.,

Insurance 82

Insurance Predictive Modeling Cost-Benefit Statistics 82

Ontotext

MAY 31, 2023

To support drug discovery, Ontotext has recently developed a method for gene-disease link prediction, which can help focus research efforts where it would matter most and speed up the drug development process. The link prediction models are based on the so-called Knowledge Graph Embeddings, which relying on knowledge graph technology.

Experimentation 52

Experimentation Cost-Benefit Predictive Modeling Risk 52

IBM Big Data Hub

MAY 18, 2023

This report outlines the combination of traditional decision automation tools with machine learning models and other technologies. As Forrester notes in the report, many organizations are eager to harness the power of AI but also must be cautious of risks.

Reporting 94

Reporting Scorecard Predictive Modeling Machine Learning 94

CIO Business Intelligence

AUGUST 23, 2023

To do so, they explored the optimization problem of “cardinality constraints” and developed a hybrid quantum-classical approach to financial index tracking portfolios that maximizes returns and minimizes risk. We started our models, pressed run, and had to wait until the morning and hope they hadn’t crashed overnight,” Broer says.

IT 96

IT Machine Learning Risk Optimization 96

Smarten

MARCH 12, 2020

A solution that provides a balance between data agility and access and data governance and security can provide solid, dependable information and the ability for users to leverage Self-Serve Data Preparation , Assisted Predictive Modeling and Smart Data Visualization while protecting the organization from risk and mitigating security issues.

Data Governance 67

Data Governance Predictive Modeling Data-driven Visualization 67

Business Over Broadway

SEPTEMBER 27, 2018

pharmacogenomics) and risk assessment of genetic disorders (e.g., Analytics applied to these types of data help you generate better predictive models because your integrated data contain all the key variables that are useful in predicting customer churn. Machine Learning and Predictive Modeling of Customer Churn.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

Smart Data Collective

MARCH 23, 2022

This AI could be utilized as a safety feature , like real-time risk assessment, for example, alerting the driver when a potential incident has been detected. Utilizing advanced heuristics and AI modeling OEMs can simulate a multitude of conditions, fast-tracking these models using automation.

IoT 111

IoT Internet of Things Testing Cost-Benefit 111

DataRobot

OCTOBER 19, 2021

DataRobot models successfully identified areas with high per-capita infection rates across the board, not only the densely populated urban counties. This approach allows end-users to make better informed decisions when assessing risk and other criteria such as age or ethnic diversity. reporting backlogs). White Paper.

Forecasting 98

Forecasting Predictive Modeling Optimization Testing 98

Smarten

MAY 17, 2019

These techniques can be beneficial for infrastructure planning, construction, highway planning and management, government, agriculture, weather, travel and city planning, and can help the business to plan for resources, locations, supply chain, marketing, inventory, pricing, risk management, maintenance and other planning activities.

Predictive Analytics 58

Predictive Analytics Analytics Predictive Modeling Risk Management 58

DataRobot

MARCH 2, 2021

With DataRobot, you can build dozens of predictive models with the push of a button and easily deploy them. Monitoring deployed models is easy because we provide features to check on service health, data drift, and accuracy. DataRobot products offer an end-to-end solution to address all stages of the AI pipeline.

Predictive Modeling 98

Predictive Modeling Risk Consulting Dashboards 98

Smarten

JUNE 8, 2022

Predictive analytics uses data integrated from appropriate data sources, and augmented analytics allows the business to anticipate production demands, plan for new locations and markets and predict targeted customer buying behavior and changes in product demand across multiple market segments. Anticipating Machine Maintenance Needs.

Predictive Analytics 52

Predictive Analytics Predictive Modeling Forecasting Optimization 52

Smarten

MAY 17, 2019

Whether you need to anticipate and plan for equipment maintenance, target online customers, control customer churn, or identify ways to cross-sell and upsell customers on existing and new products and services, these predictive analytics tools can help you to optimize your marketing budget and your resources and mitigate risk and market missteps.

Predictive Analytics 65

Predictive Analytics Forecasting Analytics Predictive Modeling 65

Smarten

APRIL 17, 2018

How Can Assistive Predictive Modeling Help My Business Users? Assisted Predictive Modeling can help your business achieve its goals.

Predictive Analytics 40

Predictive Analytics Predictive Modeling Analytics Forecasting 40

Smarten

MAY 16, 2019

In the interim, there is loss of productivity and the risk of crucial mistakes. Augmented analytics can also identify the need for training, the types of jobs that are most at risk of frequent turnover, the key skills for a particular position and the probability of advancement. Learn More: Human Resource Attrition. Customer Targeting.

Predictive Analytics 51

Predictive Analytics Analytics Predictive Modeling Cost-Benefit 51

O'Reilly on Data

DECEMBER 12, 2019

Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1] 1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. That’s where model debugging comes in. Interpretable ML models and explainable ML.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

IBM Big Data Hub

OCTOBER 5, 2022

You also build planning models to capture relationships and constraints so that you can change your driver assumptions and immediately see the impact on resources and capacity over time. Time matters too: your models must be quick to run, so analysis can be done before the assumptions are out-of-date.

Analytics 52

Analytics Forecasting Predictive Modeling Manufacturing 52

Smarten

JUNE 25, 2019

Augmented analytics allows for data prep, Smart Data Visualization and Assisted Predictive Modeling with the help of machine learning and natural language processing (NLP), so users need not be trained as data scientists to get to the heart of the data and find those elusive nuggets of information that will help them create, change and improve.

Analytics 51

Analytics Predictive Modeling Visualization Machine Learning 51

DataKitchen

JUNE 19, 2023

This pillar emphasizes the importance of implementing thorough data validation tests to mitigate the risks of erroneous analysis or decision-making based on faulty data. The above image shows an example custom ‘data in use’ test of a predictive model and API. The value here is improved end-user experienc e.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

Smart Data Collective

MAY 23, 2021

While this can be classed as data science, one difference is that data science tends to use a predictive model to make its analysis, while AI can be capable of analyzing based on learned knowledge and facts. One way that AI can be used to benefit your tech company is to carry out risk analysis. The benefits to your tech company.

Data Science 99

Data Science Cost-Benefit Statistics Predictive Modeling 99

Sisense

MARCH 27, 2019

Finally, real-time BI helps better understand trends and create more accurate predictive models for organizations. By combining with historic trends, they can also create predictive models for ordering that automate time-consuming tasks. Who Uses Real-Time BI? What are the Real-Time BI Best Practices?

Business Intelligence 74

Business Intelligence Data Warehouse Predictive Modeling Visualization 74

CIO Business Intelligence

DECEMBER 13, 2022

We’re also doing a lot with population health management, performing more comprehensive patient assessments, managing our high-risk patients, stabilizing transitions of care, optimizing outpatient care, and really trying to call out things that help us understand disease progression.

Strategy 98

Strategy Technology Digital Transformation Data Lake 98

CIO Business Intelligence

OCTOBER 5, 2023

For AI, the high-value quadrant is where you’ll find most predictive modeling. Here, partnerships can make a huge difference in both risk mitigation and improving time to market. The quadrant Davé’s team attacks next is either “high-value, low-feasibility” or “low-value, high-feasibility,” depending on their objectives.

Experimentation 130

Experimentation Strategy Machine Learning Interactive 130

Smarten

MAY 16, 2019

Perhaps the greatest risk to a lending organization is that presented by loan applicants who are unprepared to fulfill the long-term obligation of paying off a loan. Use Assisted Predictive Modeling to define the perfect loan applicant profile and to monitor and manage existing loans to anticipate and mitigate loan defaults.

Predictive Analytics 40

Predictive Analytics Analytics Predictive Modeling Insurance 40

FineReport

APRIL 9, 2024

The implementation of robust healthcare data management strategies is imperative to mitigate the risks associated with data breaches and non-compliance. The integration of clinical data analysis tools empowers healthcare providers to leverage predictive analytics for proactive decision-making.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

IBM Big Data Hub

JUNE 29, 2023

This information is then used to build predictive models of an asset’s performance over time and help spot potential problems before they arise. One of the ways maintenance managers refine and improve predictive analytics to increase asset reliability is through the creation of a digital twin.

Cost-Benefit 86

Cost-Benefit Measurement Management Predictive Analytics 86