CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics in business Predictive analytics draws its power from a wide range of methods and technologies, including big data, data mining, statistical modeling, machine learning, and assorted mathematical processes. Models can be designed, for instance, to discover relationships between various behavior factors.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

IBM Big Data Hub

MARCH 7, 2023

The challenge was gleaning relevant insights from the vast amount of data collected to help identify those infants at risk. The specific approach we took required the use of both AI and edge computing to create a predictive model that could process years of anonymized data to help doctors make informed decisions.

Risk 52

Risk Technology Informatics Predictive Modeling 52

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. So, it’s not just volume, but diversity that improves predictions.

Predictive Modeling 87

Predictive Modeling Modeling Risk Statistics 87

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 104

Finance Forecasting IoT Predictive Modeling 104

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

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. The latest trends in business intelligence are reshaping the way organizations utilize data to gain a strategic advantage.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

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. For predictive analytics to deliver high accuracy, a lot depends on the combination of domain knowledge and technical expertise.

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. Predictive Analytics. Predictive Analytics can help businesses in reducing risk (eg.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Smarten

SEPTEMBER 28, 2022

Gartner has predicted that, ‘Overall analytics adoption will increase from 35% to 50%, driven by vertical and domain-specific augmented analytics solutions.’ Predictive analytics uses sophisticated analytical methodologies to predict future outcomes based on historical data. Customer Churn. Quality Control. Demand Planning.

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 legal sector is still in its infancy when it comes to big data and analytics. Are they still legal experts if they use a computer? How can personal injury companies use analytics?

Analytics 127

Analytics Big Data Predictive Modeling Insurance 127

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

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. It is used to return a prediction or result based on conditional probability.

Insurance 79

Insurance Predictive Modeling Cost-Benefit Statistics 79

IBM Big Data Hub

MAY 18, 2023

As Forrester notes in the report, many organizations are eager to harness the power of AI but also must be cautious of risks. It provides a low-code environment where business experts can manage decision automation projects and apply their knowledge to model decisions without extensive coding or deep AI knowledge.

Reporting 91

Reporting Scorecard Predictive Modeling Machine Learning 91

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. Appliance-based models are usually significantly more expensive than disaggregated solutions. Modernize data flows.

Data Architecture 62

Data Architecture Predictive Modeling Data Governance Data-driven 62

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

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

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

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. How do they make vehicles safer?

IoT 109

IoT Internet of Things Testing Cost-Benefit 109

IBM Big Data Hub

MAY 17, 2024

But as businesses around the globe rapidly adopt the technology to augment processes from merchandising to order management, there is some risk. This includes trust in the data, the security, the brand and the people behind the AI. Recent advancements in artificial intelligence (AI) are transforming commerce at an exponential pace.

B2B 67

B2B Interactive Optimization Forecasting 67

DataKitchen

JUNE 19, 2023

Our customers start looking at the data in dashboards and models and then find many issues. Perhaps we could just chill out in those stressful situations and “let go,” as the Buddha suggests. The spiritual benefits of letting go may be profound, but finding and fixing the problem at its root is, as Samuel Florman writes, “ existential joy.”

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

DataRobot

OCTOBER 19, 2021

By leveraging prediction and augmented decision-making, governments can address the needs of taxpayers proactively while quickly adapting to evolving circumstances. DataRobot helped combat this problem head on by applying AI to evaluate and predict resource allocation and identify the most impacted communities from a national to county level.

Forecasting 98

Forecasting Predictive Modeling Optimization Testing 98

CIO Business Intelligence

OCTOBER 5, 2023

We’ve seen so many initiatives fail when it’s technology for technology’s sake,” says Davé, who suggests two means of avoiding this mistake: prioritization models aligned to your business strategy and strategic partnerships. Let’s start with the models. For AI, the high-value quadrant is where you’ll find most predictive modeling.

Experimentation 129

Experimentation Strategy Machine Learning Interactive 129

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 191

Machine Learning Modeling Testing Risk Management 191

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. Every day, millions of people interact with AI systems, often without knowing it. Our Program.

Predictive Modeling 98

Predictive Modeling Risk Consulting Dashboards 98

Smarten

JUNE 27, 2018

For example, if an outlier indicates a risk or a mistake, that outlier should be identified and the risk or mistake should be addressed. For example, if an outlier indicates a risk or a mistake, that outlier should be identified and the risk or mistake should be addressed. About Smarten.

IT 40

IT Business Intelligence Predictive Modeling Testing 40

Smarten

JUNE 8, 2022

Predicting Demand. In order to predict and forecast and assure product or service availability, the business must also look at the dependability of suppliers, shipping and the purchasing of parts that make up the products. machine in a good condition is to timely monitor it and detect the patterns to predict the breakdowns.

Predictive Analytics 52

Predictive Analytics Predictive Modeling Forecasting Optimization 52

CIO Business Intelligence

OCTOBER 12, 2023

Generac Power Systems’ Tim Dickson is an award-winning CIO who drives transformative change through technology and talent. He’s known as a digital game changer who operates at the intersection of advanced technology and business strategy. What’s your take on the changing role of the CIO? Tim Dickson: I have a funny story that sort of encompasses it.

IoT 125

IoT Manufacturing Strategy Modeling 125

Smarten

MAY 17, 2019

There is a lot of information within your enterprise, and being able to analyze that information is crucial to decision-making and to managing your business and predicting results with efficiency and accuracy. View the Predictive Analytics Using External Data Use Case Slide Share. Customer Targeting. Customer Churn. Fraud Mitigation.

Predictive Analytics 58

Predictive Analytics Analytics Predictive Modeling Risk Management 58

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

CIO Business Intelligence

DECEMBER 13, 2022

Our digital transformation strategy is centered around establishing a consumer-oriented model that helps us customize chronic care management based on the ever-changing conditions of each patient.” Here, IT is playing a significant role. A lot of innovation initiatives right now are small and more closely aligned with tangible results.

Strategy 98

Strategy Technology Digital Transformation Data Lake 98

Smarten

JUNE 28, 2018

Business Problem: A bank wants to group loan applicants into high/medium/low risk based on attributes such as loan amount, monthly installments, employment tenure, the number of times the applicant has been delinquent in other payments, annual income, debt to income ratio etc. What is Hierarchical Clustering? Use Case – 1.

IT 40

IT Business Intelligence Predictive Modeling Risk 40

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. The programming for data science relies on already having statistics and predictive trends to work with.

Data Science 99

Data Science Cost-Benefit Statistics Predictive Modeling 99

IBM Big Data Hub

JUNE 29, 2023

When a critical asset like an expensive piece of machinery or infrastructure breaks unexpectedly, it affects customers and can cost companies millions. To be successful, businesses need to have clear, real-time visibility into the condition of their assets and a plan to keep them running smoothly and make repairs quickly when things break.

Cost-Benefit 84

Cost-Benefit Measurement Management Predictive Analytics 84

Smarten

APRIL 17, 2018

How Can Assistive Predictive Modeling Help My Business Users? In order to achieve goals and objectives and perform well in their respective roles, business users need to analyze data, draw conclusions, predict results and help the organization achieve its goals. If you want to find out more, Contact Us.

Predictive Analytics 40

Predictive Analytics Predictive Modeling Analytics Forecasting 40

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

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. Predictive Analytics Using External Data.

Predictive Analytics 51

Predictive Analytics Analytics Predictive Modeling Cost-Benefit 51