IBM Big Data Hub

FEBRUARY 19, 2024

To mitigate these risks , companies need the resources and technology to develop robust contingency plans. Fewer disruptions : A healthy supply chain mitigates risks and protects against inevitable disruption. Because finding the right suppliers can be challenging, some businesses turn to technology to help.

Strategy 82

Strategy Management Forecasting Cost-Benefit 82

IBM Big Data Hub

JUNE 29, 2023

By integrating financial planning with strategic and operational planning, organizations can evaluate financial profitability, identify potential gaps or risks, and make necessary adjustments to achieve financial targets. Automation streamlines data processes reduces manual effort and minimizes the risk of errors or data discrepancies.

Key Performance Indicator 76

Key Performance Indicator Forecasting Sales Data Integration 76

Smart Data Collective

JUNE 26, 2019

The insurance industry is based on the idea of managing risk. To determine this risk, the industry must consult data and see what trends are evident to draft their risk profiles. The in-depth analysis of historical data gives insurers a platform to base their determination of risk.

Insurance 94

Insurance Data Analytics Analytics IoT 94

IBM Big Data Hub

JULY 27, 2023

EAM systems can include functions like maintenance management, asset lifecycle management , inventory management and work order management, among others. Access to asset/system simulations can enable more proactive maintenance planning, improved decision-making and better risk management.

Cost-Benefit 55

Cost-Benefit IoT Internet of Things Enterprise 55

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

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. Inventory transparency and order accuracy AI-powered order management systems provide real-time visibility into all aspects of the critical order management workflow.

B2B 65

B2B Interactive Optimization Forecasting 65

Decision Management Solutions

FEBRUARY 27, 2019

Manage Risk Better (aka underwriting and adjusting). On the risk management front, we have begun working with some insurers to automate underwriting and pricing. This will drive consistency and accuracy and allow them to use more advanced analytics and machine learning to manage risk. Sell More.

Insurance 40

Insurance Technology Business Driver Predictive Analytics 40

FineReport

MARCH 24, 2024

Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue. Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making. JPMorgan Chase & Co.:

Statistics 52

Statistics Data mining Visualization Reporting 52

datapine

MARCH 31, 2022

It allows its users to extract actionable insights from their data in real-time with the help of predictive analytics and artificial intelligence technologies. Like this, data scientists, engineers, managers, and other users, can access data from multiple sources and perform advanced analysis to extract relevant insights from it.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

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

Ontotext

FEBRUARY 26, 2024

The answers to these foundational questions help you uncover opportunities and detect risks. We bundle these events under the collective term “Risk and Opportunity Events” This post is part of Ontotext’s AI-in-Action initiative aimed to empower data, scientists, architects and engineers to leverage LLMs and other AI models.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Now, there is a data risk here.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

BizAcuity

MARCH 31, 2022

85% of AI (marketing) projects fail due to risk, confusion, and lack of upskilling among marketing teams.(Source: Not just banking and financial services, but many organizations use big data and AI to forecast revenue, exchange rates, cryptocurrencies and certain macroeconomic variables for hedging purposes and risk management.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Cloudera

JUNE 23, 2021

Yet there are also more subtle risks to monitor, including changes to insured assets, risks, and exposures. Climate change can also impact the insurance carrier as an enterprise itself—similarly to cyber risks, insurers underwrite cyber risks for their customers, as well as manage their own risks and exposure as a company.

Insurance 52

Insurance Risk Modeling Risk Management 52

Smart Data Collective

DECEMBER 15, 2020

The market you specialize in should very much depend on your own interests, as well as your financial position, your attitude to risk, the hours you plan to spend trading, and various other factors. Understand the risk with predictive analytics risk scoring algorithms.

Data Analytics 65

Data Analytics Analytics Big Data Risk 65

datapine

AUGUST 29, 2022

However, don’t be deceived – just as you don’t need to be a literal startup to gain a lot of value from Eric Ries’ work, companies of all sizes and shapes can learn a lot of valuable information from “Lean Analytics”. 7) Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Cloudera

MARCH 18, 2021

The Fundamental Review of the Trading Book (FRTB), introduced by the Basel Committee on Banking Supervision (BCBS), will transform how banks measure risk. In order to help make banks more resilient to drastic market changes, it will impose capital requirements that are more closely aligned with the market’s actual risk factors.

Risk 55

Risk Machine Learning Risk Management Measurement 55

CIO Business Intelligence

JANUARY 26, 2023

Costs can be charged back to the specific teams, and ManageEngine’s predictive analytics will plan reserved instances based on historical data. Many of the tools are customer-facing solutions like IT automation, but there are also more backend tools for optimizing IT operations by intelligently managing performance.

Management 116

Management Forecasting Dashboards Optimization 116

Cloudera

JANUARY 22, 2019

Cloudera enables high-value analytical use cases from the edge to AI including proactive and predictive maintenance, usage-based analytics for targeted communications, recommendation engines, Enterprise Risk Management, AML (Anti-Money Laundering), Fraud Detection/Prevention, Cybersecurity, and Machine Models.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Octopai

NOVEMBER 11, 2020

BI teams in financial institutions are challenged on a daily basis with being able to quickly assess compliance risks, support risk reduction and prepare for economic challenges. They need to use power predictive analytics for optimized trade routing.

Finance 52

Finance Risk Risk Management Data-driven 52

Andrew White

JANUARY 11, 2021

Some data is more a risk than valuable. What are you seeing as the differences between a Chief Analytics Officer and the Chief Data Officer? Value Management or monetization. Risk Management (most likely within context of governance). Product Management. Would really like to explore this one in debate.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52