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

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.

Machine Learning 55

Machine Learning Risk Risk Management Measurement 55

Cloudera

SEPTEMBER 7, 2023

But these measures alone may not be sufficient to protect proprietary information. Even when backed by robust security measures, an external AI service is a tempting, outsized target for potential security breaches: each integration point, data transfer, or externally exposed API becomes a target for malicious actors.

Insurance 83

Insurance Risk Data-driven Finance 83

IBM Big Data Hub

JUNE 29, 2023

Continuous monitoring and performance management Integrated Business Planning is an ongoing process that requires continuous monitoring of performance against plans and targets. Key performance indicators (KPIs) are established to measure progress and enable proactive management.

Key Performance Indicator 76

Key Performance Indicator Forecasting Sales Data Integration 76

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. There are primarily two underlying techniques that can be leveraged for AML initiatives- Exploratory Data Analysis and Predictive analytics. Predictive Analytics can help businesses in reducing risk (eg.

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. There are primarily two underlying techniques that can be leveraged for AML initiatives- Exploratory Data Analysis and Predictive analytics. Predictive Analytics. Exploratory Data Analysis (EDA).

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Ontotext

FEBRUARY 26, 2024

Risk management : Understanding the correlation between events and stock price fluctuations helps manage risk. Strategic planning and predictive analytics : Companies can use this analysis for strategic planning. Market sentiment analysis : Events can significantly influence market sentiment.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

IBM Big Data Hub

MAY 17, 2024

Commerce operations Traditional AI allows for the automation of routine tasks such as inventory management, order processing and fulfillment optimization, resulting in increased efficiency and cost savings. Generative AI further enhances these capabilities by developing predictive models that anticipate changes in payment regulations.

B2B 64

B2B Interactive Optimization Data-driven 64

Andrew White

JANUARY 11, 2021

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. measuring value, prioritizing (where to start), and data literacy? Governance. Architecture.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

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.

Insurance 150

Insurance Risk IoT Data-driven 150

Cloudera

JUNE 23, 2021

Data and Analytics Can Help . When deployed smartly, data can help manage the disruption associated with such natural events. Analytics and the increased use of AI can improve underwriting and risk-management practices for customers, insurers, and reinsurers. De-Risking with Data and AI.

Insurance 52

Insurance Risk Modeling Risk Management 52

datapine

AUGUST 29, 2022

7) Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel. Best for: someone who has heard a lot of buzz about predictive analytics, but doesn’t have a firm grasp on the subject. – Eric Siegel, author, and founder of Predictive Analytics World.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

CIO Business Intelligence

MARCH 26, 2025

Implementing robust security measures such as encryption, regular security audits, and employee training, and partnerships with legal experts can help ensure adherence. For instance, AI-driven predictive maintenance and digital twins can reduce maintenance costs by 20%, optimizing production and supply chains.

IoT 66

IoT Data-driven Digital Transformation Optimization 66

CIO Business Intelligence

MARCH 18, 2025

Information risk management is no longer a checkpoint at the end of development but must be woven throughout the entire software delivery lifecycle. The evolution of risk management Modern information security requires thinking like a trusted advisor rather than a checkpoint guardian.

Risk Management 99

Risk Management Risk Management Metrics 99

Octopai

NOVEMBER 11, 2020

They need to use power predictive analytics for optimized trade routing. Automated data lineage on the cloud: helping finance with risk management, regulations, financial crime. Automated data lineage on the cloud: helping finance with risk management, regulations, financial crime.

Finance 52

Finance Risk Risk Management Data-driven 52