CIO Business Intelligence

JUNE 21, 2022

Governance should be designed with adaptability in mind to ensure IT remains in alignment with business objectives, continually providing value while effectively safeguarding the organization against potential risks, Bales says. Poor risk planning. Insufficient operational visibility.

IT 116

IT Risk Measurement Risk Management 116

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. However, it is possible to identify some potential drawbacks and apply risk management practices in advance. Pursue a phased approach. Rome wasn’t built in a day: neither will your BI.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

Cloudera

FEBRUARY 15, 2024

While there are clear reasons SVB collapsed, which can be reviewed here , my purpose in this post isn’t to rehash the past but to present some of the regulatory and compliance challenges financial (and to some degree insurance) institutions face and how data plays a role in mitigating and managing risk.

Insurance 88

Insurance Data Architecture Risk Management Risk 88

Cloudera

JUNE 12, 2024

Traditional machine learning (ML) models enhance risk management, credit scoring, anti-money laundering efforts and process automation. Some of the biggest and well-known financial institutions are already realizing value from AI and GenAI: JPMorgan Chase uses AI for personalized virtual assistants and ML models for risk management.

Finance 77

Finance Risk Management Risk Data-driven 77

Cloudera

OCTOBER 28, 2021

Since the beginning of Commercial insurance as we know it today, insurers have been using data generated by other industries to assess and rate risks. In the days of Lloyd’s Coffee House , insurers gathered data about cargo, voyages, seasonal weather and the performance history of vessels and mariners to underwrite risks.

Insurance 97

Insurance Risk Unstructured Data Data-driven 97

Cloudera

JULY 29, 2022

It supports business objectives like increasing revenues, improving customer experience, and driving profitability by giving business units and users access to relevant data so they can quickly gain the insight they need. The proof is in the pudding.

Data Architecture 89

Data Architecture Data Strategy Risk Management Strategy 89

CIO Business Intelligence

SEPTEMBER 30, 2024

CIO.com / Foundry They also cited AI/ML capabilities in specific areas — such as risk management, fraud detection, smart manufacturing, predictive maintenance, quality control, and personalized employee engagement — as fueling transformation. Everyone is looking at AI to optimize and gain efficiencies, for sure.

Machine Learning 141

Machine Learning ROI Data Processing Optimization 141

CIO Business Intelligence

OCTOBER 3, 2023

They enable greater efficiency and accuracy and error reduction, better decision making, better compliance and risk management, process optimisation and greater agility. Intelligent document processing: uses artificial intelligence and machine learning techniques to automate the processing of documents and unstructured data.

Cost-Benefit 122

Cost-Benefit Machine Learning Interactive Software 122

Smart Data Collective

FEBRUARY 2, 2021

Also, thanks to Big Data, recruitment is now more accurate. Keep in mind that recruitment agencies have to deal with huge volumes of unstructured data, and analyzing all this data by traditional means is not only slow, but also ineffective. Public services.

Big Data 106

Big Data Recreation/Entertainment Cost-Benefit Finance 106

CDW Research Hub

MAY 24, 2021

It encompasses other components, including data security that focuses primarily on protecting unstructured data in storage from unauthorized access, use, loss or modification. Develop a security risk management program. Apply defense-in-depth measures and assess the security controls to identify and manage risk.

Risk Management 52

Risk Management Unstructured Data Risk Business Objectives 52

CIO Business Intelligence

SEPTEMBER 2, 2022

Skills for financial data engineers include coding skills, data analytics, data visualization, data optimization, data integration, data modeling, cloud computing services, knowledge of relational and nonrelational database systems, and an ability to work with high volumes of structured and unstructured data.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

Skills for financial data engineers include coding skills, data analytics, data visualization, data optimization, data integration, data modeling, cloud computing services, knowledge of relational and nonrelational database systems, and an ability to work with high volumes of structured and unstructured data.

Finance 98

Finance IT Software Reporting 98

bridgei2i

MAY 17, 2021

AI-based automation tools can significantly enhance efficiency, reduce human biases and errors, and learn about the data sets to spot anomalies or identify long-term trends. In addition, it can counter the various pitfalls in profiling customers and credit scoring and reducing the supply chain’s potential risks. billion by 2026.

Finance 52

Finance Unstructured Data Risk Management Cost-Benefit 52

Cloudera

NOVEMBER 18, 2021

This included using NiFi to automatically collect and centralize documents consisting of unstructured data and then leveraging advanced natural language processing to extract tacit knowledge and perform sentiment analysis on unstructured text and images from more than 20 million documents. Data for Good.

Data Lake 77

Data Lake Cost-Benefit Digital Transformation Risk 77

CIO Business Intelligence

JULY 6, 2023

For example, IDP uses native AI to quickly and accurately extract data from business documents of all types, for both structured and unstructured data,” Reis says. Another benefit is greater risk management.

Cost-Benefit 119

Cost-Benefit Technology Unstructured Data Testing 119

Smart Data Collective

OCTOBER 14, 2019

Understanding Big Data Analytics. Big data analytics is the process of evaluating large chunks of information at once. Said information can be a combination of semi-structured and unstructured data sets — coming from web server logs, social media, network traffic logs, etc.

Big Data 88

Big Data Data Analytics Analytics Unstructured Data 88

AWS Big Data

SEPTEMBER 26, 2024

Organizations are collecting and storing vast amounts of structured and unstructured data like reports, whitepapers, and research documents. By consolidating this information, analysts can discover and integrate data from across the organization, creating valuable data products based on a unified dataset.

Data Lake 101

Data Lake Cost-Benefit Unstructured Data Modeling 101

CIO Business Intelligence

MARCH 27, 2023

For example, underwriters used to toggle between nearly a dozen tools to get their job done — today they use one streamlined tool with all relevant information at their fingertips to make better decisions while understanding risks, Soni says. Foundry / CIO.com With data and analytics a critical engine for driving business strategy, Dow Inc.

Strategy 109

Strategy Digital Transformation Insurance Technology 109

bridgei2i

APRIL 9, 2019

Wealth Management for Clients. Most enterprises and heavyweight financial companies are acquiring start-ups with the motive to analyze the massive amounts of unstructured data automatically. The banking sector that makes the most use of AI is wealth management. This is where AI companies come into the picture.

Unstructured Data 69

Unstructured Data Sales Data-driven Finance 69

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

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

Laminar Security

MAY 3, 2023

They define DSPM technologies this way: “DSPM technologies can discover unknown data and categorize structured and unstructured data across cloud service platforms. At Laminar, we refer to those “unknown data repositories” as shadow data. Data can be copied, modified, moved, and backed up with just a few clicks.

Management 40

Management Risk Risk Management Data Processing 40

IBM Big Data Hub

AUGUST 28, 2023

Named entity recognition (NER): NER extracts relevant information from unstructured data by identifying and classifying named entities (like person names, organizations, locations and dates) within the text. Popular algorithms for topic modeling include Latent Dirichlet Allocation (LDA) and non-negative matrix factorization (NMF).

Data mining 53

Data mining Machine Learning Deep Learning Marketing 53

bridgei2i

MAY 21, 2019

Wealth Management for Clients. Most enterprises and heavyweight financial companies are acquiring start-ups with the motive to analyze the massive amounts of unstructured data automatically. The banking sector that makes the most use of AI is wealth management. This is where AI companies come into the picture.

Unstructured Data 40

Unstructured Data Sales Data-driven Finance 40

bridgei2i

FEBRUARY 28, 2020

Today, with AI, more sophisticated rules can be developed which address the sparse data problems by factoring in alternate and behavioural data such as smart phone usage and payment behaviour. With AI, apart from the quantitative data, unstructured data systems can be assessed for risk management.

Risk Management 78

Risk Management Unstructured Data Machine Learning Digital Transformation 78

Domino Data Lab

AUGUST 10, 2021

The model uses algorithms to identify patterns in the data that form a relationship with an output. Models can predict things before they happen more accurately than humans, such as catastrophic weather events or who is at risk of imminent death in a hospital. Managing Model Risk. This comes down to model risk management.

Modeling 64

Modeling IT Deep Learning Risk Management 64

bridgei2i

APRIL 23, 2020

The banking sector globally is definitely going to see impact, some more grave than the others and most of them are announcing short to mid term measure both from a customer and business risk mitigation standpoint. Europe is in worse shape than America, with banks in UK, Italy and Germany in the risk of being in red.

Risk 52

Risk Management Scorecard Forecasting 52

Jet Global

MAY 9, 2024

The architecture may vary depending on the specific use case and requirements, but it typically includes stages of data ingestion, transformation, and storage. Data ingestion methods can include batch ingestion (collecting data at scheduled intervals) or real-time streaming data ingestion (collecting data continuously as it is generated).

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

CIO Business Intelligence

FEBRUARY 4, 2025

Although the probe is still ongoing and the nature or extent of the ban is yet to be decided, experts believe that the ban may impact enterprises or any user in multiple ways, including loss of access, compliance risks, security concerns, data continuity issues, and migration. Other experts, such as agentic AI-providing Doozer.AI

Enterprise 101

Enterprise Data Processing Consulting Risk 101

CIO Business Intelligence

FEBRUARY 14, 2025

Since data is the fuel for AI, unlocking its full potential is only possible when organizations have mastered data management. However, according to Foundry research conducted for GEP, weak internal data management capabilities were the most common challenge organizations face when preparing data for AI initiatives (45%).

Management 59

Management Unstructured Data Risk Management Risk 59