IBM Big Data Hub

MAY 8, 2023

In my previous post , I described the different capabilities of both discriminative and generative AI, and sketched a world of opportunities where AI changes the way that insurers and insured would interact. Usage risk—inaccuracy The performance of an AI system heavily depends on the data from which it learns.

Insurance 68

Insurance Risk Testing Data Quality 68

DataKitchen

OCTOBER 20, 2023

While this is a technically demanding task, the advent of ‘Payload’ Data Journeys (DJs) offers a targeted approach to meet the increasingly specific demands of Data Consumers. Deploying a Data Journey Instance unique to each customer’s payload is vital to fill this gap.

Insurance 169

Insurance Metadata Data-driven Data Quality 169

Cloudera

SEPTEMBER 7, 2023

The way to manage this is by embedding data integration, data quality-monitoring, and other capabilities into the data platform itself , allowing financial firms to streamline these processes, and freeing them to focus on operationalizing AI solutions while promoting access to data, maintaining data quality, and ensuring compliance.

Insurance 83

Insurance Risk Data-driven Finance 83

CIO Business Intelligence

MAY 24, 2022

In order to help maintain data privacy while validating and standardizing data for use, the IDMC platform offers a Data Quality Accelerator for Crisis Response.

Finance 140

Finance Management Metadata Machine Learning 140

CIO Business Intelligence

OCTOBER 17, 2024

Liberty Dental Plan insures about 7 million people in the United States as a dental insurance company. And over time I have been given more responsibility on the operations side: claims processing and utilization management, for instance, both of which are the key to any health insurance company (or any insurance company, really).

Management 111

Management Insurance ROI Cost-Benefit 111

erwin

DECEMBER 9, 2024

A data catalog providing automated data profiling does just this and, when tied in with data lineage, your organization can easily see metadatas pathway back to all sources feeding your AI model. Within the catalog one can visualize this lineage for data quality results and sensitive data inputs.

Metadata 52

Metadata Data Quality Sales Modeling 52

erwin

MARCH 30, 2020

This data will be collected from organizations such as, the World Health Organization (WHO), the Centers for Disease Control (CDC), and state and local governments across the globe. Privately it will come from hospitals, labs, pharmaceutical companies, doctors and private health insurers. Data lineage to support impact analysis.

Metadata 122

Metadata IT Data Governance Data Quality 122

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage).

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

CIO Business Intelligence

SEPTEMBER 30, 2024

Like others, Bell’s data scientists face challenges such as data cleanliness and interoperability, and Mathematica will at times partner with other organizations to overcome those challenges.

Data Quality 116

Data Quality Experimentation Insurance Statistics 116

Smart Data Collective

SEPTEMBER 28, 2022

Big data management increases the reliability of your data. Big data management has many benefits. One of the most important is that it helps to increase the reliability of your data. Data quality issues can arise from a variety of sources, including: Duplicate records Missing records Incorrect data.

Big Data 126

Big Data Management Data Quality Cost-Benefit 126

Cloudera

MARCH 3, 2022

It’s believed the source of the breach was Marriott’s Starwood subsidiary and Marriott might not have done due diligence when merging its newly acquired subsidiary’s data into its own databases. In 2017, Anthem reported a data breach that exposed thousands of its Medicare members.

Data Governance 100

Data Governance Enterprise Data Quality Metadata 100

Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. At Cloudera, we believe in the untapped opportunity presented by data and AI, too.

Risk 100

Risk Optimization Management Insurance 100

erwin

APRIL 11, 2019

Some industries, such as healthcare and financial services, have been subject to stringent data regulations for years: GDPR now joins the Health Insurance Portability and Accountability Act (HIPAA), the Payment Card Industry Data Security Standard (PCI DSS) and the Basel Committee on Banking Supervision (BCBS).

Data-driven 100

Data-driven Insurance Data Governance Metadata 100

CIO Business Intelligence

MARCH 31, 2022

To date, many of those appointments have been concentrated in the insurance, banking, media and entertainment, retail, and IT/technology verticals. Chief data officer job description. The CDO oversees a range of data-related functions that may include data management, ensuring data quality, and creating data strategy.

Consulting 134

Consulting Data Strategy Data Governance Strategy 134

CIO Business Intelligence

APRIL 29, 2022

Despite soundings on this from leading thinkers such as Andrew Ng , the AI community remains largely oblivious to the important data management capabilities, practices, and – importantly – the tools that ensure the success of AI development and deployment. Further, data management activities don’t end once the AI model has been developed.

Data Governance 145

Data Governance IT Data Lake Risk 145

CIO Business Intelligence

APRIL 28, 2022

Having disparate data sources housed in legacy systems can add further layers of complexity, causing issues around data integrity, data quality and data completeness. million in insurance fraud in just 7 months. .

Analytics 98

Analytics Insurance Big Data Uncertainty 98

CIO Business Intelligence

JUNE 13, 2022

Today, most banks, insurance companies, and other kinds of financial services firms have deployed natural language processing (NLP) tools to address some of their customer service needs. billion, and for insurance, the savings will approach $1.3 Ready to evolve your analytics strategy or improve your data quality?

Deep Learning 105

Deep Learning Data Processing Insurance Cost-Benefit 105

CIO Business Intelligence

JUNE 7, 2022

billion in cost savings for the insurance industry as well during the same period. . For banks, brokerages, insurance companies, fintech firms, and other financial services organizations, NLP is increasingly being seen as a solution to too much data and too few employees. The same study estimated that chatbots would lead to $1.3

Unstructured Data 98

Unstructured Data Deep Learning Insurance Interactive 98

Decision Management Solutions

NOVEMBER 13, 2018

80% of data and analytics leaders with global life insurance and property & casualty carriers surveyed by McKinsey reported that their analytics investments are not delivering high impact. This was the leading obstacle to high impact analytics, outscoring even poor data quality or a lack of strategic support or alignment.

Insurance 40

Insurance Analytics Modeling Visualization 40

AWS Big Data

JANUARY 30, 2023

We examine a hypothetical insurance organization that issues commercial policies to small- and medium-scale businesses. The insurance prices vary based on several criteria, such as where the business is located, business type, earthquake or flood coverage, and so on. getOrCreate() #Define the table schema schema = StructType().add("policy_id",IntegerType(),True).add("expiry_date",DateType(),True).add("location_name",StringType(),True).add("state_code",StringType(),True).add("region

Insurance 86

Insurance Data Lake Data-driven Management 86

Alation

JUNE 17, 2021

Joint Success with Texas Mutual Insurance. Our most influential customers frequently highlight the importance of data governance when attempting to mobilize data across their organizations,” says Chris Atkinson, Global Partner CTO, Snowflake. Texas Mutual Insurance Company (TXM) is one joint customer of Snowflake and Alation.

Data Governance 98

Data Governance Data Lake Insurance Enterprise 98

Smart Data Collective

FEBRUARY 28, 2023

Data analytics technology has had a profound impact on the state of the financial industry. A growing number of financial institutions are using analytics tools to make better investing decisions and insurers are using analytics technology to improve their underwriting processes.

Analytics 126

Analytics Data mining Finance Analytics Technologies 126

IBM Big Data Hub

MAY 9, 2024

Healthcare organizations need a strong data governance framework to help ensure compliance with regulations like the Health Insurance Portability and Accountability Act of 1996 (HIPAA) in the US and the General Data Protection Regulation (GDPR) in the EU. All this relies on reliable data and requires data lineage for governance.

Data Governance 66

Data Governance Data Quality Insurance Predictive Analytics 66

Cloudera

JULY 20, 2021

Risk models for financial institutions and insurers are exponentially more complicated . So relying upon the past for future insights with data that is outdated due to changing customer preferences, the hyper-competitive world and emphasis on environment, society and governance produces non-relevant insights and sub-optimized returns.

Manufacturing 106

Manufacturing Forecasting IoT Insurance 106

CIO Business Intelligence

JANUARY 31, 2023

“It democratizes the architecture so you can ask questions about the applications used,” says enterprise architect Mike Winfield of London-based Tokio Marine Kiln, a specialist insurance company. Winfield agrees, adding: “The difficult bit is getting accurate data into the EAM.”

Enterprise 138

Enterprise Digital Transformation Risk Visualization 138

datapine

MAY 31, 2022

This has increased the difficulty for IT to provide the governance, compliance, risks, and data quality management required. Every time a company moves data from the internal storage to a cloud, it is faced with being compliant with official regulations and laws.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

CIO Business Intelligence

MAY 21, 2024

They worked with Ituran MOB, which develops and manufactures a suite of hardware and software solutions for fleet management, stolen vehicle recovery, car connectivity, and performance-based insurance needs. The device plugs into CAN bus cables by induction.

Broadcasting 126

Broadcasting Recreation/Entertainment Manufacturing Data Lake 126

IBM Big Data Hub

JUNE 22, 2023

Technology-enabled business process operations, the new BPO, can significantly create new value, improve data quality, free precious employee resources, and deliver higher customer satisfaction, but it requires a holistic approach. The results can be apparent quickly.

Consulting 77

Consulting Insurance Finance Uncertainty 77

Cloudera

JUNE 13, 2024

Cloudera’s true hybrid approach ensures you can leverage any deployment, from virtual private cloud to on-premises data centers, to maximize the use of AI. Reliability – Can you trust that your data quality will yield useful AI results?

Big Data 103

Big Data Machine Learning Contextual Data Data Lake 103

DataRobot Blog

JULY 21, 2022

Data aggregation such as from hourly to daily or from daily to weekly time steps may also be required. Perform data quality checks and develop procedures for handling issues. Typical data quality checks and corrections include: Missing data or incomplete records Inconsistent data formatting (e.g.,

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

IBM Big Data Hub

JANUARY 15, 2024

As an insurance company integrating technology into the new development landscape, BoB-Cardif Life Insurance Co., As an insurance company integrating technology into the new development landscape, BoB-Cardif Life Insurance Co.,

Digital Transformation 66

Digital Transformation Insurance Optimization ROI 66

Octopai

JUNE 26, 2020

Steve, the Head of Business Intelligence at a leading insurance company, pushed back in his office chair and stood up, waving his fists at the screen. We’re dealing with data day in and day out, but if isn’t accurate then it’s all for nothing!” Why aren’t the numbers in these reports matching up?

Metadata 98

Metadata Data Governance Enterprise Reporting 98

CIO Business Intelligence

APRIL 6, 2022

For example, on the front end, healthcare organizations can optimize secure access to clinical data to improve the level of care provided and reduce patient wait times. While on the back end, AIOps can facilitate insurance processes, protect patient information, and minimize fraud. Just starting out with analytics?

Data mining 72

Data mining Deep Learning Insurance Visualization 72

Smart Data Collective

SEPTEMBER 25, 2019

million penalty for violating the Health Insurance Portability and Accountability Act, more commonly known as HIPAA. If you trust the data, it’s easier to use confidently to make business decisions. Organizations receive significant fines for noncompliance.

Technology 102

Technology Statistics Strategy Insurance 102

CIO Business Intelligence

MAY 27, 2024

This industry is often generally categorized into providers — hospitals and centers that employ doctors and treat patients — and payers — companies that sell health insurance or ancillary services. State of healthcare By way of illustration, let’s focus on the healthcare space , where technology has changed the rules of engagement.

IT 105

IT Strategy Risk Technology 105

Sisense

APRIL 15, 2021

From data preparation , with attendant data quality assessment, to connecting to datasets and performing the analysis itself, helpful AI elements, invisibly integrated into the platform, make analysis smoother and more intuitive. A typical data science text outlining these methods is 1,000 pages of equations and algorithms.

Analytics 98

Analytics Data Science Machine Learning Modeling 98

Timo Elliott

JANUARY 5, 2022

The first one is: companies should invest more in improving their data quality before doing anything else. To make a big step forward with data science, you first need to do that painful work. They are already impacting industries such as agriculture and insurance. That’s an awful waste of resources.

Digital Transformation 115

Digital Transformation Machine Learning Enterprise Data Science 115