Decision Management Solutions

APRIL 23, 2019

In February, we published a blog post on “Using Technology to Add Value in Insurance”. in which he states there are only three levers of value in insurance: Sell More, Manage Risk Better (aka underwriting and adjusting), and Cost Less to Operate. Insurers can also manage risk more effectively through continuous improvement.

Insurance 69

Insurance Risk Technology Management 69

Decision Management Solutions

MAY 1, 2019

In February, we published a blog post on “Using Technology to Add Value in Insurance”. One clear way to reduce operating costs in insurance is to add automation to complex decision-making processes, such as underwriting and claims handling. in which he states that there are only three levers of value in insurance: 1. Sell More , 2.

Insurance 75

Insurance Technology Predictive Analytics Risk 75

Smart Data Collective

OCTOBER 13, 2020

Deloitte Analytics author Ashwin Patil recently talked about the incredible benefits of big data in the automotive sector. His article focused primarily on the applications of big data in auto manufacturing. “At However, there are plenty of other applications of big data after the manufacturing process is finished.

Data-driven 133

Data-driven Big Data Manufacturing Insurance 133

CIO Business Intelligence

NOVEMBER 16, 2023

In a career spanning such companies as IBM, KeyCorp, M&T Bank, and BMO, she has “answered the call” many times, most recently as CIO of The Hartford, where she is responsible for the overall strategy, vision, and execution of business technology, cyber, data analytics, and data science. Can you expand on that?

Insurance 125

Insurance Enterprise Risk Digital Transformation 125

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 103

Analytics Data mining Finance Analytics Technologies 103

CIO Business Intelligence

FEBRUARY 13, 2023

This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). The economy may be looking uncertain, but technology continues to drive the business and CIOs are investing big in 2023.

IT 145

IT Insurance Machine Learning Marketing 145

IBM Big Data Hub

JUNE 23, 2023

Although interest rates have increased at an unprecedented rate over the past year due to efforts by central banks to curb inflation, insurers are locked into low-yielding investments, and it will take several years for their investment yields to improve. Core modernization (processes and technology) is a top priority for every insurer.

Insurance 62

Insurance Cost-Benefit Digital Transformation Marketing 62

CIO Business Intelligence

FEBRUARY 6, 2023

We call our approach high tech and high touch, because that takes into account the very clear feedback that we’re getting from our customers — that they want digital solutions to take the transactional nature from our relationship away in a way that is intuitive and secure, but they want us to be there when it matters the most,” he says.

Insurance 124

Insurance IT Digital Transformation Machine Learning 124

Smart Data Collective

JUNE 3, 2021

The market for data analytics in the insurance sector is projected to be worth nearly $22.5 Many of the applications of big data for insurance companies will be realized with machine learning technology. However, there are multiple other reasons that life insurance companies use machine learning as well.

Insurance 98

Insurance Machine Learning Cost-Benefit Risk 98

Decision Management Solutions

APRIL 15, 2019

In February, we published a blog post on “Using Technology to Add Value in Insurance.” Manage Risk Better (aka underwriting and adjusting). NBO is an increasingly accepted approach to improving the targeting and effectiveness of marketing in consumer-facing industries, such as insurance and retail banking. Sell More.

Insurance 63

Insurance Technology Predictive Analytics Sales 63

Smart Data Collective

AUGUST 26, 2021

Data analytics technology is one of the biggest reasons that things are changing faster than ever. This is one of the areas that has been fundamentally transformed by new advances in data analytics technology. Understanding the Shift Caused by Data Analytics in Digital Lending. Employees work online.

Data-driven 69

Data-driven Software Risk Testing 69

bridgei2i

NOVEMBER 17, 2020

But what is changing today, is the nature and shape of data powering these systems and processes. A more automated support, claims, underwriting, collections or pricing processes focused on increasing customer experience at every moment of truth. We look at three waves of this change. Cost out and waste reduction were the key motto.

Deep Learning 85

Deep Learning Manufacturing Optimization Data-driven 85

Decision Management Solutions

FEBRUARY 27, 2019

Manage Risk Better (aka underwriting and adjusting). This resonated with me as we have been doing a lot of work recently developing digital decisioning solutions using our DecisionsFirst approach for insurance carriers and have seen all three drivers in play. Cost Less to Operate. This can also have an impact on selling.

Insurance 40

Insurance Technology Business Driver Sales 40

Cloudera

OCTOBER 6, 2022

For example, we have some customers using their data platform originally established for compliance initiatives to drive new use cases. These data lakes house much of the data needed to also support other use cases. We maintain the same information in multiple places because it is used across the enterprise.

Digital Transformation 84

Digital Transformation Cost-Benefit Data Lake Machine Learning 84

Decision Management Solutions

MARCH 25, 2019

Nancy Casbarro and Deb Zawisa of Novarico recently published a new paper on Data Science in Insurance: Expansion and Key Issues subscription required) that was summarized in this nice little article on Dig-in 3 challenges facing insurers in data science implementation. 1 – Getting business buy-in.

Insurance 75

Insurance Data Science Testing Modeling 75

Decision Management Solutions

MARCH 11, 2019

For decades we’ve had three major disciplines each doing something different about improving the quality of decisions. Gartner asserts that these disciplines are starting to overlap more and more, creating new opportunities for companies and government agencies to improve their decision making. It’s not data modeling.

Management 74

Management IT Data Science Modeling 74

bridgei2i

NOVEMBER 20, 2020

Business users across various verticals and domains have been using this to reduce their time to actionability, thus preventing impact to their businesses. In the previous podcast, we heard Predeep Ghimrey, an expert in the CPG industry who talked about the use cases of Watchtower in the CPG domain. Subscribe Now.

Risk Management 92

Risk Management Risk Management Metrics 92

Smart Data Collective

MAY 11, 2023

The good news is that big data technology is helping banks meet their bottom line. Therefore, it should be no surprise that the market for data analytics is growing at a rate of nearly 23% a year after being worth $744 billion in 2020. Big data can help companies in the financial sector in many ways.

Data mining 99

Data mining Big Data Sales Cost-Benefit 99

AWS Big Data

OCTOBER 11, 2023

Under the Transparency in Coverage (TCR) rule , hospitals and payors to publish their pricing data in a machine-readable format. The data in the machine-readable files can provide valuable insights to understand the true cost of healthcare services and compare prices and quality across hospitals.

Visualization 92

Visualization Dashboards Data-driven Gap analysis 92

AWS Big Data

JUNE 13, 2023

The ability to utilize data to make near-real-time decisions is a source of competitive advantage for Klarna. This post presents a reference architecture for real-time queries and decision-making on AWS using Amazon Kinesis Data Analytics for Apache Flink. These underwriting decisions are critical artefacts.

Data Analytics 52

Data Analytics Analytics Risk Snapshot 52

CIO Business Intelligence

JUNE 26, 2023

Transitioning to automated, data-driven processes is the best way for these companies to not only cope with change but also take advantage of it. Consumer banks can use digital interactions to gather more customer data and apply real-time analytics to expand services and speed up processes.

Data-driven 97

Data-driven Insurance Risk Risk Management 97

Cloudera

SEPTEMBER 7, 2023

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. It’s the most revolutionary technological development in at least a generation.

Insurance 78

Insurance Risk Data-driven Modeling 78

bridgei2i

AUGUST 2, 2020

In simple terms, it means automation and simplification of processes, by learning from data of different types and formats and then removing the manual and prone-to-error parts from the process. Machine learning algorithms help us assess the right patterns in step 2. This moment of truth is now getting shifted irremovably.

Digital Transformation 95

Digital Transformation Insurance Unstructured Data Cost-Benefit 95

Cloudera

JUNE 23, 2021

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 carriers are of course heavily involved in underwriting events related to weather. Climate and Supply Chain.

Insurance 52

Insurance Risk Modeling Risk Management 52

Cloudera

NOVEMBER 4, 2020

Here the insurance industry has a tremendous opportunity to leverage the data sourced from new technology to improve risk assessments and underwriting models – wearable tech such as fitness trackers and other smart devices, geo location, telematics. They’re not using the data to add insight into their customers profiles.

Insurance 110

Insurance Machine Learning Risk IoT 110

bridgei2i

APRIL 13, 2020

Typically, computer vision technology uses special neural networks called Convolutional Neural Networks, which are trained using thousands of sample images and algorithms to break down individual components in the image pixel by pixel, and these are then memorized by the system. billion by 2024 in the US. billion by 2025!

Insurance 52

Insurance Manufacturing Deep Learning Enterprise 52

CIO Business Intelligence

DECEMBER 19, 2022

Some of the key problems that we are working on include creating an underwriting solution for our customers in tier 2 and 3 cities. To develop these products, we will heavily use data, artificial intelligence, and machine learning. There still isn’t a place in the industry where you can get a home loan in minutes.

Data Warehouse 116

Data Warehouse Finance Machine Learning Technology 116