Thursday, May 8, 2025
News PouroverAI
Visit PourOver.AI
No Result
View All Result
  • Home
  • AI Tech
  • Business
  • Blockchain
  • Data Science & ML
  • Cloud & Programming
  • Automation
  • Front-Tech
  • Marketing
  • Home
  • AI Tech
  • Business
  • Blockchain
  • Data Science & ML
  • Cloud & Programming
  • Automation
  • Front-Tech
  • Marketing
News PouroverAI
No Result
View All Result

Examples of IBM assisting insurance companies in implementing generative AI-based solutions

January 23, 2024
in Blockchain
Reading Time: 3 mins read
0 0
A A
0
Share on FacebookShare on Twitter



IBM collaborates with insurance clients on various fronts to help them navigate their digital transformation journey. The IBM Institute for Business Value (IBV) has identified three key imperatives for insurers: embracing digital transformation to drive revenue growth and improve customer experience, improving core productivity while reducing costs, and adopting incremental application and data modernization using secure hybrid cloud and AI technologies. To successfully transform their companies, insurers must focus on providing digital offerings to customers, increasing efficiency, utilizing data more intelligently, addressing cybersecurity concerns, and striving for a resilient and stable offering.

Most insurance companies have recognized the importance of digital transformation and IT core modernization. They are leveraging hybrid cloud and multi-cloud infrastructure and platforms to achieve their objectives. This approach enables them to accelerate speed-to-market, develop innovative products and services, facilitate business growth, and enhance the overall customer experience. IBM, with its extensive capabilities in AI, is uniquely positioned to assist insurance companies in incorporating generative AI into their business processes. In fact, IBM has been recognized as a leader in AI-related capabilities by Gartner.

IBM works closely with insurance companies to identify opportunities where generative AI can make a significant impact. This includes optimizing processes related to handling large documents and text or image blocks. These use cases already account for a significant portion of AI workloads, and there is a growing trend towards enhancing their functionality using generative AI. Areas where generative AI can make a difference in the insurance industry include customer engagement, digital labor, application modernization, IT operations, and cybersecurity.

IBM has developed generative AI-based solutions for various insurance use cases, such as virtual agents, conversational search, compliance and regulatory processes, claims investigation, and application modernization. These solutions leverage automation and personalized AI to deliver secure and trustworthy outcomes. For example, IBM’s generative AI chatbots can provide personalized responses to insurance product queries, offer comprehensive views of insurance coverages, assist with adding required documents and beneficiaries, and perform other functions to enhance customer engagement.

Insurance agents and contact center agents can also benefit from generative AI-based solutions. These solutions can reduce document search time, summarize information, and enable advisory capabilities, leading to increased productivity and improved customer satisfaction metrics. IBM has been implementing traditional AI-based solutions for insurance companies and is now incorporating generative AI capabilities to enhance agent assistance.

Risk management is another area where generative AI can be applied. By leveraging publicly available data and proprietary experience data, insurers can enhance their risk evaluation and decision-making processes. IBM is working on collecting relevant data and developing foundation models within its watsonx AI and data platform to facilitate this.

Code modernization is a critical challenge for many insurance companies with legacy systems. IBM is using generative AI capabilities to understand the business rules and logic embedded in the existing codebase and support its transformation into a modular system. This process follows industry frameworks and models to guide the redesign and also aids in generating test cases and scripts for testing the modernized code.

While generative AI offers significant potential, there are concerns that need to be addressed. IBM recognizes these concerns and offers solutions through its watsonx platform components, such as AI studio, data store, and governance toolkit. These components provide explainability, ethics, bias mitigation, trust, and compliance capabilities to ensure the responsible and ethical use of generative AI.

In summary, IBM collaborates with insurance clients to facilitate their digital transformation journey by leveraging generative AI and other advanced technologies. IBM’s solutions address key imperatives, help insurers provide digital offerings, improve efficiency, utilize data intelligently, address cybersecurity concerns, and strive for a resilient and stable offering.



Source link

Tags: AIbasedassistingcompaniesExamplesgenerativeIBMImplementingInsuranceSolutions
Previous Post

Skills top tech companies are hiring for in 2024

Next Post

Scaling transformers for graph-structured data – Google Research Blog

Related Posts

5 SLA metrics you should be monitoring
Blockchain

5 SLA metrics you should be monitoring

June 10, 2024
10BedICU Leverages OpenAI’s API to Revolutionize Critical Care in India
Blockchain

10BedICU Leverages OpenAI’s API to Revolutionize Critical Care in India

June 9, 2024
Arkham: US Government Seizes $300M from Alameda Research Accounts
Blockchain

Arkham: US Government Seizes $300M from Alameda Research Accounts

June 8, 2024
Fake Musk Live Streams Flood YouTube During SpaceX Launch
Blockchain

Fake Musk Live Streams Flood YouTube During SpaceX Launch

June 7, 2024
How to Track Crypto Transactions for Taxes?
Blockchain

How to Track Crypto Transactions for Taxes?

June 7, 2024
NVIDIA Enhances Low-Resolution SDR Video with RTX Video SDK Release
Blockchain

NVIDIA Enhances Low-Resolution SDR Video with RTX Video SDK Release

June 7, 2024
Next Post
Scaling transformers for graph-structured data – Google Research Blog

Scaling transformers for graph-structured data – Google Research Blog

Researchers from Washington University in St. Louis Propose Visual Active Search (VAS): An Artificial Intelligence Framework for Geospatial Exploration 

Researchers from Washington University in St. Louis Propose Visual Active Search (VAS): An Artificial Intelligence Framework for Geospatial Exploration 

NVIDIA AI Introduces ChatQA: A Family of Conversational Question Answering (QA) Models that Obtain GPT-4 Level Accuracies

NVIDIA AI Introduces ChatQA: A Family of Conversational Question Answering (QA) Models that Obtain GPT-4 Level Accuracies

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

  • Trending
  • Comments
  • Latest
Is C.AI Down? Here Is What To Do Now

Is C.AI Down? Here Is What To Do Now

January 10, 2024
Porfo: Revolutionizing the Crypto Wallet Landscape

Porfo: Revolutionizing the Crypto Wallet Landscape

October 9, 2023
A Complete Guide to BERT with Code | by Bradney Smith | May, 2024

A Complete Guide to BERT with Code | by Bradney Smith | May, 2024

May 19, 2024
A faster, better way to prevent an AI chatbot from giving toxic responses | MIT News

A faster, better way to prevent an AI chatbot from giving toxic responses | MIT News

April 10, 2024
Part 1: ABAP RESTful Application Programming Model (RAP) – Introduction

Part 1: ABAP RESTful Application Programming Model (RAP) – Introduction

November 20, 2023
Saginaw HMI Enclosures and Suspension Arm Systems from AutomationDirect – Library.Automationdirect.com

Saginaw HMI Enclosures and Suspension Arm Systems from AutomationDirect – Library.Automationdirect.com

December 6, 2023
Can You Guess What Percentage Of Their Wealth The Rich Keep In Cash?

Can You Guess What Percentage Of Their Wealth The Rich Keep In Cash?

June 10, 2024
AI Compared: Which Assistant Is the Best?

AI Compared: Which Assistant Is the Best?

June 10, 2024
How insurance companies can use synthetic data to fight bias

How insurance companies can use synthetic data to fight bias

June 10, 2024
5 SLA metrics you should be monitoring

5 SLA metrics you should be monitoring

June 10, 2024
From Low-Level to High-Level Tasks: Scaling Fine-Tuning with the ANDROIDCONTROL Dataset

From Low-Level to High-Level Tasks: Scaling Fine-Tuning with the ANDROIDCONTROL Dataset

June 10, 2024
UGRO Capital: Targeting to hit milestone of Rs 20,000 cr loan book in 8-10 quarters: Shachindra Nath

UGRO Capital: Targeting to hit milestone of Rs 20,000 cr loan book in 8-10 quarters: Shachindra Nath

June 10, 2024
Facebook Twitter LinkedIn Pinterest RSS
News PouroverAI

The latest news and updates about the AI Technology and Latest Tech Updates around the world... PouroverAI keeps you in the loop.

CATEGORIES

  • AI Technology
  • Automation
  • Blockchain
  • Business
  • Cloud & Programming
  • Data Science & ML
  • Digital Marketing
  • Front-Tech
  • Uncategorized

SITEMAP

  • Disclaimer
  • Privacy Policy
  • DMCA
  • Cookie Privacy Policy
  • Terms and Conditions
  • Contact us

Copyright © 2023 PouroverAI News.
PouroverAI News

No Result
View All Result
  • Home
  • AI Tech
  • Business
  • Blockchain
  • Data Science & ML
  • Cloud & Programming
  • Automation
  • Front-Tech
  • Marketing

Copyright © 2023 PouroverAI News.
PouroverAI News

Welcome Back!

Login to your account below

Forgotten Password? Sign Up

Create New Account!

Fill the forms bellow to register

All fields are required. Log In

Retrieve your password

Please enter your username or email address to reset your password.

Log In