Disputes between two parties occur in almost all domains such as taxation, insurance, banking, healthcare, etc. The disputes are generally resolved in a specific forum (e.g., consumer court) where facts are presented, points of disagreement are discussed, arguments as well as specific demands of the parties are heard, and finally a human judge resolves the dispute by often favouring one of the two parties. In this paper, we explore the use of large language models (LLMs) as assistants for the human judge to resolve such disputes, as part of our DRAssist system. We focus on disputes from two specific domains -- automobile insurance and domain name disputes. DRAssist identifies certain key structural elements (e.g., facts, aspects or disagreement, arguments) of the disputes and summarizes the unstructured dispute descriptions to produce a structured summary for each dispute. We then explore multiple prompting strategies with multiple LLMs for their ability to assist in resolving the disputes in these domains. In DRAssist, these LLMs are prompted to produce the resolution output at three different levels -- (i) identifying an overall stronger party in a dispute, (ii) decide whether each specific demand of each contesting party can be accepted or not, (iii) evaluate whether each argument by each contesting party is strong or weak. We evaluate the performance of LLMs on all these tasks by comparing them with relevant baselines using suitable evaluation metrics.

Hurricane Ian made its way across Florida in late September 2022, causing tens of billions in estimated insurance losses due to wind and flood damage. Now, half a year later after the disaster, homeowners are still picking up the pieces and rebuilding with the payouts that have been slowly coming out from insurance policies. However, many have had the unexpected shock to learn that flooding was not a part of their homeowners insurance. Here we explain natural disasters, AI and insurance risk assessment. This event and many like it are stark reminders to both individuals and businesses that checking in with their insurance company to review insurance policies is something that needs to happen regularly, not because something may have gone unnoticed, but because things change.

With inflation sparking an increase in the cost of repairs, labor and claims, fees for insurance are similarly spiking across the board. Car insurance premiums rose 13.7% nationally over the past year, according to a study from Bankrate.com. Home insurance, meanwhile, climbed 12.1% year-on-year, Policygenius found. But Jonathan Matus argues that it doesn't have to be that way. He's the founder of Fairmatic, a company that's applying AI to -- at least according to him -- reduce risk in the car insurance industry.

In 1999, the world's first commercially obtainable colour video and digital camera telephone arrived within the type of the Kyocera VP-210 in Japan. A 12 months after its launch, worries over the fast rise in "up-skirt" voyeurism the telephones enabled unfold rapidly all through the nation, prompting wi-fi carriers to institute a policy guaranteeing the telephones they provided would characteristic a loud digital camera shutter noise that customers couldn't disable. The effectiveness of that measure is, to this present day, up for debate. However the occasion stays a helpful historical past lesson on the widespread adoption of expertise: new instruments make doing every part simpler, and never simply the great things. Speedy-based AI artwork turbines at the moment are having their VP-210 instant.

Documents have spent decades stubbornly guarding their contents against software. In the late 1960s, the first OCR (optical character recognition) techniques turned scanned documents into raw text. By indexing and searching the text from these digitized documents, software sped up formerly laborious legal discovery and research projects. Today, Google, Microsoft, and Amazon provide high-quality OCR as part of their cloud services offerings. But documents remain underused in software toolchains, and valuable data languish in trillions of PDFs.

People who are skeptical of artificial intelligence (AI) and machine learning (ML) often harbor fears of robots stealing jobs and human workers being replaced by automatons. But the reality is that AI is increasingly being applied across sectors not to replace our jobs but to enhance them. AI and ML applications are augmenting every facet of how we do business, giving knowledge workers superpowers to be more productive, capable and effective than ever before. As a founding partner at an investment firm specializing in technology, I have a ringside view of the ways that companies are integrating new intelligent software into their business practices, bringing breakthrough solutions to major problems and opening up new opportunities for revenue growth. With the ability to avoid hours of menial labor and solve problems that were previously insurmountable, companies can elevate human potential in unprecedented ways.

There's no denying that automation is a long-term goal for many industries. To automate a business is to transform it for the better, and there are so many different ways to achieve such a goal, particularly with AI (artificial intelligence). Even startup owners are looking toward automation sooner rather than later, as automation can help businesses scale without growing pains. That said, what about the world of insurance? While automation affects every aspect of the business sector, it's understandable to be confused about how it might impact the insurance space.

DroneUp, LLC, an autonomous drone supply platform and main drone companies supplier, at present introduced the appointment of Andy Thurling. Mr. Thurling is an completed industrial drone coverage and security skilled and the corporate's first Vice President of Airspace Innovation. On this function, Mr. Thurling will lead the event and execution of DroneUp's airspace and Unmanned Plane System Visitors Administration (UTM) methods. He will even assist create requirements and insurance policies that assist the corporate's path to industrial past visible line-of-sight (BVLOS) operations. Mr. Thurling beforehand was Chief Expertise Officer (CTO) at NUAIR, a New York-based nonprofit group targeted on the protected integration of uncrewed plane techniques (UAS) into the nationwide airspace.

Insurtech has become a major part of the insurance market, with record-breaking amounts spent on technology-based innovations that can revolutionise the sector. It's an area ripe for investment – with more than $1bn (£760m) spent every month on investment into insurtech startups in 2021, according to reinsurance broker Wills Re. The momentum that carried insurtech through 2021 is forecast to continue in 2022, with plenty of areas within the sector ready for disruption. But what should you be looking out for as the next big thing? Here are five tech trends that could transform the way we buy, sell and claim on insurance.

Insurance industry that operated with low profit margins, is facing increased competition both in terms of price and time to serve. This approach resonates with customers as 85% of customers want to buy insurance policies more quickly. How can insurers keep up? To keep up, Insurers are renewing their underwriting departments to price risk better and in less time. We explain why insurers must renew their underwriting approach and introduce four key technologies that enable more effective underwriting.