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When Lawsuits Are Investments. Uncovering the Pernicious Toxicity of Litigation Funding - Risk & Insurance
When Lawsuits Are Investments. Uncovering the Pernicious Toxicity of Litigation Funding
Factors like the increasing popularity of third-party litigation funding are contributing to rising litigation costs in the U.S.
Litigation costs are on the rise across the U.S.
These increased costs have an impact on federal, state and local governments — and on insurance carriers and policyholders.
One of the key drivers of increasing litigation costs is the rapid rise in popularity of third-party litigation funding (TPLF), a practice defined by the U.S. government as “an arrangement in which a funder who is not a party to the lawsuit agrees to help fund it.”
These arrangements often keep the identity of the funder a secret from the rest of the parties involved with the lawsuit, meaning the hidden entities behind third-party litigation funding could be anyone, anywhere — including bad actors with malicious agendas.
Foreign-sourced money being washed through TPLF schemes is a growing concern, especially with the privacy privileges granted to the funders.
And even without the fear of a shadowy quasi-government figure or political group with ulterior motives providing funding, the rules for third-party litigation funding lack transparency.
It is possible, for example, that an entity could fund part of a lawsuit without the knowledge of the judge, attorneys, plaintiffs and defendants.
If the involved parties in the lawsuit don’t know of the existence of the funding firm, they also may not be aware of its influence over the lawsuit. While some funding firms are interested in the large profits they stand to make if the lawsuit succeeds, others may have more nefarious motives.
A webinar held by the Travelers Institute addressed the topic of rising litigation costs and its key drivers.
Abi Potter Clough
"Insurance fraud is a huge problem in the United States"
A recent study has revealed concerning trends regarding the tolerance for insurance fraud among certain demographic groups in the US.
The survey published by Verisk and the Coalition Against Insurance Fraud found that Americans aged 45 and younger display a higher tolerance for insurance fraud, with some even expressing envy towards those who commit such acts.
In contrast, 87-96% of older respondents considered insurance fraud a crime, compared to only 75% of those under the age of 45. The percentage contin
"The E&S market is on the path to becoming overwhelmed"
The property and casualty (P&C) marketplace currently does not have the capacity to satiate demand from clients, which is driving more and more policyholders to the excess and surplus (E&S) industry, according to one expert. This increased interest may not be sustainable in the long term and could cause some major issues within that sector.
"The E&S market is on the path to becoming overwhelmed,” said Martha Bane (pictured), property practice leader at Gallagher.
In a conversation with Insurance Business, Bane spoke about why the E&S market has been able to absorb this heightened demand so far, what the impact of a major hurricane or natural catastrophe might look like later this year and the importance of finding suitable alternatives in traditional markets for clients.
“London carriers have been stepping up to the plate”
Since standard markets have pulled back this year in providing P&C coverage and reduced the amount of capacity being offered, clients had nowhere to go but to E&S providers.
“And they have probably written more business this year than they have in the past 20 years,” said Bane.
While these carriers may have filled large gaps in coverage, they have generally done so at a more expensive rate than what would be offered in the standard market..
Bane also noted how working with E&S carriers sacrifices some of the necessary interpersonal connection involved in insurance dealings.
Divided Appellate Panel Upholds Total Loss Valuations Using CCC Software
An insurer that used CCC Intelligent Solutions software to determine the payout for a claimant’s vehicle did not violate a Florida law that sets forth only three methods that auto insurers may use to determine actual cash value, a divided panel with the 11th Circuit Court of Appeals ruled.
In a 2-1 decision Monday, the appellate panel affirmed a ruling by the US District Court for the Southern District of Florida that dismissed a putative class action lawsuit filed against Safeco Insurance Co. of Illinois. Policyholder Gina Signor alleged that Safeco failed to comply with Florida Statute 626.9743 when it used CCC to determine a total loss payout for her 2014 Lexus.
“The meaning of this statute is a question of first impression in our Circuit,” the majority opinion says. “Further, we have no authoritative interpretation of it from Florida’s appellate courts to guide us.”
Class action lawsuits alleging improper valuation methods have been costly for auto insurers in recent years. Last month, a federal judge gave preliminary approval to a $2.3 million settlement in a class-action lawsuit against USAA Casualty Insurance Co. for allegedly underpaying for taxes on totaled vehicles.
In 2021, American Family Mutual Insurance agreed to pay $5.7 million to settle a lawsuit that alleged it had underpaid total loss claims in Washington state by using a “typical negotiation discount when determining actual cash values. PEMCO Insurance Co. also agreed in 2021 to pay a $14.1 million settlement for using a similar discount in Washington.
The decision in Signor’s case may save Safeco from a similar costly settlement.
Safeco determined that Signor’s vehicle was a total loss after an accident. It used CCC’s One Market Valuation system to calculate the value of that loss.
[Ed. note: significant and innovative collaboration] Tokio Marine introduces Global Digital Market Intelligence Platform
Tokio Marine Holdings, Inc. ("Tokio Marine") introduced a group-wide market intelligence platform in June 2023 to support operations related to collaboration with external companies. The system allows the group to share information, including the status of search and scouting for potential future business partners, as well as meeting minutes. As open innovation is accelerated, the platform fosters efficiency, streamlining the search process for startup companies.
In today's rapidly evolving landscape, the Insurtech sector, which combines insurance and technology, is experiencing remarkable growth globally. Tokio Marine actively pursues collaborations with Insurtech companies, recognizing their immense potential to drive the development of new products and innovation within its insurance operations.
Previously, the absence of an information sharing system meant that Tokio Marine's group companies worldwide conducted searches for potential business partners independently. This decentralized approach resulted in scenarios where multiple group companies unknowingly engaged with the same startup companies. To address this issue, the platform was co-developed with Tällt Ventures, building upon its Sønr Platform, a company database with over 2 million companies with cutting-edge technologies highly compatible with the insurance industry. Group companies can now seamlessly share information on company searches on the platform.
Besides information sharing on the platform, the platform allows information management through assigning attributes information tags to each external company. Each user can also customize the information display at the home screen to facilitate effective use of the system.
Tokio Marine Holdings commented, "The introduction of this system will allow us to simultaneously facilitate corporate search and horizontal development of collaboration. By leveraging the expertise of our Global Digital Innovation Labs, we aim to accelerate open innovation throughout the group."
Commentary/Opinion
Understanding the impact of automation in claims
The primary driver of any change is effective and efficient technology. However, as most know, the insurance space is a little different than other industries. At its core, it’s transactional where it needs to be transformational. Therefore, any implementation of technology must create efficiency, effectiveness and reimagine processes.
As a result, the industry has entered a new era of claims management, sometimes referred to as Claims Management 2.0. This revolution uniquely impacts each insurance stakeholder through next-generation engagement.
Policyholder point of view
Claims automation looks a little different from the policyholder perspective. While the central focus is on information sharing, the goal remains a customer-centric service approach. Automation enables this by establishing an efficient and accurate claims process.
One key accomplishment is the capability to push data into estimating software in real time. Another benefit is easily assigning adjusters in the field based on location, capacity, skillset and licensing requirements. This is especially true when deploying adjusters to catastrophe zones. Technological advances simplify pulling resources and moving them forward to aid the policyholder in a thoughtful and timely manner.
Communication with the policyholder is also enhanced. By automating initial contacts, acknowledgment letters and scheduling, the policyholder benefits from streamlined processes. Robotic process automation (RPA), or bots, assist with more of the mundane tasks in the claims process and fill the gap between legacy systems to improve operational efficiency and the overall customer experience. Some of these functions include:
Integrating and transferring data from one platform to another
Reconciling and verifying claims data using multiple sources, including regulations and compliance standards
Opening and gathering data from emails and PDF files and inputting it into the claims management system
Analyzing images, audio and documents throughout the claims process
Using workflow automation with set rules for fully automated processes and policyholder reminders
Implementing smart contracts enabled by blockchain technology to instantaneously authorize payments to a financial account
Policyholders are quickly seeing that this integration of technology doesn’t discount the human element. In fact, it digitally enables the human touch or what has been termed human-in-the-loop automation. It’s about finding a balance between convenience, decision-making and sensitivity. Right-touch service can boost insurer loyalty, which is critical to retaining policyholders.
George Burgee (gburgee@johnseastern.com) is the Director of Operations – Field Adjusting & Catastrophe Services for Johns Eastern
Responsible AI: A Mandate In Finance And Insurance
AI is rapidly becoming an essential technology for companies in every industry, and the finance and insurance industries are no different. AI is already being used to help such businesses stand out from competitors. Fintech companies are using it to automate back-office processing and improve customer service. Traditional financial services companies are using it in trading and to optimize back- and front-office operations. Insurance companies use AI for everything from underwriting and pricing to claims processing and measuring the detailed behaviors of individuals.
As all of these trends accelerate, the companies that can effectively adopt AI will likely leave behind the companies that can’t.
But for all of its potential, there are still huge limitations to AI technologies today, and the massive misconceptions about generative AI only make matters worse. For instance, the generative AI currently dominating headlines is powered by a large language model (LLM) called GPT-4, on which ChatGPT is built. Such models suffer from problems including biases in their training data, an inability to explain where they get information and a lack of commonsense reasoning. ChatGPT specifically has been shown to present wrong information as fact and give unpredictable responses when facing new situations. Although such errors may seem minor in a school paper or advertising copy, the bar is much higher when it comes to financial services, health and other regulated arenas.
A good practice is to use human relevance feedback to train models with more curated and well-labeled data designed to provide “adversarial” feedback as the LLM is built and used. But this takes time and iteration and is expensive, underscoring the need for companies to have a human-centric AI strategy—what we refer to as “experiential AI” at the Institute for Experiential AI (EAI) at Northeastern University. The “AI haves” using AI—such as Google, Microsoft, Amazon, Meta and OpenAI—know that human intervention is the only way to keep the algorithms on track.
Usama Fayyad Executive Director, Institute for Experiential AI at Northeastern University, Founder and Chairman, Open Insights
AI in Insurance
Generative AI’s Impact on Insurance Coverage: An Interview with ChatGPT-4 and Coverage Counsel on What Policyholders Should Be Doing Now
Generative AI is transforming our economy in previously unimagined ways, with Goldman Sachs estimating a $7 trillion (7%) increase in global GDP by virtue of this ecosystem. Insurance is but one sector that will be impacted, with new products, services and opportunities for efficiencies being the most obvious benefits. For insight into the insurance implications of this technology, we asked AI oracle du jour ChatGPT-4 the top three ways it believes generative AI will impact policyholders.
Here’s what it said:
By analyzing a broad range of data, AI could create personalized policies with coverage and pricing that accurately reflect each policyholder’s risk profile. This could lead to better coverage and potentially lower costs for many policyholders.
The use of AI in claims processing could significantly speed up the time it takes for policyholders to receive payouts. Automated systems could review claims, assess damages, and approve payouts quickly and accurately.
Generative AI could aid in understanding and interpreting policy language and terms. The AI could be trained on insurance law and policy documents to generate explanations and clarifications in plain language.
While there may ultimately be some opportunities for policyholders to use generative AI directly in their policy underwriting and insurance claims, our focus here is on the insurable risks posed by generative AI. Any policyholder starting to incorporate generative AI into its business operations (or whose employees may be doing so) should take a step back to evaluate its exposures and existing insurance programs and to assess any insurable gaps in coverage.
Organized by generally applicable lines of insurance, some of the chief exposures that have been identified as the risks of generative AI include the following:
Professional Liability/Errors & Omissions Insurance
Using generative AI to answer questions or develop work product is of course not without risk. As has become well-known, current generative AI models may create erroneous or “hallucinatory” output that lacks a factual basis—and may even justify its output with additional fabricated sources. An attorney already learned this lesson the hard way when he filed briefs citing non-existent legal authorities provided by ChatGPT. The attorney was admonished by the Court and ultimately sanctioned for using the program and failing to review its work.
Leveraging GPT in Insurance Automation
The power of artificial intelligence continues to grow at an amazing rate. Just look at the rapid advancement of ChatGPT. The “GPT” in ChatGPT refers to generative pre-trained transformer language models, a new kind of AI more commonly referred to as generative AI. The practical applications of this type of advanced AI are frequently referred to as ‘Applied AI’.
By expanding on deep learning to enable instant understanding of complex documents, this new wave of AI presents a number of great opportunities for automation in the insurance industry. These were some of the topics that were discussed at the recent panel hosted by Insurtech Insights “How Will ChatGPT Impact Insurance?”. Participants were Instabase Insurance Leader Bastiaan de Goei, Alchemy Crew CEO Sabine Van der Linden, and Paul Tyler – CMO at Nassau Financial Group.
Moving from Deep Learning to Large Language Models
Deep learning is a subset of machine learning that has been popular for a few years now. Deep learning models are trained on dozens, hundreds, or even thousands of data points. The more data a deep learning model ingests, the better it becomes at solving highly complex problems in a similar way to how the human brain works.
In a more recent development, Generative AI takes things a bit further. The underlying technology behind generative AI is large language models. Large language models are a form of Deep Learning models but trained on far more data. As a result, they are smarter and require no additional training on specific document types. Instead, large language models understand new and complex document types on the first submission. This leap forward in AI allows for instant automation of many insurance processes which the panel discussed, including claims processing and commercial submissions automation.
Advantages of Instabase Modularity
As Bastiaan discussed, Instabase is designed as a modular platform. This unique approach allows Instabase to quickly leverage new technologies such as generative AI as they become available. The platform provides a future-proof way for clients to access the latest in technology without the costly ‘rip-and-replace’ scenarios that often occur when organizations need new tech.
The Instabase platform offers advanced security and enterprise-level certifications, giving clients confidence as they make use of all available Applied AI technology.
Reshaping Insurance with Generative AI and ChatGPT: Use Cases and Considerations
An illustration of high-value use cases in underwriting and claims management
Insurance firms are data-rich and time-starved. An Accenture report found that most insurers process only 10–15 percent of their internal data. We can assume that this includes:
- Underwriters who create new insurance policies
- Claims personnel who investigate customer claims
- Salespeople who cross-sell and up-sell insurance products
- Customer service staff who deal with client inquiries
In this post, we will focus on the underwriting and claims functions. Generative AI is a game-changer in these areas because it can make insurers truly data-driven.
Generative AI is the technology behind ChatGPT and other Large Language Models (LLMs). An LLM learns from vast amounts of existing data to create new data.
When trained on company-specific data, an LLM can act as an internal search engine. It speeds up information retrieval and gives staff the data they need to make informed and timely decisions. An internal ChatGPT can also summarize complex information and generate marketing content and customer communication.
Raj Shroff, AI consultant & educator. Writing about how AI , business and society. LinkedIn
InsurTech/M&A/Finance💰/Collaboration
Conning and Its Affiliates to Be Acquired by Generali; Transaction Enhances Firms' Long-Term Growth Plans
Conning and Its Affiliates to Be Acquired by Generali; Transaction Enhances Firms' Long-Term Growth Plans
- Conning and its Affiliates Will Continue to Operate under Current Leadership and Brands**
- New Strategic Support Expected from Generali to Accelerate the Strategy for Conning and its Affiliates
- Conning's Partnership with Cathay Life to Continue
Conning Holdings Limited ("Conning and its Affiliates1"), a leading global asset manager serving the needs of insurance company and institutional clients, today announced that it will be acquired by Generali Investment Holdings ("GIH"), an entity comprising the majority of asset management activities of Generali Group ("Generali"). Conning and its Affiliates will continue to execute their growth strategies with support from the firm's current owner, Cathay Life Insurance Co. Ltd. ("Cathay") and Generali.
"This is a highly complementary business combination that presents exceptional long-term opportunities for Conning and our Affiliates – maintaining our firms' ability to provide performance and service to our clients while extending our global investment capabilities," said Woody Bradford, Chief Executive Officer and Chair of the Conning Holdings Limited Board.
"We believe this transaction provides stability for our clients and employees, maintains continuity of leadership and strategy, and will generate new collaboration opportunities with Generali and its affiliates to strengthen both firms."
Insurtech scaleup Qover raises $30 million to drive growth and profitability
Brussels-based insuretech scaleup Qover, has raised $30 million in a Series C round that is expected to fuel continued growth, support the development of additional partnerships, and ultimately, achieve profitability.
Announced earlier this week, Qover has most recently partnered with UK fintech giant Monzo, and the $30 million Series C up round drew the support of Anthemis, Alven, Kreos Capital, and Zurich Global Ventures.
Offering an embedded insurance product, or rather, what the company differentiates itself from competitors as an insurance orchestration platform, because Qover’s offer is able to be seamlessly integrated with any insurer or broker, the uptake has resulted in collaborations with Revolut, Qonto, ING, Monese, Fisker, Nio, Volta Trucks, Niu, and naturally, Monzo, resulting in the coverage of some 2.5 million individuals across 32 European countries.
“Our ability to navigate and quickly adapt to the changing tech landscape has been instrumental in attracting top-tier clients and investors,” says Qover CEO and co-founder Quentin Colmant, “We are incredibly proud of what our team has accomplished. With their resilience as our driving force, we’re excited about the opportunities that lie ahead as we continue to push boundaries and shape the future of insurance.”
Since 2016, Qover has raised a total of just shy of $72 million.