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<title>Artificial Intelligence | Insurance Advocate</title>
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<title>$50 billion opportunity emerges for insurers worldwide from generative AI’s potential to boost revenues and take out costs</title>
<link>https://www.insurance-advocate.com/2024/04/15/50-billion-opportunity-emerges-for-insurers-worldwide-from-generative-ais-potential-to-boost-revenues-and-take-out-costs/</link>
<dc:creator><![CDATA[Insurance Advocate]]></dc:creator>
<pubDate>Mon, 15 Apr 2024 08:31:42 +0000</pubDate>
<category><![CDATA[2024]]></category>
<category><![CDATA[April 2024]]></category>
<category><![CDATA[Artificial Intelligence]]></category>
<guid isPermaLink="false">https://www.insurance-advocate.com/?p=14698</guid>
<description><![CDATA[<p>AI technology offers insurance businesses large-scale financial potential from productivity gains, optimizing sales channels and digital advice, and delivering enhanced, personalized customer experience υInsurance businesses worldwide have a $50 billion dollar financial opportunity from generative AI to harness the technology in ways that could boost their revenues by as much as 20% and cut their costs by […]</p>
The post <a href="https://www.insurance-advocate.com/2024/04/15/50-billion-opportunity-emerges-for-insurers-worldwide-from-generative-ais-potential-to-boost-revenues-and-take-out-costs/">$50 billion opportunity emerges for insurers worldwide from generative AI’s potential to boost revenues and take out costs</a> first appeared on <a href="https://www.insurance-advocate.com">Insurance Advocate</a>.]]></description>
<content:encoded><![CDATA[<p class="p1"><strong>AI technology offers insurance businesses large-scale financial potential from productivity gains, optimizing sales channels and digital advice, and delivering enhanced, personalized customer experience</strong></p>
<p class="p1"><span class="s1">υ</span>Insurance businesses worldwide have a $50 billion dollar financial opportunity from generative AI to harness the technology in ways that could boost their revenues by as much as 20% and cut their costs by up to 15%, research from Bain & Company finds.</p>
<p class="p1">Bain’s report, It’s for Real: Generative AI Takes Hold in Insurance Distribution, (excerpted below) concludes that leveraging generative AI in insurance distribution has the potential to yield more than $50 billion in annual economic benefits for companies in the sector.</p>
<p class="p1">“For insurers, benefits due to generative AI will come through three routes,” said Bhavi Mehta, global lead of AI in Financial Services at Bain. “This includes raising productivity, lifting sales through more effective agents and digital advice, and better risk identification and targeting that will help both customers, agents and the enterprise. At Bain, we remain committed to helping our clients not only within insurance – but across industries– identify and realize AI’s full business potential.”</p>
<p class="p1">Generative AI will transform insurance distribution in four ways</p>
<p class="p1">Early use of generative AI within insurance suggests the technology will transform distribution in four ways, including:</p>
<p class="p1">• Agent productivity: The technology will help agents to navigate and produce content faster. It will reduce low-value interactions and provide coaching for more effective interactions with customers.</p>
<p class="p1">•<span class="Apple-converted-space"> </span>Customer self-service and sales support: An always-on virtual assistant will extend the availability of agents and help customers with product comparisons and digital purchases.</p>
<p class="p1">• Hyper-personalization at scale: Tailored conversations, content, and offers will more readily respond to individual customer needs.</p>
<p class="p1">• Business insights and decisions: Combining signals from unstructured data with structured data will yield new insights and aid in risk identification.</p>
<p class="p3">Managing the risks</p>
<p class="p1">Bain’s analysis also pinpoints key risk areas emerging from insurers’ developing use of generative AI including hallucination, data provenance, misinformation, toxicity, and intellectual property ownership.</p>
<p class="p1">“As with any nascent technology, there will be risks,” said Sean O’Neill, leader of Bain’s global Insurance practice. “To manage risks, insurers should adopt a responsible AI strategy that includes short-term priorities, as well as a long-term vision enabling companies to build valuable AI capabilities to redefine their business operations.”</p>
<p class="p1">Critical steps for insurance business leaders</p>
<p class="p1">As generative AI continues to evolve, Bain urges insurance companies to take several critical steps to adapt to the fast-developing technology. These include aligning across business units on how AI can support business strategy, determining what to build internally and what to buy from vendors, ensuring that delivery teams are cross-functional, and designing an operating model that is adaptable. <span class="s2">[</span><span class="s3"><b>I</b></span><span class="s4"><b>A</b></span><span class="s2">]</span></p>The post <a href="https://www.insurance-advocate.com/2024/04/15/50-billion-opportunity-emerges-for-insurers-worldwide-from-generative-ais-potential-to-boost-revenues-and-take-out-costs/">$50 billion opportunity emerges for insurers worldwide from generative AI’s potential to boost revenues and take out costs</a> first appeared on <a href="https://www.insurance-advocate.com">Insurance Advocate</a>.]]></content:encoded>
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<title>Vast majority of Insurance Customers Prefer Conversational AI and Messaging Experiences</title>
<link>https://www.insurance-advocate.com/2020/12/13/vast-majority-of-insurance-customers-prefer-conversational-ai-and-messaging-experiences/</link>
<dc:creator><![CDATA[Insurance Advocate]]></dc:creator>
<pubDate>Sun, 13 Dec 2020 06:02:47 +0000</pubDate>
<category><![CDATA[2020]]></category>
<category><![CDATA[December 13]]></category>
<category><![CDATA[Artificial Intelligence]]></category>
<guid isPermaLink="false">https://www.insurance-advocate.com/?p=12554</guid>
<description><![CDATA[<p>LivePerson, Inc. (Nasdaq: LPSN), a global leader in conversational AI, has announced the findings of its 2020 Survey of Consumer Preferences Around Insurance examining consumer attitudes and behavior around interactions with insurers, messaging, and conversational AI and commerce. The 2020 survey of more than 2,500 U.S., U.K., and Australian respondents reveals that the vast majority […]</p>
The post <a href="https://www.insurance-advocate.com/2020/12/13/vast-majority-of-insurance-customers-prefer-conversational-ai-and-messaging-experiences/">Vast majority of Insurance Customers Prefer Conversational AI and Messaging Experiences</a> first appeared on <a href="https://www.insurance-advocate.com">Insurance Advocate</a>.]]></description>
<content:encoded><![CDATA[<p class="p1">LivePerson, Inc. (Nasdaq: LPSN), a global leader in conversational AI, has announced the findings of its 2020 Survey of Consumer Preferences Around Insurance examining consumer attitudes and behavior around interactions with insurers, messaging, and conversational AI and commerce. The 2020 survey of more than 2,500 U.S., U.K., and Australian respondents reveals that the vast majority of consumers trust messaging experiences and chatbots to help them with insurance questions.</p>
<p class="p1"> The survey results point to the need for insurers to put AI-powered messaging options front and center to accommodate evolving behaviors. Nearly half (49%) of respondents said the pandemic has made them rethink their medical and life insurance policies, and 63% say they would use an insurer’s chatbot that could instantly answer questions, including those related to COVID-19 symptoms and testing.</p>
<p class="p1"> “The relationship between consumers and their insurers is built on trust, and the vast majority of consumers now clearly report that they trust insurance companies more if they provide the option to message to get advice, ask questions, and even make purchases,” said Robert LoCascio, founder and CEO of LivePerson. “This is a win-win for policyholders and insurance companies. Policyholders can engage whenever and wherever they want on the messaging channels they love using with family and friends, and insurers can leverage conversational AI to reduce call volume, boost self-service, and exceed customer expectations with an end-to-end digital experience tailored to their needs.”</p>
<p class="p2"><b>Key findings of LivePerson’s 2020 Survey of Consumer Preferences Around Insurance are:</b></p>
<p class="p1"> • Consumers say conversational insurance experiences are in high demand.</p>
<p class="p1">• 75% of consumers say they prefer to have a conversation with someone at their insurance company before making a purchase.</p>
<p class="p1">• 70% say they want the ability to securely text or message with their insurance company.</p>
<p class="p2"><b>Consumers express high levels of trust in Conversational AI and messaging for insurance.</b></p>
<p class="p1">• 70% of consumers say they trust an insurance company more if associates are readily available via messaging to give advice, answer questions, and help with purchases.</p>
<p class="p1">• 71% say they would also trust an insurance company more if it provided personalized service, which Conversational AI can help insurers deliver at scale.</p>
<p class="p1">• The vast majority of respondents say they trust chatbots to help them:</p>
<p class="p4">Provide a quote (76%)</p>
<p class="p4">Change address (75%)</p>
<p class="p4">Make a claim (71%)</p>
<p class="p4">Add a member to coverage (74%)</p>
<p class="p4">Calculate a rate (78%)</p>
<p class="p4">Provide a renewal quote (77%)</p>
<p class="p4">Tell them about waiting periods (82%)</p>
<p class="p4">Update billing information (76%)</p>
<p class="p2"><b>Consumers are much more likely to buy and continue service if given Conversational AI and messaging options.</b></p>
<p class="p1">• 63% said they were more likely to buy insurance from a company if they had the option to message them instead of just call.</p>
<p class="p1">• 65% said they are more likely to stay with an insurance company that offers this service.</p>
<p class="p1">• More than half (51%) say they’d purchase more from an insurance company that offered a chatbot concierge to help, as opposed to strictly self-serve.</p>
<p class="p2"><b>The world’s most innovative insurance brands, like Bupa and Zurich, have seen success deploying conversational experiences for their customers.</b></p>
<p class="p1">LivePerson’s 2020 Survey of Consumer Preferences Around Insurance was conducted in October 2020 via an online survey of 2,574 consumers aged 18 and older in the United States, United Kingdom, and Australia. Respondents were asked a series of questions related to insurance and customer care topics.</p>
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<title>Artificial Intelligence Review of Insurance Contracts – Are we there yet?</title>
<link>https://www.insurance-advocate.com/2020/10/20/artificial-intelligence-review-of-insurance-contracts-are-we-there-yet/</link>
<dc:creator><![CDATA[Guest Author]]></dc:creator>
<pubDate>Tue, 20 Oct 2020 06:46:21 +0000</pubDate>
<category><![CDATA[October 20]]></category>
<category><![CDATA[Artificial Intelligence]]></category>
<guid isPermaLink="false">https://www.insurance-advocate.com/?p=12530</guid>
<description><![CDATA[<p>by Joe Chvasta, JD, MBA, CPCU The use of Artificial Intelligence to review insurance contracts is growing as AI tools can rapidly compare a high volume of contract clauses and make human reviewers faster and more effective. First implemented in 2011, the technology automating the review of contracts has progressed dramatically, leading to the question […]</p>
The post <a href="https://www.insurance-advocate.com/2020/10/20/artificial-intelligence-review-of-insurance-contracts-are-we-there-yet/">Artificial Intelligence Review of Insurance Contracts – Are we there yet?</a> first appeared on <a href="https://www.insurance-advocate.com">Insurance Advocate</a>.]]></description>
<content:encoded><![CDATA[<p><strong>by <span class="s1">Joe Chvasta, JD, MBA, CPCU</span></strong></p>
<p class="p1">The use of Artificial Intelligence to review insurance contracts is growing as AI tools can rapidly compare a high volume of contract clauses and make human reviewers faster and more effective. First implemented in 2011, the technology automating the review of contracts has progressed dramatically, leading to the question if AI technology by itself is ready to totally automate the review of contracts or if it remains a tool to assist humans in their contract review.</p>
<p class="p1">Insurance companies are adopting AI contract review for greater efficiency.</p>
<p class="p1">Insurance companies are joining law firms and other large corporations by adopting AI for contract review due to its efficiency compared to using lawyers, paralegals and other persons. LawGeex, a leader in AI contract review, is used by three of the five largest insurance companiest. LawGeex estimates that contract review by AI saves 80% of the time and 90% of the cost and results in deals closing three times faster. Kira Systems, a provider with insurance company and law firm clients estimate cost savings at 60% while other sources estimate total cost savings at a still hefty 50%. One insurance company leading in the use of AI contract review is Swiss Re which writes about 20,000 contracts a year using an AI tool to compare single clauses against the entire data set expediting the underwriting process. Some in the industry believe that comprehensive contract review without AI is impossible. One analyst commented that an insurance company could not hire enough underwriters and lawyers to review a high volume of contracts with any depth unless they used AI.</p>
<p class="p3"><b>What is Artificial Intelligence?</b></p>
<p class="p1">Artificial Intelligence consists of many related technologies including: “Machine Learning,” a subset of AI in which computers use algorithms and statistical models to identify patterns in data and adapt with experience and without the need for reprogramming. Machine learning makes predictions based on data and uses techniques such as decision trees.</p>
<p class="p1">“Deep Learning,” a type of machine learning loosely modeled on the neural pathways of the human brain. Deep learning is a self-learning model where algorithms attempt to model high level abstractions in data and requires more computational power than other types of machine learning. “Natural Language Processing (NLP),” a type of machine learning with the ability of a computer to understand, analyze, manipulate, and potentially generate human language. NLP is useful for identifying and tagging phrases in a document. “Optical character recognition (OCR)” is a type of natural language processing.</p>
<p class="p3"><b>How does AI review contracts?</b></p>
<p class="p1">AI is used both to review individual contracts and a high volume of contracts. The process of contract analysis for a large volume of contracts typically involves five steps:</p>
<p class="p1">1. Importing contract documents into a database. This can be done multiple ways including drag-and-drop, upload directs, imports, etc.</p>
<p class="p1">2. The AI software automatically converts the files into machine readable forms. The software works with numerous document formats. Then OCR or another AI tool is used to extract key items and clauses as per specified by the user and tagged for further review.</p>
<p class="p1">3. Place the contracts with tagged clauses into a searchable repository. With some software the user may participate in the review before contracts are stored.</p>
<p class="p1">4. Use AI such as machine learning to identify patterns in the data and analyze them looking for variances from a set standard wording.</p>
<p class="p1">5. Provide customized reports with charts and summaries for almost any data point selected by the user.</p>
<p class="p1">By comparing many like clauses AI can identify the core concepts found in each clause and conversely, identify the variances from core concepts. For example, an insurance company may want to review all of the waiver of subrogation clause endorsements found in its policies to confirm that the waiver is mutual, the core concept of the clause. If the AI tool finds that some of these clauses lack mutuality it would flag these contracts for further review. Another example of a clause subject to review on a high volume in an insurance contract is a cure clause such as how long does the party at fault have to correct the default. AI can look for variations from the base wording on the number of days to cure a default and if there is a variance for further review flag it. Properly used AI would facilitate keeping a group of contracts uniform.</p>
<p class="p1">Human Review of flagged clauses. A human ultimately reviewing the contracts flagged by the AI tool is expected. At this time algorithms used by AI do not have the judgment for a nuanced read of a contract clause. Similarly, the algorithms lack the nuanced understanding of how conflicting contract clauses work together.</p>
<p class="p1">AI models have different approaches to review by a human. LexCheck streamlines the review process by automatically correcting contract provisions, highlighting issues for review and proposing possible fixes. LawGeex uses AI to analyze contracts one at a time where the user selects from a list of clauses and variations to require, accept or reject. The AI scans the contract to see what clauses and variations are present. The language at issue is highlighted with a green thumbs-up or red thumbs-down per the user’s guidelines.</p>
<p class="p1">3. Most providers of AI contract review allow users to review features and increase or decrease the level of human review. More human review will be more expensive. On the other hand, there are situations where additional human review may be necessary as when the policy language is vague or where the clause at issue may at some point be subject to regulatory scrutiny. In September 2020, Kira Systems adopted “Answers and Insights,” a smart field for contract review. Users can ask the software a question about the data, such as “will this policy renew automatically?” and receive a straightforward answer. Alternatively, the software also allows the reviewer to pick from pre-selected questions and choose answers in either yes/no or multiple-choice formats, a capability which users have long requested as a way to speed up the review process.</p>
<p class="p1">When is AI better?</p>
<p class="p1">The tremendous speed of AI in reviewing a high volume of contracts for uniformity allows it to quickly separate contracts with acceptable clauses from those needing further review. This is perhaps the greatest value of AI in contract view – simply reducing the number of contract clauses needing human review.</p>
<p class="p1">Another advantage is that the results of the AI tool derived from the data can be validated statistically. The data results would be able to estimate the accuracy of a model’s predictions on unobserved cases. Accordingly, the user would have an understanding of the likelihood of a certain event. For example, if the AI tool found that the original sample of insurance policies all had a mutual waiver of subrogation, AI can use the data from the sample to predict the likelihood of other policies with the same characteristics having the same mutual waiver of subrogation.</p>
<p class="p1">AI is also better when the language of the contract is in a language other than the human reviewer’s native language as it can translate the contract to the reviewer’s native language. The value of this is apparent when the reviewer is managing a large volume of contracts in multiple languages.</p>
<p class="p1">In insurance policies AI is especially valuable in flagging policy renewal dates so that they can be reviewed for changes before the regulatory deadline for policy revisions on a policy renewal. AI can also identify when an insurance policy requires a future obligation by the insurer, such as a dividend or return of premium. Likewise, AI can monitor contractual obligations by an insured including premium payments and changes required by a safety inspection without the need of a human to track compliance by the insured.</p>
<p class="p1">When are humans better? There’s a reason that current AI software for contract review is designed to have additional review by humans. Humans are better at understanding the nuances of a vague contract clause. There are other functions in the contract process besides review where humans are better than AI. Humans are better at strategy, creativity, judgment and empathy and the activities that use these tools including:</p>
<p class="p1">· Advocacy.</p>
<p class="p1">· Negotiation.</p>
<p class="p1">· Structuring of the initial contract.</p>
<p class="p1">· Making revisions outside of a defined template.</p>
<p class="p1">· Correcting or explaining contracts subject to regulatory scrutiny.</p>
<p class="p1">· Understanding the nuance of vague contract wordings.</p>
<p class="p1">· Understanding the nuance of contractual clauses that conflict with other clauses.</p>
<p class="p1">Humans are better when there is an issue with a regulatory or compliance matter. One of the issues with AI is understanding how the algorithm made the decision. In insurance this would be especially important when a policy is being non-renewed or cancelled. A human, typically working from written guidelines, can better explain their decision process to a regulator than an AI tool that used thousands of factors in its decision. The insurance company representative in this situation would have a difficult time explaining which factor or factors the AI tool found determinative.</p>
<p class="p1">The list of activities where humans are better is generally with the contract process itself. For contract review humans alone cannot match the speed and efficiency of AI in reviewing a high volume of contracts or even a single contract. The areas of contract review where humans are better involve nuance such as vagueness in a clause or vagueness due to conflicting clauses and this review can be done in conjunction with AI tools, too.</p>
<p class="p3"><b>Are we there yet?</b></p>
<p class="p1">The value of AI when reviewing similar clauses with a large volume of contracts is unmistakable. The question is what level of human review is necessary to ensure that the contracts under review are meeting the requirements of the insurance company and its regulators for acceptable language. One approach is to use AI for first and final review. In the initial review AI will separate the contracts that meet all user requirements from those requiring additional review. Then humans with or without further assistance from AI will review the clauses for corrections so that they are correct and uniform. Then AI will conduct a final review for uniformity.</p>
<p class="p1">Even as AI develops humans will continue to take the lead in creating new contracts where our strategy, creativity, judgment and empathy are not available to AI. Similarly, humans will continue to negotiate drafts of contracts. There is no answer to the question of “Are we there yet?” as it depends on what we are expecting AI to do. Once humans set the parameters, are we expecting AI to do a total review of a contract without further human involvement? Or are we expecting AI to tell us what’s wrong with the contracts by pointing out variances without having received human input during the review process? The question becomes how much thinking do we want AI to do when reviewing contracts? As there are no commonly accepted goals, I suspect that we will not have the answer to “Are we there yet?” anytime soon.</p>
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