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1、The Future of Insurance with Trusted Generative AICustom content for Salesforce by studioID2 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AIAI Benefits and Use Cases for Insurance With generative AI,both insurance company employees and customers are empowered with a powerful partner that drives b

2、etter experiences,all from natural language.Generative AI can automatically interpret and categorize customer inquiries,allowing employees to focus on resolving more complex issues that require human intervention.For customers,AI can instantly provide a detailed update and even explain the next step

3、s in the customer service process,all in a conversational tone that mimics human interaction.By assisting customers from the get-go with AI,the cognitive load on employees is reduced,so employees can provide more thoughtful and personalized service and also improve productivity.This not only enhance

4、s productivity but also reduces the cognitive load on employees,who can then provide a more thoughtful and personalized service.Each policyholder and client can receive hyper-personalized coverage options based on data about their household,property,or business data and financial goals.Insurance car

5、rier sales/distribution channel managers might leverage a virtual assistant to prep for broker meetings or develop customized communications based on agency performance or recent milestones.3 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AIMarketing:AI can create more personalized content,tailor m

6、essaging and offers,and even automate the creation of web pages and campaigns,significantly boosting campaign effectiveness and ROI.Service:AI can automatically generate responses to inquiries,compile detailed case summaries,and produce informative articles to broaden the knowledge base available to

7、 customers.Generative AI Benefits and Use CasesAn example is hyper-personalization.Generative AI can craft email subject lines and body copy that closely mimic human writing.By integrating these capabilities with predictive AI that analyzes customer behavior,insurers can create communications that a

8、re both timely and highly relevant to individual customer needs.An example is automated responses.By analyzing data from previous customer interactions,generative AI can instantly create precise responses tailored to customer queries.Additionally,AI can help refine chatbot responses and extend the c

9、apabilities of automated self-service platforms,making them more intuitive and helpful to users.4 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AISales and Distribution Management:Generative AI can summarize customer interactions and enhance client and account research efforts.Underwriting and Cla

10、ims:Generative AI models can analyze large amounts of structured and unstructured data to help automate routine tasks and augment identification potential risk patterns.An example is enhanced customer insights.Acting as a data analysis assistant,generative AI can delve into CRM systems to identify p

11、atterns and relationships that might not be immediately obvious.This allows agents to target high-value opportunities and adapt their strategies in real-time to the dynamics of customer relationships and market conditions,ensuring that efforts are always aligned with the most promising leads.Another

12、 example is producer performance.A territory sales manager can use generative AI to personalize marketing messages unique to each producer based on their prior activity and engagement as well as next best action through topics or programs to discuss at an upcoming meeting.For brokerages,generative A

13、I can help drive efficiency by automating alerts and communications for potential line of business attrition or loss of Broker of Record status.The US Bureau of Labor Statistics projects that the insurance industry could lose around 400,000 workers through attrition by 2026.Generative AI virtual age

14、nts will become particularly important as veteran underwriters and claims adjusters retire and make way for a less-experienced insurance workforce.Generative AI can automate tasks by developing templated emails for brokers as well as create notes and tracking activity for underwriters.Another exampl

15、e is claims fraud detection and prevention.Generative AI can be programmed to simulate and recognize fraudulent behaviors,ensuring that insurance companies are always a step ahead in safeguarding against new and evolving fraud tactics.5 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AILarge Languag

16、e Model(LLM):A type of AI algorithm that uses large data sets to understand,summarize,generate,and predict new content.LLMs can answer customer service questions,create personalized outreach,assist client research,and even generate code.Generative Pre-Trained Transformer(GPT):A neural network family

17、 that is trained to generate content.GPT models are pre-trained on large amounts of text data,which lets them generate clear and relevant text based on user prompts or queries.Hallucination:When a generative AI model produces new content that doesnt correspond to reality or its training data.Explain

18、ability/Mechanistic Interpretability:Aspect of AI that ensures the system is doing the right thing(e.g.,following predetermined rules,such as adhering to established credit criteria).Human in the Loop:Ensuring a human has oversight of a generative AI output and can give direct feedback to the model

19、in both the training and testing phases and during active use of the system.Ethical AI:AI that adheres to well-defined ethical guidelines regarding fundamental values,such as individual rights,privacy,nondiscrimination,and non-manipulation.Of all the technological innovations since the birth of the

20、Internet,artificial intelligence(AI)is in a class by itself.According to PwCs Global Artificial Intelligence study,AI could contribute up to$15.7 trillion to the global economy by 2030 as well as up to a 26%boost in GDP for local economies.And Gartner predicts that generative AI software spending al

21、one will soar to 35%by 2027.“Generative AI is not just a new tool in the insurance toolboxits a transformative force that redefines how we understand risk,customize policies,and engage with our customers,”says Evan Groot,global insurance go-to-market director at Salesforce.“Its about turning data in

22、to dialogue and predictions into partnerships.”Key AI Terms and DefinitionsThe AI Revolution6 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AIAI and Insurance TodayAlthough the concept of AI has been around since the 1950s,most industries didnt begin exploring AI for basic tasks like data manageme

23、nt and customer service until the 1980s and 1990s.The explosion of big data and the refinement of machine learning led to more sophisticated AI applications.With generative AI,we are now seeing insurers increasingly invest in AI as a key component of their operations.Today,generative AI is at the fo

24、refront of reshaping how insurance companies interact with their customers,enhancing analysis of risks,and streamlining processes across the value chain.This shift is driven primarily by the technologys ability to analyze massive datasets more efficiently than ever before,finding new patterns and in

25、forming smart decisions that can ultimately determine profitability of insurance operations.For example,generative AI can be used to personalize policy coverages and pricing,enhance customer service through chatbots and virtual assistants,and improve the accuracy of risk assessment models.The adopti

26、on of generative AI in detecting fraud and automating claims processes cannot only reduce operational costs but also improve customer satisfaction and trust.7 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AIInsurers have a remarkable opportunity to create substantial value and realize the potentia

27、l of gen AI by making well-thought-out investments aligned with their respective business strategies.Source:DeloittePredictive vs.Generative AIThe Generative AI DifferenceAI is the broad concept of having machines think and act like humans.But there are different types of AI,including predictive AI

28、and generative AI,both of which help your teams work smarter and faster by automating routine tasks.Predictive AI is designed to forecast outcomes based on historical data,and its primary goal is to predict future events or behaviors by analyzing patterns and trends.Well-known use cases include prop

29、ensity to buy,claims fraud detection,and storm damage models.Generative AI involves training a model to generate new data that is similar to the training data it was given.The output is typically some form of content from text to images to video and even computer code.While generative AI also relies

30、 on historical data,its primary goal is to learn underlying patterns of past examples without replicating the examples themselves.With generative AI,you can create diverse customer engagement materials or even assist in territory sales management.8 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AII

31、nsurance companies should establish strict governance as well as a dedicated compliance framework for generative AI,ensuring that these systems are not just effective but also legally sound.Some challenges and how to address them include:Risk management:Insurance companies should develop generative

32、AI models in tandem with risk experts to tailor outputs to regulatory standards.Data privacy and security:Insurance companies must enforce strict data governance policies,use advanced encryption methods,safeguard against using public LLMs,and continuously update their security protocols to ensure th

33、at employees dont share sensitive customer data.Bias and fairness:Regular auditing of generative AI models is essential to check for bias,risk of hallucinations,or language toxicity.Training these systems with diverse datasets and establishing guidelines to ensure decisions are fair and equitable is

34、 crucial.Change management:Integrating generative AI into existing insurance infrastructure requires a strategic change management approach encompassing clear communication,stakeholder engagement,and a phased implementation of generative AI models.AI expertise:Insurance companies should invest in co

35、ntinuous upskilling and training programs to build AI expertise across their workforce while also tapping into new talent pools through collaborations with academic institutions and tech companies.Generative AI Challenges9 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AIResponsible AI is AI with“g

36、ood intentions”and designing,developing,and deploying AI with good intentions is the best path forward for earning trust.Below are five key guidelines for the development of trusted generative AI:1.Accuracy:Deliver verifiable results that balance accuracy,precision,and recall in the models by traini

37、ng models on your companys trusted customer data.Communicate when there is uncertainty about the veracity of the AIs response and enable users to validate these responses.2.Safety:Make every effort to mitigate bias,toxicity,and harmful output by conducting bias,explainability,and robustness assessme

38、nts.Protect the privacy of any personal identifying information present in the data used for training and create guardrails to prevent additional harm.3.Honesty:Respect data provenance and ensure that you have consent to use the data.Insurance companies must also be transparent that AI has created c

39、ontent when it is autonomously delivered.Building a Trusted,Responsible,Generative AI Strategy10 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AI Be responsible Be accountable Be transparent Be empowering Be inclusive Guidelines for building trust4.Empowerment:There are some cases where it is best

40、 to fully automate processes but there are others where AI should play a supporting role to the human or where human judgment is required.Identify the appropriate balance to“supercharge”human capabilities and involvement.5.Sustainability:Develop right-sized models,where possible,to reduce your carbo

41、n footprint.When it comes to AI models,larger doesnt always mean better:In some instances,smaller,better-trained models outperform larger,more sparsely trained models.11 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AIA comprehensive data integration strategy is critical for insurance companies be

42、fore implementing generative AI.The challenge is that most firms have islands of trapped data across their organization,whether in data lakes or core systems.AI initiatives can(and likely will)falter without connected and harmonized data,leading to inefficiencies and suboptimal outcomes.Companies sh

43、ould:Integrate disparate data from multiple sources,ranging from customer information and claims history to quote activity or marketing engagement and financial data,into a single,unified repository for comprehensive analysis and accurate AI-driven insights.Enhance interoperability between departmen

44、ts and systems within the organization to ensure a seamless flow of information and enable effective deployment of AI technologies.Identify patterns and trends through advanced analytics to benefit risk assessment,fraud detection,and personalized customer service.Build a scalable data infrastructure

45、 to accommodate their growing data needs as AI capabilities expand;this will allow an organization to adapt and evolve its AI strategies over time.The Foundation of Generative AI is Data12 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AISet clear objectives:Define what you want to achieve and ensu

46、re alignment with your business goals and ethical standards.Be sure to develop metrics and thresholds for success,such as error rate and latency during pilot projects.Establish regular monitoring of AI systems to measure performance against objectives and be prepared to iterate on your strategy base

47、d on feedback and measured outcomes.Engage stakeholders:Involve them from the start,and bring in people from various departments,whether they are directly involved.You want the most holistic view of AIs potential impact as possible.Assess technology needs and infrastructure:Identify the types of gen

48、erative AI(like natural language processing,image generation,etc.)that are most relevant to your objectives.Determine if the current IT infrastructure can support generative AIs computational demands or if upgrades are necessary.Assess data readiness:Evaluate the quality and quantity of your data an

49、d improve data collection and management processes,if necessary.Handle data responsibly by ensuring that data governance and ethical standards are in place.Implementing Your Generative AI Strategy13 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AI“Whenever new technologies emerge,I think first abo

50、ut the consumer or end user.The majority of(AI)technology uses thus far have been beneficial to the back office and middle office,but very little has occurred in terms of AI uses,thus far,have been for front-end customers.If you focus too much on the back end,then youre going to lose customers and w

51、aste all that time making things more efficient.You need to innovate on the front end as well.”Philip Benton,Principal Analyst,Financial Services,OmdiaDespite the best safeguards against fraud or data leakage,the reality is that bad actors exist.Insurance companies need to be extra cautious and dili

52、gent to ensure quality and limit risk.Recommended oversights include:Conduct regular security audits and updates and keep software current to best protect against new threats.Review relevant regulations regarding data privacy,intellectual property,and AI ethics.Develop or update policies that reflec

53、t ethical AI usage,especially in the context of generative models that can create new content.Also imperative is striking the right balance between automated processes and human oversight.Start with automating smaller,low-risk tasks,then gradually scale up as the system proves its reliability and ef

54、ficiency.Data Security and Human Oversight14 THE FUTURE OF INSURANCE WITH TRUSTED GENERATIVE AIVendor selection Evaluate ethical standards:Choose vendors who share your commitment to ethical AI practices.Assess technical expertise:Ensure the vendor has the necessary technical expertise and experienc

55、e to implement AI responsibly.Consider long-term support:Look for vendors who offer robust support and maintenance post-implementation.Implementation Take an iterative approach:Allow employees to experiment with generative AI on internal systems so they can build their skill sets and become more com

56、fortable.Continuously monitor and evaluate:Regularly monitor generative AI systems and their outputs to ensure they operate as intended and adhere to ethical standards.Conduct employee training:Educate employees on how to interact with AI systems and understand their outputs.15 THE FUTURE OF INSURAN

57、CE WITH TRUSTED GENERATIVE AIWhy Now for Generative AI?Generative AI will fundamentally change the insurance industry and society in a positive way.New roles will be created,such as generative AI security or generative AI customer service.Generative AI can make it easier to help each customer with l

58、ong-term financial planning,decide when to pay off their mortgage,or how to grow their retirement savings.The imperative is to learn and keep pace with generative AI technology.For insurance carriers,agencies,and brokerages,acting now will offer opportunities to start small,iterate,learn,and quickly

59、 benefit from the efficiencies that generative AI drives.Start by identifying pain points in your customer and employee journeys to understand where generative AI can produce the most benefit to your organization.By improving personalization and policyholder/client experiences,insurance firms can fu

60、ture-proof and grow their book of business over the long term.“Let your mind wander and say,how do we put generative AI to work in a meaningful way for the business?If you spend some time understanding those concepts and how generative AI can improve experiences for your customers,then you cant help

61、 but get super excited really fast.”Evan Groot,Senior Director,Insurance Industry Advisors at SalesforceAbout Salesforce for Financial ServicesSalesforce is the worlds#1 AI customer relationship management platform.Our purpose-built banking solutions span retail,commercial,mortgage and lending,and c

62、orporate investment banking and are designed to help organizations grow and maintain trusted relationships,personalize engagement,and scale service while reducing operational costs.Learn moreLEARN MOREstudioID is Industry Dives global content studio offering brands an ROI rich tool kit:Deep industry

63、 expertise,first-party audience insights,an editorial approach to brand storytelling,and targeted distribution capabilities.Our trusted in-house content marketers help brands power insights-fueled content programs that nurture prospects and customers from discovery through to purchase,connecting brand to demand.