Instructional Module 1 for course, Developing Technology Foresight: Case Study of AI in InsurTech

McShane, Michael

Pinto, C. Ariel

English

Tahami, Hesamoddin

Fakhravar, Hengameh

Old Dominion University

Old Dominion University ODU Digital Commons Developing Technology Foresight: Case Study of AI in InsurTech Open Course Materials 2022 Module 1: Introduction to Technology Foresight, Risk Management, and InsurTech Michael McShane Old Dominion University C. Ariel Pinto Old Dominion University Follow this and additional works at: https://digitalcommons.odu.edu/oer_developingtechnologyforesight  Part of the Artificial Intelligence and Robotics Commons, and the Insurance Commons Repository Citation McShane, Michael and Pinto, C. Ariel, "Module 1: Introduction to Technology Foresight, Risk Management, and InsurTech" (2022). Developing Technology Foresight: Case Study of AI in InsurTech. 1. https://digitalcommons.odu.edu/oer_developingtechnologyforesight/1 This Modules is brought to you for free and open access by the Open Course Materials at ODU Digital Commons. It has been accepted for inclusion in Developing Technology Foresight: Case Study of AI in InsurTech by an authorized administrator of ODU Digital Commons. For more information, please contact digitalcommons@odu.edu. Developing Technology Foresight: Case Study of Artificial Intelligence (AI) in InsurTech Module 1Introduction to Technology Foresight, Risk Management, and InsurTechAcknowledgementsThis material was made possible through a grant from theSpencer Educational Foundation. Students interested inpursuing a career in Risk Management and Insurance may beeligible to apply for a Spencer Scholarship. To learn more,visit: www.spencered.org.Module 1 Objectives1. Discuss Importance of Technology Foresight in the Insurance   Industry2. Understand The definition of AI and ML, their concepts, and application area3. Discuss State-of-art in InsurTech and current problemsModule 1 Learning Outcomes: Upon completion of Module 1, students will be able to explain key concepts of AI, the Insurance Industry, and summarize the current and future roles of AI in InsurTech. In particular:1. Importance of Technology Foresight in the Insurance Industry2. The definition of AI and ML, their concepts, and application area3. State-of-art in InsurTech and current problemsTopics in Module 11. Fundamentals of Technology Foresight2. Fundamentals of AI3. Introduction to InsurTechIce breakerWhat is your major?If that wasn’t your major, what would your major be?Besides graduating, what is your number one goal for your remaining time at college?1.1. Fundamentals of Technology Foresight• Introduction to principles of Technology ForesightTechnology foresight could be described as readiness to deal with long-term issues inscience, technology and innovation systems using new toolsTechnology foresight is defined today as a “process involved in systematically attempting tolook into the longer-term future of science, technology, the economy, the environment andsociety with the aim of identifying the emerging generic technologies and the underpinningareas of strategic research likely to yield the greatest economic and social benefits”3Introduction to principles of Technology Foresight❖ There are five important aspects to this definition:• Attempts to look into the future must be systematic to be called “foresight”. This distinguishes foresight from the endogenous scenario building that we are all engaged in when planning our everyday lives.• Foresight must be concerned with the longer term, which is generally considered to be beyond normal planning horizons. Foresight time horizons therefore typically range between five and thirty years.• Science/technology push should be balanced with market pull. Whilst this is a rather crude way to think about the innovation process, the point is that technology foresight should not be dominated by science and technology (S&T) alone. Attention also needs to be paid to socio-economic factors that are well known to shape innovationsIntroduction to principles of Technology Foresight (cont.)• Foresight concentrates on emerging generic technologies where there is a legitimate case for government support. This is because companies are often unwilling to fund the strategic research that underpins emerging generic technologies.• Attention must be given to social impacts, not just those concerned with wealth creation. This has led to some recent foresight exercises to adopt more problem-oriented perspectives from the outset, for example, focusing upon issues such as crime prevention, education and skills, ageing societies, etc.Is Foresight the same as Forecasting?• Forecasters aspire for precision in their attempts to predict how the world might look atsome point in the future.• By contrast, foresight does not seek to predict instead, it is a process that seeks tocreate shared visions of the future, visions that stakeholders are willing to endorse by theactions they choose to take today.Is Foresight the same as Forecasting?(cont.)(Picture Focus on Technologies)Why is it important to the insurance industry?• Insurance is an information driven industry. New sources of information as well as processingtechnologies will take underwriting to an entirely new level and are enhancing insurers’ abilityto manage risk and offer more sophisticated and personalized policies.• The insurance industry is viewed by many as being very conservative and certainly not agileand progressive. Many insurers are hindered by outdated and costly legacy IT systems whichare entrenching inefficient back-office processes such as claims processing, invoicing andparticularly workflow. Emerging technologies (Cloud-based IT solutions, application programinterface(API)) provide many opportunities to revitalize back-office operations in the insuranceindustry.Why is it important to the insurance industry? (cont.)• Ensuring competitiveness for the future and sustainable innovation• Differentiating the company for future competition• Cultivating existing technology or knowledge areas• Identifying new technology or knowledge areas (‘white spaces’)• Not to miss or oversee new trends or ‘weak signals’• Accompanying outsourcing or cooperation strategy• Generating new businesses or new technological knowledge for the development of new businesses• Anticipating technological discontinuities or global changes so that the firm is not outrun by new paradigms or new competitorsHow can it be helpful in the future?• Cyber security of data and information remains a very high priority forcustomers, government and the industry, including insurers and otherfinancial institutions• New types of data from IoT devices and social media, coupled with AIand analytics, enable insurers to develop much more sophisticated riskprofiles of individuals, enabling personalized policies.1.2. Fundamentals of AIIntroduction to Artificial Intelligence  Artificial Intelligence teaches the computer to solve problems by looking at hundreds orthousands of examples, learning from them, and then using that experience to solve thesame problem in new situations.Artificial Intelligence is a general field with a broad scope including: Computer Vision,Language Processing, Creativity, and Summarization.Introducing Machine Learning  • Machine Learning is the branch of AI that covers the statistical part ofartificial intelligence.• Machine learning is the subfield of computer science that gives computersthe ability to learn without being explicitly programmed.Natural Language Processing (NLP) overview Natural language processing (NLP) combines linguistics and artificialintelligence (AI) to enable computers to understand human or naturallanguage input. The business value of NLP is probably obvious. NLP canmake sense of the unstructured data that is produced by social data sourcesand help to organize it into a more structured model to support SQL-basedqueriesIntroduction to InsurTechHere is a look at some of the biggest challenges facing the insurance industry,1. Digitizing small commercial2. Commoditization3. Improving quality of analytical data 4. Using data to improve experiences5. Cybersecurity1. Digitizing small commercial• A niche but profitable market within the insurance industry is small business insurance, otherwiseknown as small commercial. While this section of the market had been relatively insulated from outsidepressure to modernize and get on board with digital technologies, that is no longer the case. Larger,more aggressive insurers understand the value of small commercials and are making a push to move intothis market and update it. This is forcing carriers who already offer small commercials to significantlyinvest in new digital technologies to keep up with their competitors.• A report from PricewaterhouseCoopers (PwC) recommended three steps these insurers could take tostay relevant in the small commercial market:• Improve customer experience with digital interactions• Digitize underwriting and claims• Invest in employees/talent2. CommoditizationInsurers are constantly trying to one-up their competitors to win over new customersand retain their current ones. And while low rates are an excellent way to do that,another equally important factor for the modern consumer is how they are treated bythe companies they work with commoditization, the process of treating someone likethey are a mere commodity, is a fast way to lose customers. They want to feel valuedand important, not like just another number.To achieve this, insurers have been deploying solutions such as artificial intelligence(AI) and automated processes to deliver personalized yet fast, customer experiences.Digital insurance technologies also help insurers create unique products quickly withlow-code tools, as well as use complex data sets to improve risk pricing and offerbetter, more personalized rates.3. Improving quality of analytical data • Data is constantly being generated and leveraged in the insurance industry. But aswe know, quantity doesn’t always equate to quality. To get the most out of user,operational and marketing data, insurers need to have robust data managementplans in place. With these plans, they can improve the overall quality of analyticaldata and gain more meaningful insights to improve customer experiences.• Insurance industry experts at PwC make three operational recommendations tomaximize data analytics practices:• Clearly define a) the customer segments and interactions that are top priorities andb) the insights needed to drive the experiences that result in new business andbetter customer retention.3. Improving quality of analytical data (cont.)• Take a holistic approach to data-driven decision making and push it out to the edges of theorganization so everyone can make better, faster decisions. To facilitate this process, insurerscan develop pilot programs that allow them to test what works and what doesn’t. In thisenvironment, insurers can gain practical and practicable insights, as well as help develop aculture that understands the power of data.• Modernize the data analytics foundation to make it agile, flexible and reusable. To do this,determine the type of architecture that will work in the near- and long-term future, as well as adata governance strategy that promotes data quality and usefulness.4. Using data to improve experiences• While using data to improve offerings and, ultimately, customer experience is not a new phenomenon inthe insurance industry, doing it well and consistently is still a challenge for many. There are outsidefactors at play here as well, as insurers grapple with market instability and increasing competition.• To meet this challenge and maximize data in pursuit of better customer experiences, companies mustleverage the digital insurance solutions at their disposal. With agile cloud systems, data analyticscapabilities, and more, insurers can meet the demands of today’s consumers with important featuressuch as:• Chatbots• Mobile applications• Omnichannel claims capabilities• AI-generated quotes5. Cybersecurity• Because so much of the world has gone digital, there is now an ever-presentconcern about cybersecurity threats. This presents a unique opportunity for insurers,as individuals and businesses alike seek out protection for their own data andprivacy.• For individuals and businesses wary of identity theft or a data breach, insurers cancover the costs associated with cybersecurity issues, which can include contactingauthorities, notifying individuals, settlement costs, fines, costs of discovering thecause, loss of business, loss of customers, loss of reputation and cyber extortion.Providing this coverage can be a cost-effective, low-risk investment that showsinsurers are forward-thinking and looking out for the best interests of theircustomers.Module 1- Highlights• Insurance is an information driven industry. New sources of information as well asprocessing technologies will take underwriting to an entirely new level and areenhancing insurers’ ability to manage risk and offer more sophisticated andpersonalized policies.Module 1 Review Questions1. Describe Importance of Technology Foresight in the Insurance   Industry2. Explain The definition of AI and ML, their concepts, and application area3. Define the State-of-art in InsurTech and current problems

Module 1: Introduction to Technology Foresight, Risk Management, and InsurTech

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Module 1: Introduction to Technology Foresight, Risk Management, and InsurTech

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