Impact of Machine Learning and AI in an Insurance Organization
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This paper explores the impact of machine learning and AI in a motor vehicle insurance organization, including customer journey mapping, information architecture, technology architecture, project governance, and cost-benefit analysis.
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Running head: IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION Impact of machine learning and AI in motor vehicle insurance industry Name of the Student Name of the University Author Note
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IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION1 Executive Summary The incorporation of the machine learning techniques and artificial intelligence can be very much useful in a motor vehicle insurance organization. All the usage-based insurances can be covered up well using AI technology. This paper will be having numerous segments, it will be introducing with the detailed description of the customer journey mapping. The following section will highlight the Information Architecture and the Technology Architecture with proper justifications. The steps of project governance and the selected project management methodology will be discussed in the paper as well. The feasibility of the plan will be provided in this business report in terms of the time frame of each of the sub-activities, work break down structure and the work package decomposition. A list of recommendations will be concluding this business report.
2IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION Table of Contents Introduction................................................................................................................................3 Customer journey.......................................................................................................................3 Information Architecture............................................................................................................5 Justification............................................................................................................................6 Technology architecture.............................................................................................................6 Justification............................................................................................................................6 Governance and methodologies.................................................................................................7 Justification............................................................................................................................7 Cost Benefit Analysis.................................................................................................................8 Time frame of the project...........................................................................................................9 Work Breakdown Structure......................................................................................................10 work package decomposition...................................................................................................10 Recommendation:....................................................................................................................12 Conclusion:..............................................................................................................................13 References................................................................................................................................14
3IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION Introduction The notable determination of the paper is to focus on the role of machine learning and artificial intelligence in a major motor vehicle insurance organization from the perspective of an ICT specialist. The needs and expectations of the consumers of this industry keep on changing due to the wide application of the disruptive technologies (Jhaet al. 2018). It can be said that the incorporation of the machine learning techniques and artificial intelligence can help this insurance organization to enhance their business reach and attract most of the potential clients of the organization. Customer journey The customer journey map can be very much useful before the incorporation of AI and machine learning techniques in this major insurance organization both the internal stakeholders of this organization such as the top-level management team as well as for the external stakeholders of this organization such as the consumers who needs and requirements are always changing during to the enactment of numerous disruptive technologies by most of the major insurance organizations (Kelleyet al.2018). The gap between the channels and the different categories of departments of this organization can be successfully minimized using the customer journey map (Hengstler, Enkel and Duelli 2016). The improvement initiative of this organization can also be enhanced using this mapping technique. The expectations of the customerscanalsobeknownusingcustomerjourneymapping(Kumar2018).The experience of the consumers of this organization which can be capitalized in the future ventures can also be decided using the customer journey mapping (Hanna 2017). The complaints of the customers of this organization can be addressed using the customer journey map as well, thus it can be said that the customer retention policy of this organization can be maintained using the3 customer journey map.
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4IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION Figure 1: Customer Journey Mapping (CJM) of this major insurance organization (Source: Created by the author) The following steps can be very much useful for creating the CJM in this major motor vehicle insurance organization. StepsDetailsExplanation Step 1Define the personaTheneedsandexpectationofconsumershavetobe identified in the first place. Step 2Definecustomer phases Phases such as scoping, mapping out customer expectation, improvement and maintenance is very much vital for the consumer journey mapping. Step 3Touch point for the consumers Insurance details, pre-sales support, facilities during the insurance packages can be useful to maintain the branding of this business. Step 4ResearchDevelopmentoftheemployeesworkinginthis Identify gap between channel and department Improve customer retention Experience ofthe consumers can be used forthewell- fareofthis organization. Enhance improvemen t initiative
5IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION organization must be aligned with the organizational target. Step 5Determine point of friction Overheads cost of the organization needs to be minimized and customer experience must be enhanced. Step 6ResolveThe journey of the customers must be smooth so that the business growth of this organization is maintained. Table 1: CJM of this major insurance organization for the consumers (Source: Created by the author) Information Architecture The detailed description of an Information Architecture will be presented in this unit of the paper. Insurance organization Upcoming productsSearch optionLog out Dashboard options ServicesCustomer experience and coverage personalization Claims settlement issues Benchmark AI solutions Account Management andPolicy renewal Trainingand report Premium pricingof theservice usingAI technology. Chatbots based onAI technology can be resolved all theissuesof theclients afterverifying identity. Customer satisfaction canbe enhanced after a claim isofficially filed. Productand service evaluation can be done bythe consumers ofthis organization. Theaccount ofthe adminsas wellasthe consumers canbe managed using the AI technology. Education details for the future employees in termsofthe job opportunities canbe notifiedto the registered account holders. Policy details About Us pagePayment option Complaints section ContactUs page History of the organization Table 2: Information Architecture for the organization (Source: Created by the author)
6IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION Justification Thisinformationarchitecturecanbeverymuchusefulforboththeinternal stakeholders of this insurance organization to understand the impact of the machine learning and AI technology (Lee, Lee and Kim 2019). All the latest coverage can be easily understood by the clients of this motor vehicle insurance organization using the above Information Architecture. The technology architecture will be presented in the ensuing section of the paper. Technology architecture This unit of the paper will be discussing the desired technology architecture for this motor vehicle insurance organization. Figure 2: Technology architecture for the vehicle motor insurance organization (Source: Created by the author) Policies and Principles Each of the motor vehicles have separate insurance packages. Policies keeps on updating. Current services and IT trends Chat bot and executivr team will be helpful to deak with the consumer complaints AI technology is used in the organization portal Business requirements and department direction Business decision can be taken by the machine learning techniques. Future services and production can be managed internally by the admins of the organization.
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7IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION Justification Theproposedtechnologyarchitecturecanbeverymuchbeneficialforthis organization as it describes the interaction and the structure of the services offered by this motor-vehicle insurance organization (Nakamuraet al.2019). All the business units of this corporation can be managed using this architecture. The project governance procedures, as well as the project management methodology which will be selected in this project, will be discussed briefly in the following sections of this report. Governance and methodologies Professional project governance plan can be very much important regarding the incorporation of the artificial intelligence in the working environment of this organization. PhasesExplanation Phase 1The configuration of the AI technology must be compatible with the existing technologies used in the organization. Phase 2Business data should be carefully migrated from one end of the organization to another. Phase 3The usage and the support required must be gathered from the employees of this organization. Phase 4Orientationtrainingandskilldevelopmenttrainingcanbeverymuch important regarding the successful implementation of the AI technology. Phase 5The outcome of the incorporation procedure of AI technology must be matched with the deliverables of the project. Table 3: Project governance plan for the organization (Source: Created by the author) Justification This project governance plan can be very much essential for this organization as it can successfully help in identifying the issues which can be faced during the incorporation procedure of the AI technology. Waterfall project management methodologiescan be very much important for the implementation of the AI technology in this motor vehicle organization. Each phase of the
8IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION project can be professionally monitored using the waterfall project management methodology (Shalini, Krishnamurthy and Narasimha 2017). This project management methodology can be understood by both the consumers as well as the employees of this organization which is the initial reason behind selecting this methodology (Agrawal, Gans and Goldfarb 2019). The changing expectations of the consumers of this organization can be purposefully aligned using this project management methodology (Stilgoe 2018). The cost benefit analysis of this project will be presented using a pictorial diagram. Cost Benefit Analysis RMOCost/Benefit Analysisfor the implementationof AI inmotor vehicle insurance organization Incorporation of AI technology60000 Additional cost15000 Total Cost for the project75000 Year of Project year 0year1year 2year 3year 4year 5TOTALS Net economicbenefit$0.00$35,000.00$35,000.00$35,000.00$35,000.00$35,000.00 Discount Rate 8%10.92590.85730.79380.73500.6806 PV Of Benefits$0.00$32,407.41$30,006.86$27,784.13$25,726.04$23,820.41 NPV of all BENEFITS$0.00$32,407.41$62,414.27$90,198.39$115,924.44$139,744.85$440,689.36 One Time Costs$75,000.00 RecurringCosts$0.00$100.00$100.00$100.00$100.00$100.00 Discount Rate 8%1.00000.92590.85730.79380.73500.6806 PV Of RecurringCosts$0.00$92.59$85.73$79.38$73.50$68.06 NPV Of All Costs$75,000.00$75,092.59$75,178.33$75,257.71$75,331.21$75,399.27$451,259.11 Overall NPV($10,569.75) Overall ROI =(Overall NPV / NPVOf All Costs-0.02 Total Costfortheproject Figure 3: CBA for incorporating AI technology in an insurance organization (Source: Created by the author)
9IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION Overall NPV($10,569.75) Overall ROI =(Overall NPV / NPVOf All Costs-0.02 Break-Even Analysis YearlyNPV Cash Flow$0.00$32,314.81$29,921.12$27,704.75$25,652.54$23,752.35 Overall NPV Cash Flow$75,000.00($42,685.19)($12,764.06)$14,940.68$40,593.23$64,345.58 Project break-even occurs between years 2 and 3 Use 1st year of positive cash flow to calculate break-even fraction2.4607years Figure 4: Break even for incorporating AI technology in a motor vehicle insurance organization (Source: Created by the author) Time frame of the project The detailed description of each of the activities of this project will be presented in the below pictorial diagram. IDTask Mode Task NameDurationStartFinish 1Implementation of AI in insurance organization 56daysWed5/1/19Wed7/17/19 2Phase 110daysWed5/1/19Tue5/14/19 3Selection of technology 2daysWed5/1/19Thu 5/2/19 4Literature Review2daysFri 5/3/19Mon5/6/19 5Documentation5daysTue 5/7/19Mon5/13/19 6Evaluation1dayTue 5/14/19Tue 5/14/19 7Phase 211daysTue5/7/19Tue5/21/19 8Understanding business requirements 5daysTue 5/7/19Mon5/13/19 9Evalyating customer issues 1dayTue 5/14/19Tue 5/14/19 10Understand the opportunity of AI 5daysWed5/15/19Tue 5/21/19 11Phase 35daysWed5/22/19Tue5/28/19 12Design the system5daysWed5/22/19Tue 5/28/19 13Phase436daysWed5/29/19Wed7/17/19 14Incorporation phase 30daysWed5/29/19Tue 7/9/19 15Understand the limitation of AI 5daysWed7/10/19Tue 7/16/19 16Trainingfor staff1dayWed7/17/19Wed7/17/19 282610141822263037111519232715913 Apr 22, '19May 6, '19May 20, '19Jun 3, '19Jun 17, '19Jul 1, '19Jul 15, '19 Figure 5: Time frame for incorporating AI technology in an insurance organization (Source: Created by the author)
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10IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION Work Breakdown Structure The following pictorial diagrams will be stating each of the sub categories of the four phases of implementation. Implementation of AIin insurance organization Phase 1 Selection of technology Literature Review Documentation Evaluation Phase 2 Understanding business requirements Evalyating customer issues Understand the opportunity of AI Phase 3 Design the system Phase 4 Incorporation phase Understand the limitation of AI Training for staff Figure 6: Phase wise WBS (Source: Created by the author) Work package decomposition The following table can be very much helpful for the readers of this document to have an idea about each of the phases of incorporating Artificial Intelligence and machine learning techniques in the business environment of motor vehicle insurance organization. Implementation of AI in a motor vehicle insurance organization Phase 1Phase 2Phase 3Phase 4 The selection of the machinelearning proceduresand artificial intelligence is considered in this Theneedsand expectationsofthe consumersofthe organizationhasto be aligned with the Designingofthe systemwillbe consideredinthis phase of the project (Brynjolfsson,Rock Thisisthemost importantphase among the rest of the phases.The implementationof
11IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION phase of the project. Detailed analysis of the AI will be done bytheinternal stakeholdersofthe organizationinthis phase.All assumptionsand deliverable are note inaformal document. incorporation procedureofAI technology.The futureopportunities has to be considered duringthe implementationof the AI technology. and Syverson 2018).theAItechnology will be considered in this phase Table 5: Work package decomposition for this project (Source: Created by the author) Critical Success Factors for the Project There are different categories of Critical Success Factors which are needed to be considered during the enactment of the Artificial Technology in the working environment of this major motor vehicle insurance organization (Felten, Raj and Seamans 2019). These critical factors will be discussed in this section of the paper. Different types of Critical Success FactorsExplanation Prioritizing engineeringThe deployment of the software must be known to both the internal along with the external stakeholders of this motor vehicle insurance organization so that the business inconsistencies are easily resolved. Financial capabilitySupport from the investors as well as from thetop-levelmanagementisverymuch desired during the incorporation of the AI technology in this motor vehicle insurance organization (Takacset al. 2018). TrainingServicetraining,orientationtraining,on- boardtrainingande-trainingfacilitiesis verymuchsignificantregardingthe enactmentoftheAItechnologyinthis motor vehicle insurance organization. LPM principlesThe risk associated with the project has to be considered before the design phase of this project (Frey and Osborne 2017). CommunicationCommunication between the consumers and the employees of this organization can play a huge role in the implementation of AI
12IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION technology in thisinsurance organization (Hanna and Kimmel 2017.). LeadershipThe role of the organizational leaders are verymuchimportantregardingthe implementationoftheseemerging technologies. Organization cultureA sense of acceptance must be there for eachofthestakeholdersofthis organization,maintainingaprofessional work culture will be important regarding the implementation of the AI technology in this organization. Table 6: CSF which has to be considered in this project (Source: Created by the author) Impact of the implementation on the organization Change management strategy must be selected in such a way so that it does not have any effect on the existing process of this organization. Change management strategy such as the redefining the cultural value, exercising authority and shifting the burden of change should be focused during the enactment of the machine learning as well as the Artificial Intelligence Technology. These change management strategies cab be very much beneficial to deal with issue such as internal resistances. These above discussed change manage strategies can be very much important during the enactment of these technologies in this major insurance organization. The basic elements of the change management strategy should be considered during the enactment procedure so that it does not affects the other technologies which are already been used in this industry. Recommendation The recommendation of this project will be discussed in this section of the paper.
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13IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION The new technology should not be having any issues with the technologies which are already been used in the business environment of this major motor vehicle insurance organization. All the business process and business data should be protected from any sort of data security issues such as data alteration and data manipulation, as it would be a huge financial and reputations loss for this organization. The risks of the implementation procedure and the knowledge gaps among the employees of the incorporating technology must be addressed with the help of risk management plan and skill development training respectively. IT governance plan should be considered during the implementation of this plan, at the same time it can also be said that the waterfall project management methodology can be very much beneficial in this project. Selection of professional human resources is very much recommended in this project as they can manage each if the difficulties in an organized and structured manner. Resources should be understanding the value creation ability of this new emerging technology. The limitations, as well as the benefits of Artificial Intelligence and machine learning procedures, must be known to each of the stakeholders of the business. The ethical considerations of Artificial Intelligence has to be focussed before the start of the project. Conclusion: The paper is very much helpful for the readers of this document to understand the importance of customer journey mapping in a major insurance organization. The detailed explanation of the CJM can be understood from the tabular description of the paper. The paper has highlighted the desired Information architecture and the Technology architecture
14IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION along with justification.The desired project governance plan of this project can also be understood from the paper. The paper also presents the cost-benefit analysis of the project along with the break-even occurrence. The timeframe of each of the activities of the project has been presented in the form of gnat charts and work breakdown structure. Critical success factors which are needed to be incorporated during this project such as communication, leadership, organization, culture and training can also be determined from this paper. Thus, the feasibility of incorporating Artificial Intelligence in an insurance organization can be understood from the paper.
15IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION References Agrawal, A., Gans, J.S. and Goldfarb, A., 2019.Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction(No. w25619). National Bureau of Economic Research. Brynjolfsson, E., Rock, D. and Syverson, C., 2018. Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics. InThe economics of artificial intelligence: An agenda. University of Chicago Press. Felten, E.W., Raj, M. and Seamans, R., 2019. The Variable Impact of Artificial Intelligence on Labor: The Role of Complementary Skills and Technologies.Available at SSRN 3368605. Frey, C.B. and Osborne, M.A., 2017. The future of employment: how susceptible are jobs to computerisation?.Technological forecasting and social change,114, pp.254-280. Hanna, M.J. and Kimmel, S.C., 2017. Current US federal policy framework for self-driving vehicles: opportunities and challenges.Computer,50(12), pp.32-40. Hanna, M.J., 2017. Policy memorandum:The case for adopting autonomousvehicles technology and supporting research in artificial intelligence.J. Sci. Policy Gov,11(1). Hengstler, M., Enkel, E. and Duelli, S., 2016. Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices.Technological Forecasting and Social Change,105, pp.105-120. Jha, S., Tsai, T., Hari, S., Sullivan, M., Kalbarczyk, Z., Keckler, S.W. and Iyer, R.K., 2018. Kayotee: A Fault Injection-based System to Assess the Safety and Reliability of Autonomous Vehicles to Faults and Errors. In3rd IEEE International Workshop on Automotive Reliability & Test.
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16IMPACT OF MACHINE LEARNING AND AI IN AN INSURANCE ORGANIZATION Kelley, K.H., Fontanetta, L.M., Heintzman, M. and Pereira, N., 2018. Artificial Intelligence: Implications for Social Inflation and Insurance.Risk Management and Insurance Review, 21(3), pp.373-387. Kumar, Y., 2018. Artificial Intelligence & Robotics–Synthetic Brain in Action.Available at SSRN 3325115. Lee, S.M., Lee, D. and Kim, Y.S., 2019. The quality management ecosystem for predictive maintenance in the Industry 4.0 era.International Journal of Quality Innovation,5(1), p.4. Nakamura, S., Komada, M., Matsumura, Y. and Matsushita, K., 2019.Effects of the Feature Extraction from Road Surface Image for Road Induced Noise Prediction using Artificial Intelligence(No. 2019-01-1565). SAE Technical Paper. Shalini, V., Krishnamurthy, S. and Narasimhan, S., 2017.Predictive Analytics in Automobile Industry: A Comparison between Artificial Intelligence and Econometrics(No. 2017-01- 0238). SAE Technical Paper. Stilgoe, J., 2018. Machine learning, social learning and the governance of self-driving cars. Social studies of science,48(1), pp.25-56. Takacs, A., Rudas, I., Bosl, D. and Haidegger, T., 2018. Highly Automated Vehicles and Self-DrivingCars[IndustryTutorial].IEEERobotics&AutomationMagazine,25(4), pp.106-112.