Advantages And Disadvantages Of Using AI In Insurance Company

Question: Discuss about the Artificial Intelligence In Insurance Company. Answer: Introduction Artificial intelligence is the future of the technological advancements. It can be understood as the intelligence that is displayed by the modern day machines (Scherer, 2015). They develop this by evaluating the amount of data that they have stored from their past experiences (Noto, 2018). In this Machine understands its environment and responds accordingly. Use of artificial intelligence is going to increase in the coming years. It is going to enhance the efficiency of the business as well as it will reduce the numbers of errors that occurs due to human errors (Ngai and et. al., 2011). In many cases it can be seen that artificial intelligence is not only changing the business but it is changing the overall dimensions of the business and hence improving customer experiences. This report also showcases the advantages and disadvantages of using AI in the working of the insurance company as well as its usefulness in lives of the people. Literature review In the views of Granzon and Josefson (2012), Artificial intelligence is the technological advancements on which the future of the business is leaning towards. It is not only going to reduce the efforts of the employees but it is also going to enhance the efficiency of the firm. This is due to the fact that most of the time the fault in the business is due to the errors done by the human beings or due to the reason that machines did not have the capacity to think according to the situation. They generally work according to the particular set of instructions that is fed into them. This makes them irresponsive towards the environment that they are in. It creates a situation in which machines also becomes ineffective. Use of technology was for the reason to make work more effective and if they do not have the ability to think then it may reduce its efficiency. There are several aspects to the use of technology i.e. from reducing human interventions to reducing the human interference (Tao and Li, 2011). This cannot be possible without machines smarter. According to the views of Wu and Olson (2013), Artificial intelligence is changing the lifestyle of the people all around the world. It has got greater influence in the daily activities of life. From transportation to medication and from research to agriculture in almost every field it has made greater contribution and made the whole process smarter. It has also reduced the amount of human interventions that was previously required for doing a job. Artificial intelligence has empowered people who have severe disease in performing many of their personal life activities (Broeksema and et. al., 2013). In some of the restaurants of Japan, humanoid robots serve food to the consumers. There are many areas like security of organisation as well as home can be done in a better way by the use of artificial intelligence technologies like face or voice recognition. On the other hand Omoteso (2012), Suggests that there are many areas in which artificial intelligence is utilised properly. These advancements have only been implemented and trusted in certain areas of greater importance like the medical, research, transportation, military etc. There are several other business areas in which AI can be utilised especially in the banking and insurance. It not only helps the insurance providers in making their processes easier but it also assists the consumers in understanding the whole process and then taking the services. It is to be understood that there is larger number of people who are the consumers of the insurance company. It has become essential for the companies to make use of the most advanced AI technologies for the making process easier for consumers. It helps in bringing highest order of satisfaction in the minds of consumers. According to Dirican (2015), Most of the people that are taking the services of the insurance company has been disappointed by the services they have receiving over the years. It is also to be understood that this is the industry in which least amount of technological advancements have taken place. The innovation have not been properly utilised in this field in spite of their extraordinary benefits to the people (Morgan, 2018). There are several reasons that are responsible for it. One of the primary reasons for this is that insurance industry is related with the changing norms and the authenticity of the machine learning is still under research. On the contrary Kirlidog and Asuk (2012), states that Insurance industry is facing a lot of difficulty in terms of providing better experience to the consumers. For example if the employee has gone on vacation then consumer has to wait for him to return for claiming request. It is not only increasing the workload of the workers but also enhances problems related to the efficiency of the firm. This frustrates both consumers and employees. On the other hand Turban, Sharda and Delen (2011), says that AI can be applied for improving the claim processes. This brings the system where touch less claims can be filed and human or workers intervention is not necessary. With the use of AI, individuals can easily report the claim, capture damage, make audit of the overall system and procedures as well as they can communicate with the consumers. This affect the industry as it enhances the speed of the working process as well as allows customers to file claims without having to wade through red ta pe (Lacasse and et. al., 2016). He also underlines the fact that the companies that have implemented the technology long ago has saved a lot of time as well as they are able to maintain the quality. It is necessary for improving the employee satisfaction as well as making positive brand image of the firm. In the views of Ennals (2012), Artificial Intelligence empowered claims can fight against the most costly elements of the insurance industry i.e. fraudulent claims. This costs industry a huge sum of money i.e. approx. $40 billion a year. Artificial intelligence with the help of effective algorithms can identify data patterns and recognise when anything is fraudulent. This helps in reducing the dependence on the humans who will manually comb through reports to grab inaccurate claims. On the contrary Vladeck (2014), thinks that in the countries that are having lesser amount insurance penetration, use of Artificial Intelligence can improve the reach as well as can contribute to higher profitability. Especially in the countries such as India and many other densely populated nations use of this technology can be highly beneficial. This technology is helping companies through the use of image, voice recognition as well as through the use of natural language processing. It helps them in ide ntifying the consumers through face, voice recognition (Marr, 2018). This also helps in reducing the efforts done by the people in making claims if the original person has died. In manual methods there can be many identification problems like if the persons signature does not match or the finger prints gets faded out. AI authentication can be seen in the examples where machines ask people to select a particular kind of image then only it provides an access to the consumers. On the other hand Ansari and Riasi (2016), States that many of the insurances like health related insurance can be made easier with the use of AI. This is due to the fact that there are larger numbers of people who are coming for this insurance and their medical test procedures takes a lot of time as well as there is complexity involved in it. Artificial intelligence helps in reducing the extra efforts related to medical check-ups and reduces the chances of fraud claims. Artificial intelligence helps companies in adjusting premiums as per individual consumers (Zagorin, 2017). According to Stoneking and Curet (2014), Artificial Intelligence solves one of the biggest problems of the insurance firms that are related to the privacy of the data related to consumers. Many a times this data is leaked due to various human errors. Artificial intelligence always helps in making the authentication process more secured and hence there is very less chance that data can get stolen for the companies benefit. AI also helps the firm in collecting data from various sources (Financial services insights, 2018). Since all the Artificial intelligence devices are connected with the global networks like Internet of things which empowers them to gather more information related to the consumers. Several firms are using telematics devices that could trigger an emergency call which instructs firms representatives to call policy holders and assist them in their post-crash recovery (Ezrachi and Stucke, 2017). Smart photo analysis systems that are capable of assessing vehicle damage im mediately following an accident. On the contrary Al-Azmi (2013), says that Artificial intelligence is reducing the amount of money spent by the people in the process of availing these insurances. It also helps in getting the loans for home that is built in the disaster prone area. There are smart devices that are attached inside the house which helps them in giving the status of house (Kaplan, 2015). This is done by the use of sensors which measures various kinds of changes in the environment and send signal to the people that are associated with it. Apart from this there are many kinds of sensors that protects home from the damages that are internal in nature (Kantarjian and Yu, 2015). Like in the case of firebreak fire sensors will activate water sprinkler that will ultimately save property from getting damaged and immediate signal is sent to the insurance company and the house owner. It helps in reducing the complexity related to insurance claims. Advantages and Disadvantages of AI in the insurance firms Any technology gets implemented within an organisation only after checking the implications it poses on the business of the firms or the whole industry (Wu and et. al., 2014). There are several kinds of benefits and demerits that are attached with the use of AI in the Insurance industry. Some of the advantages and disadvantages attached with the use of AI in Insurance firms are as follows: Advantages AI helps in making the work process easier and faster. This helps in bringing efficiency to the firm which is necessary for their growth as well as achieving consumer satisfaction. AI intelligence helps in solving problems related to identification of people while they are claiming their insurance. These problems arise to the people who lost their finger prints due to some hazards. AI also helps in making process more error free which is necessary for less compliance generation. It helps in achieving higher consumer satisfaction which helps in increasing their consumer base (Kim, 2011). AI not only helps consumers in their claims but also assist them in the process of availing insurance claims. It makes the procedure easier as well as efficient especially in the case of medical insurance where medical check-up procedure takes a lot of time. It also helps in securing data in a better way. This is due to the reason that machines gets smarter and hence there is less chance of making a security breach (Experts systems, 2018). This is also due to the reason that an extra layer of authentication that is smart gets added to it. AI also creates new kinds of jobs that are related to the technology fields and at the same time it reduces the efforts of the people in doing their task (Mylopoulos and Brodie, 2014). It provides flexibility to the whole process as the insurance benefit calculation can be done according to the algorithm and hence different values get generated for different consumers. Disadvantages Apart from several benefits within an organisation there are several disadvantages hat are also associated with the integration of AI in the Insurance industry. Some of them are as follows: It is not for the people that do not know how to use advanced technology. This can be seen in the case of people whose digital literacy are on the lower side and hence require some kind of trainings for such people. Even after adding advanced layer of protection there is problem of privacy. This is due to the reason that these machines are connected to huge networks as well as sensors which can easily be hacked (Dutta, 2014). There is lot of research that is needed to be done so as to make it business friendly hence it needs continuous up gradations and a highly qualified technician to manage the system if any kind of unwanted failure arises. This is a technology that requires a huge amount of Investments in their installation and maintenance (Chew, 2018). It is also due to the reason that software and hardware attached with it is of higher cost. There is no emotional understanding inside present day AI devices and hence they cannot act accordingly. But future machines can also understand social values as it is in the process. Conclusion From the above based report it can be concluded that in the era of technological business it is important that the ways of doing business must also get smarter. This can be done by the use of technology that is smart and learns from its previous mistakes. This reduces number of human interventions required for completing the task. This also reduces the number of errors in the whole working process. AI intelligence helps insurance industry to work in a more constructive ways. It brings efficiency in the work process as well as makes the whole process faster and easier. Use of AI in the insurance industry has several advantages and disadvantages. One of the major problems that it helps to solve is of data privacy which is always a matter of concern for the consumers. AI helps consumers in their filing of claims or availing of insurance as the process gets easier. References Al-Azmi, A.A.R., 2013. Data, text and web mining for business intelligence: a survey.arXiv preprint arXiv:1304.3563. Ansari, A. and Riasi, A., 2016. Modelling and evaluating customer loyalty using neural networks: Evidence from startup insurance companies.Future Business Journal,2(1), pp.15-30. Broeksema, B. and et. al., 2013. 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