The Impact of Artificial Intelligence on Insurance Companies

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This report examines the increasing role of artificial intelligence in the insurance industry, highlighting its potential to enhance efficiency, reduce errors, and improve customer experiences. It reviews existing literature on AI's impact on various sectors, including its ability to automate processes, improve claim management, and personalize insurance premiums. The report also addresses challenges such as data privacy concerns and the need for robust authentication methods. Furthermore, it discusses the advantages of AI, such as faster processing times, error reduction, and enhanced data security, alongside disadvantages related to job displacement and ethical considerations. The analysis emphasizes AI's transformative potential in streamlining insurance operations and improving customer satisfaction while acknowledging the need for careful implementation to address potential drawbacks.
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Business Research
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Contents
Introduction...........................................................................................................................................2
Literature review...................................................................................................................................3
Advantages and Disadvantages of AI in the insurance firms.............................................................6
Conclusion.............................................................................................................................................7
REFERENCES......................................................................................................................................8
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
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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 Göranzon 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.
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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
worker’s 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 tape (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.
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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 identifying 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 person’s 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 firm’s
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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
immediately 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
ï‚· 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.
ï‚· 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.
ï‚· 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).
ï‚· 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
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in the case of medical insurance where medical check-up procedure takes a lot of
time.
ï‚· 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.
ï‚· 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).
ï‚· 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:
ï‚· 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.
ï‚· 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).
ï‚· 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.
ï‚· 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.
ï‚· 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.
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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.
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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. Decision exploration lab: A visual analytics solution for
decision management. IEEE Transactions on Visualization and Computer Graphics, 19(12),
pp.1972-1981.
Chew, B. 2018. Impact of AI on talent acquisition and recruitment in the future. [Online].
Available at: http://sbr.com.sg/hr-education/commentary/impact-ai-talent-acquisition-and-
recruitment-in-future. [Accessed on: 11th February 2018].
Dirican, C., 2015. The impacts of robotics, artificial intelligence on business and
economics. Procedia-Social and Behavioral Sciences, 195, pp.564-573.
Dutta, S., 2014. Knowledge processing and applied artificial intelligence. Elsevier.
Ennals, R., 2012. Artificial intelligence and human institutions. Springer Science & Business
Media.
Experts systems. 2018. The advantages of using AI in Insurance. [Online]. Available at:
http://www.expertsystem.com/advantages-using-ai-insurance/. [Accessed on: 11th February
2018].
Ezrachi, A. and Stucke, M.E., 2017. Artificial intelligence & collusion: When computers
inhibit competition. U. Ill. L. Rev., p.1775.
Financial services insights. 2018. Impact of Robotics, RPA and AI on the insurance industry:
Challenges and opportunities. [Online]. Available at:
https://fsinsights.ey.com/big-issues/Digital-and-connectivity/shaping-insurance-robotics-rpa-
and-ai. [Accessed on: 11th February 2018].
Göranzon, B. and Josefson, I. eds., 2012. Knowledge, skill and artificial intelligence.
Springer Science & Business Media.
Kantarjian, H. and Yu, P.P., 2015. Artificial intelligence, big data, and cancer. JAMA
oncology, 1(5), pp.573-574.
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Kaplan, J., 2015. Humans need not apply: A guide to wealth and work in the age of artificial
intelligence. Yale University Press.
Kim, S.Y., 2011. Prediction of hotel bankruptcy using support vector machine, artificial
neural network, logistic regression, and multivariate discriminant analysis. The Service
Industries Journal, 31(3), pp.441-468.
Kirlidog, M. and Asuk, C., 2012. A fraud detection approach with data mining in health
insurance. Procedia-Social and Behavioral Sciences, 62, pp.989-994.
Lacasse, R.M. and et. al., 2016. A Digital Tsunami: FinTech and Crowdfunding.
In International Scientific Conference on Digital Intelligence. April (pp. 4-6).
Marr, B. 2018. How AI and machine learning are used to transform the insurance industry.
[Online]. Available at: https://www.forbes.com/sites/bernardmarr/2017/10/24/how-ai-and-
machine-learning-are-used-to-transform-the-insurance-industry/#2386e4b13a1f . [Accessed
on: 11th February 2018].
Morgan, B. 2018. How artificial intelligence will impact the insurance industry. [Online].
Available at: https://www.forbes.com/sites/blakemorgan/2017/07/25/how-artificial-
intelligence-will-impact-the-insurance-industry/. [Accessed on: 11th February 2018].
Mylopoulos, J. and Brodie, M.L., 2014. Readings in artificial intelligence and databases.
Morgan Kaufmann.
Ngai, E.W.T. and et. al., 2011. The application of data mining techniques in financial fraud
detection: A classification framework and an academic review of literature. Decision Support
Systems, 50(3), pp.559-569.
Noto, G. 2018. Most Insurers Believe AI will completely change Insurance by 2020.
[Online]. Available at: https://bankinnovation.net/2017/04/most-insurers-believe-ai-will-
completely-change-insurance-by-2020/. [Accessed on: 11th February 2018].
Omoteso, K., 2012. The application of artificial intelligence in auditing: Looking back to the
future. Expert Systems with Applications, 39(9), pp.8490-8495.
Scherer, M.U., 2015. Regulating artificial intelligence systems: Risks, challenges,
competencies, and strategies. Harv. JL & Tech., 29, p.353.
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Stoneking, M.D. and Curet, O.L., Deloitte Development Llc, 2014. Computer assisted
benchmarking system and method using induction based artificial intelligence. U.S. Patent
8,788,452.
Tao, W. and Li, Y., 2011, June. The design and implementation of business intelligence in
insurance industry. In Computer Science and Service System (CSSS), 2011 International
Conference on (pp. 3681-3684). IEEE.
Turban, E., Sharda, R. and Delen, D., 2011. Decision support and business intelligence
systems. Pearson Education India.
Vladeck, D.C., 2014. Machines without principals: liability rules and artificial
intelligence. Wash. L. Rev., 89, p.117.
Wu, D.D. and Olson, D.L., 2013. Computational simulation and risk analysis: An
introduction of state of the art research.
Wu, Y. and et. al., 2014. Enterprise risk management and firm value within China's insurance
industry. Professional Accountant, 14(1), pp.1-10.
Zagorin, E. 2017. Artificial Intelligence in Insurance- Three Trends That Matters. [Online].
Available at: https://www.techemergence.com/artificial-intelligence-in-insurance-trends/.
[Accessed on: 11th February 2018].
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