Information System Design

This report discusses the importance of information system design in organizations and the use of AI and machine learning in improving performance and profit. It covers analysis/planning and implementation processes, as well as the benefits and challenges of adopting new information systems. The report also highlights the impact of AI and machine learning on the insurance industry and provides recommendations for organizations.

Running Head: Information System Design 0
Information System Design
Report
Student name

Information System Design 1
Table of Contents
PART-1.........................................................................................................................................................2
Analysis/Planning....................................................................................................................................2
PART-2.........................................................................................................................................................6
Implementation.......................................................................................................................................6
References.................................................................................................................................................11

Information System Design 2
PART-1
Organization requires different things to enhance thier functions in respect of growth and profit for
entire team. There are many things that make an organziation successful, which are high-level strategy,
technological changes, and business ethics. It is a way to manage all the things in proper way with a right
approach. In present era, Artificial Intelligence (AI) and Machine Learning (ML) are highly used in the
different fields to innovate new ideas, which can increase performance and profit of an organziation
( Bughin , et al., 2017).
Analysis/Planning
Analysis of any problem has different phases and planning to resolve issues, which are occurred during
analysis phase. To resolve issues make reasonable assumptions, this provides different actions in future.
It requires high-level strategy of the organisation to incorporate AI & Machine Learning ( Adams , 2017).
In case of insurance company, it requires high-level of data analytics to take decisions for different
business processes. A motor vehicle insurance company should make a data warehouse to store data of
their clients because it is a long-term process. In addition, AI provides computing algorithms, which
provides a capability to analyze the data and provides desired information after processing that data,
which is feasible for the decision-making process (Al-Saggaf, et al., 2017).
Machine leaning provides different features to learn from different data sets of data of customers,
which is collected from the different structured and unstructured sources. It uses deep leaning
approaches to make solution that is more feasible (Alter, 2001).
As a IS/ICT specialist, I will recommend new information system, which will have AI and ML features.
Those features will be useful in increasing performance of employees and business processes, which are
make effects on the profit of the organization (Baars & Kemper, 2008).
It will cost effective for the organziation, but it will provide huge benefits in long-term for the
organziation. Information System (IS) is also having maintenance cost and other perspective with it, such
as training of employees and implementation cost. It will take large amount to establish properly.
Legacy systems and process are making whole system slow and less effective, which makes huge effects
on the growth of the organziation (Bharadwaj, et al., 2013).

Information System Design 3
Customers affects from all those systems, as they have more expectations from their organization. From
last two decades, disruptive technologies are changes in present market scenarios and it will change the
expectations of the customers ( Bughin , et al., 2017).
In addition, organziation should consider their core system and its challenges. However, changes are
possible in the current system, but it is also old after sometime. Therefore, it is necessary to change the
whole system and its processes to take competitive advantages (Bélanger & Crossler, 2011).
Moreover, customers are connected with digital devices, such as smartphones and other things.
Therefore, new IS will provide uses of these things in the business processes. We can share all the
information on their smartphones and email id, which is a better way of communication and
environmental friendly (Castelluccio, 2017).
AI and ML provide helps into accessing online data of customers and motor vehicles. It will provide
complete information of customers from different databases, such as public databases and private
database, which can reduce frauds that effects revenue of an organization. In addition, it will provide
many opportunities in claim assessment, fraud and risk management (Chen, 2010).
AI and Machine Learning are helpful into motivation of the business based on its facilities to the
organization. In present era, data increases data by day and it is too difficult to manage through legacy
systems. Therefore, it requires cognitive technology to make proper systems, which can satisfy
customers as their expectations ( Davoren, 2019).
AI and ML are frequently used as a disruptive technology in the field of insurance. In addition, AI
provides helps in the claims management process. Claim management process is depends on many
things, such as claim from input, medical reports, repair estimates, incident documentation. All these
documents are in unstructured and semi-structured and it makes this process difficult to process
(Dhillon & Torkzadeh, 2006).
Furthermore, the evaluation and decision-making process depends on all those documents that are
collected in unstructured manner. However, most of the organziation have different types of documents
and few are unstructured because of their bulky processes. AI and Machine Learning will provide
automated claims management solutions (Ghosh, 2017).
It provides fast track claims based on the smart automation and robotic process automation. AI and
machine learning identify patterns in data warehouse and provides fraudulent claims in the process. AI
uses machine learning capabilities in identification process and it discover new cases in new scenarios. It
can search in historical data for more refine results (Gupta, et al., 2018).

Information System Design 4
AI and machine learning provides AI-powered Chatbot, which are available for all time and it provides
past and efficient customer service. It uses natural language processing to understand customers quires
and provides significant answer, as they are required (INC, 2018).
Insurance industry provides many benefits to the customers and they make thier business from interest
rate, consultancy fee and many other things. In case of customer’s relationship, it will provide better
understanding of plan and features of the company. Therefore, customers can purchase more plan to
secure their assets (Klumpp, 2018).
Source: Author
In above diagram, business model canvas is designed for the insurance organziation, which can provide
different benefits to the organziation. It will improve customer’s relationship using Chatbot and other
methods for satisfying customers (Laudon, & Laudon, 2016).
Insurance organization is having a huge value in the market, as they secure many things, which are
assets of a person, company, and others. They provide money based on the reality of claim against an
incident. It makes a high value of an organziation. AI and machine learning makes a good image in the
market of the organziation. It will provide revenue in long-terms based on the analysis ( Marr, 2019).
It reduces frauds from the claim management system, which is highly beneficial for organziation. It
makes more customers, which will provide a huge value to the organziation (Meister, 2018).

Information System Design 5
According to (Burns , 2018), insurance industry is based on the data and they can calculate about the
risks in the particular thing. The emergence of artificial intelligence and machine learning means that
insurance organization should scrambles for the ways of analysis and implementation of them in their
work to get better results in the competition (O'Brien & Marakas, 2005).
Insurance company can installed device in their vehicle to measure driving of customers. Therefore, they
know about the risk of the customers. They can know about the behaviour of customers using wearable
devices as well. Facial recognition system is also used in insurance companies to identify customers.
Organziation should change the data collection processes in to structured data, which is directly uses by
the AL and ML for learning and decision-making process ( Ransbotham, et al., 2017).
Based on present condition, organziation uses a legacy system to maintain different business process,
which is related to the insurance industry, such as data collection, claim management, customer
services, and many others. In addition, AI and Machine learning enabled system make automation in the
claim management system, which reduces risk of frauds. It will enable live chat option with the help of
Chatbot, which provides effective communication and proper information based on the questions on
customers from anywhere and anytime (Raymond & Bergeron, 2008).
It will provide competitive advantages to the organziation, as customers are more satisfied with all those
automatic services because all the customers requires different services in low cost and in less time.
There are many things, which provide benefits in long-terms, such as data collection for, long-term
( Sennaar, 2019).

Information System Design 6
PART-2
Implementation process is cost effective process and it will take time to establish in proper way, such as
training, hardware, software, advanced systems, and secure network. These are basic needs of a system,
which provides different facilities to manager to manage all the things in a proper way (Stair & Reynolds,
2013).
Implementation
In new system, customer can take insurance of their assets through automatic process system in which
robots will check the details of the vehicle and provide different specifications, such as model number of
product, parts numbers, body number, and many more. It makes a huge difference between current and
future system. It makes huge difference between previous and current system in terms of performance
and customer’s satisfaction. Machine Learning and cognitive approaches will be used for identification
of customers and their vehicle based on the provided information. The system will provide previous
records, which will provide help in their services (Swar, et al., 2012).
It will provide all the details of the customer, which is useful thing to make decision about insurance. It
will stop fraud from starting of the registration processes. It will also change the clam management
process in which deep learning will used to find actual cost of insurance based on the data. It is a way to
reduce frauds in claim management system. It provides actual data of the customer and vehicle within a
second (Thomas, et al., 2017).
The whole system will connect with the data warehouse, which have large amount of data. That data
will collect from different external and internal sources, such as government agencies, private agencies,
and organization. Data warehouse uses ETL processes, which is makes all the data in usable way. Beside
it, structured data is required for search and learning (Tkáč & Verner, 2016).
Machine learning will provides data about the person and assets information, which is helpful for
insurance process. AI and machine learning are highly used technology in many fields to increase
performance of the business processes. Insurance industry is also used it for reducing risks and provide
fast services to the customers (Wright & Schultz, 2018).
In this project, we will apply e-governance to manage all the things, which makes whole system perfect.
It provides online and offline facilities to the customers to manage all their works.

Information System Design 7
It will divide in four parts, which are registration, claim management, customer services, and IT services.
IT services are provided to all other departments. It also monitors all the processes and provides reports
to perspective people to make required changes in the processes. It reduces error in financial calculation
and identification of a customer and their behaviour (Zagorin, 2019).
AI and machine learning technology make a huge impact on the growth of the organziation. It makes
changes in basic processes, which are required changes from security point of view. It change
registration system, which requires all the details and it will check all the information from the national
systems to verify customer. It is a legal process and it will reduce the ratio of frauds (expertsystem.com,
2019).
Employees can improve their knowledge and working style based on the training provided by the
experts. It will have 24*7-customer support. Therefore, anyone can ask their question from experts. AI
assistants will provide whole information about the procedures of insurance and their required things,
which make customers satisfied. Motor vehicles are costly and highly risky. Therefore, it is highly
required to check all the details through machine learning and AI-enabled devices (pressbooks.com,
2019).
AI and machine learning can supports into data analytics to know about the market current situation.
Machine learning provides data based on the deep search and data sets from data centres and data
warehouses. It can use big data and Hadoop technology to data analytics ( Markgraf, 2018).
Broaden and begin implementation of a coherent strategic plan
Building on the insights from AI explorations, companies ought to determine the way to use generation
to help their commercial enterprise approach ( Bughin , et al., 2017). The senior leadership team’s
lengthy-time period strategic plan would require a multiyear transformation that touches operations,
expertise, and era. Some providers are already beginning to take innovative processes along with
beginning their personal challenge-capital palms, obtaining promising rise up organizations, and forging
partnerships with main educational establishments (Balasubramanian, et al., 2018). Insurers have to
expand a perspective on regions they need to invest in to meet or beat the market and what strategic
method as an example, forming a new entity, or constructing in-residence strategic abilities is quality
desirable for their organization (Gupta, et al., 2018).

Information System Design 8
This plan have to deal with all four dimensions involved in any massive-scale, analytics-based totally
initiative the entirety from facts to human beings to tradition (Swar, et al., 2012). The plan ought to
outline an avenue map of AI-based pilots and detail which components of the business enterprise would
require investments in ability building or centered change control (Zagorin, 2019). Most vital, a detailed
timetable of milestones and checkpoints is crucial to allow the agency to determine, on an ordinary
basis, how the plan must be modified to deal with any shifts in the evolution of AI technology and
sizable adjustments or disruptions within the industry ( Sennaar, 2019).
There are four factors, which can change scenario of the future insurance system, which are as:
Explosion of data from IoT-devices: there are different wearable devices available, which provides
health data and other information about the vehicles, such as smartphones, smart watches, home
assistants, and fitness trackers (Thomas, et al., 2017).
Increased prevalence of AI-enabled robotics: in present era, 3D printing is started and it will change
whole market of the insurance industry. In next decade, AI-enabled robots check all the information of
different parts of the vehicles, such as car, bus, and many others.
Open Source and data Ecosystems: open source technology will change the scenario of the next data
analytics. Business intelligence is a best example of it. Data analytics tools are available in the market
and it will provide data records as per requirements, which is beneficial in the decision-making process.
Advances in cognitive technologies: there are many things, which are based on the data. In present
time, deep learning is used for unstructured data, image, and voice. It will evolve in wide verity of
applications to improve their performance.
Data has constantly been on the heart of the coverage industry. What has changed in our cutting-edge
reality to create big disruption is the quantity of statistics generated day by day and the velocity at which
machines can procedure the data and uncovers insights (Fernandez & Fernandez, 2008). We will no
longer signify the insurance industry as a sloth in terms of innovation and era. Artificial intelligence (AI)
and device getting to know are reworking the coverage enterprise in a number of methods (Gupta, et
al., 2018).

Information System Design 9
Source: (Balasubramanian, et al., 2018)
Synthetic Intelligence and device mastering reworking the insurance industry
even though the concept and definition of synthetic intelligence is still morphing because the era
matures, commonly its miles the idea of constructing machines that may suppose like people. The time
period system studying is used to describe the idea of teaching computer systems to research inside the
identical manner human beings do. It represents the main edge of AI (Raymond & Bergeron, 2008).
Due to the fact insurance have constantly been facts heavy, it has drastically affected by AI. Here are
only a few ways the coverage industry is being converted. Coverage recommendation and customer
support from the first interaction whilst determining what coverage is first-rate to ongoing customer
service, machines will maintain to play an increasing function in customer service in the insurance
enterprise (Meister, 2018).
In many surveys, maximum clients do not have a problem with interacting with a bot; 74% of customers
might be happy to get laptop-generated insurance recommendation (Zagorin, 2019). Clients have come
to assume personalized answers, and AI makes that viable by way of reviewing a client profile and
presenting pointers for best insurance merchandise, which can be applicable for that customer and that,
might be the quality for them primarily based on set criteria. Chatbots that paintings with messaging

Information System Design 10
apps are began for use within the enterprise to clear up claims and solution simple questions (Klumpp,
2018).
Transaction and claims processing are surprisingly regulated industry, which coverage enterprise
procedures and thousands of claims as well as responds to lots of customer queries ( Markgraf, 2018). AI
is used to improve this procedure and pass claims thru the system from initial document to speaking
with the consumer. In some cases, these claims do now not require any human interplay in any respect.
The ones companies that have already begun to automate portions in their claims procedure are
realising the time financial savings and multiplied pleasant of service (Swar, et al., 2012).
If the insurance enterprise could correctly mitigate fraud, it might have a powerful impact on each
company’s profit and loss announcement. AI algorithms can become aware of likely fraudulent claims
and spotlight them for similarly investigation and movement by humans if essential. This lets in a
coverage organization to take action lots extra swiftly than relying on people by myself. Organizations
are growing rules and costs whilst coping with danger (Meister, 2018).
The deluge of information and coverage organization has at their disposal and the new methods they
may be soliciting it (pressbooks.com, 2019). In car monitoring gadget that if installed offers the driver a
reduction on rates while feeding the riding facts to the algorithms or records from wearable gadgets
that screen pastime stages and coronary heart charge can inform the kind of policies people qualify for
or comprehend proper behaviour with discounts (Zagorin, 2019). By means of having a greater,
complete photo of clients from a variety of assets, coverage corporations can higher manage risk and
create products and services that serve their customers first-class (expertsystem.com, 2019).
AI and machine learning is making high impact on the insurance industry. It reduces frauds in claim
management system. There are many cases, which is having deficiency in their claims. AI will provide a
solution to resolve them in a proper way. It is a best way to use technology in different industry to
manage their works with high performance and profit in long-terms.

Information System Design 11
References
Adams , . C., 2017. Describe Artificial Intelligence and how it might impact the Business Analysis
profession?. [Online]
Available at: https://www.modernanalyst.com/Careers/InterviewQuestions/tabid/128/ID/3834/
Describe-Artificial-Intelligence-and-how-it-might-impact-the-Business-Analysis-profession.aspx
Bughin , J., Chui , M. & McCarthy , B., 2017. How to make AI work for your business. [Online]
Available at: https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-to-
make-ai-work-for-your-business
[Accessed 22 April 2019].
Davoren, J., 2019. The Three Fundamental Roles of Information Systems in Business. [Online]
Available at: https://smallbusiness.chron.com/three-fundamental-roles-information-systems-business-
23681.html
[Accessed 10 March 2019].
Markgraf, B., 2018. The Three Fundamental Roles of Information Systems in Business. [Online]
Available at: https://yourbusiness.azcentral.com/three-fundamental-roles-information-systems-
business-23383.html
[Accessed 10 March 2019].
Marr, B., 2019. How AI And Machine Learning Are Used To Transform The Insurance Industry. [Online]
Available at: https://www.bernardmarr.com/default.asp?contentID=1199
[Accessed 22 April 2019].
Ransbotham, S., Kiron, D., Gerbert, P. & Reeves, M., 2017. Reshaping Business With Artificial
Intelligence. [Online]
Available at: https://sloanreview.mit.edu/projects/reshaping-business-with-artificial-intelligence/
Sennaar, . K., 2019. How America’s Top 4 Insurance Companies are Using Machine Learning. [Online]
Available at: https://emerj.com/ai-sector-overviews/machine-learning-at-insurance-companies/
[Accessed 22 April 2019].

Information System Design 12
Al-Saggaf, Y., Burmeister, O. K. & Schwartz, M., 2017. Qualifications and ethics education: the views of
ICT professionals. Australasian Journal of Information Systems, p. 21.
Alter, S., 2001. Information systems: Foundation of e-business. 4 ed. New Jersey: Prentice Hall PTR.
Baars, H. & Kemper, H. G., 2008. Management support with structured and unstructured data—an
integrated business intelligence framework. Information Systems Management, 25(2), pp. 132-148.
Balasubramanian, R., McElhaney , D. & Libarikian, A., 2018. Insurance 2030—The impact of AI on the
future of insurance. [Online]
Available at: https://www.mckinsey.com/industries/financial-services/our-insights/insurance-2030-the-
impact-of-ai-on-the-future-of-insurance
[Accessed 22 April 2019].
Bélanger, F. & Crossler, R. E., 2011. Privacy in the digital age: a review of information privacy research in
information systems. MIS quarterly, 35(4), pp. 1017-1042.
Bharadwaj, A., El Sawy, O., Pavlou, P. & Venkatraman, . N., 2013. Digital business strategy: toward a next
generation of insights. Managemengt information system:mis quarterly, 37(2), pp. 471-662.
Burns , . M., 2018. How AI and data technology are transforming the insurance industry. [Online]
Available at: http://techgenix.com/ai-insurance-industry/
[Accessed 22 April 2019].
Castelluccio, M., 2017. Artificial intelligence in business. Strategic Finance, 98(10), p. 55.
Chen, Y.-C., 2010. Citizen-Centric E-Government Services: Understanding Integrated Citizen Service
Information Systems. Social Science Computer Review, 28(4), pp. 427-442.
Dhillon, G. & Torkzadeh, G., 2006. Value focused assessment of information system security in‐
organizations. Information Systems Journal, 16(3), pp. 293-314.
expertsystem.com, 2019. The advantages of using AI in Insurance. [Online]
Available at: https://www.expertsystem.com/advantages-using-ai-insurance/
[Accessed 22 April 2019].
Fernandez, D. J. & Fernandez, J. D., 2008. Agile project management—agilism versus traditional
approaches. Journal of Computer Information Systems, 49(2), pp. 10-17.

Information System Design 13
Ghosh, . P., 2017. The Business Analyst in the World of Artificial Intelligence and Machine Learning.
[Online]
Available at: https://www.dataversity.net/business-analyst-world-artificial-intelligence-machine-
learning/
Gupta, . A. et al., 2018. Big data & analytics for societal impact: Recent research and trends. 20(2), 185-
194.. Information Systems Frontiers, 20(2), pp. 185-194.
INC, 2018. Management Information Systems (MIS). [Online]
Available at: https://www.inc.com/encyclopedia/management-information-systems-mis.html
[Accessed 11 september 2018].
Klumpp, M., 2018. Automation and artificial intelligence in business logistics systems: human reactions
and collaboration requirements. International Journal of Logistics Research and Applications, 21(3), pp.
224-242.
Laudon, , K. C. & Laudon, J. P., 2016. Management information system. s.l.: Pearson Education India.
Meister, . J., 2018. Future Of Work: How Using AI Creates An Enhanced Candidate And Employee
Experience. [Online]
Available at: https://www.forbes.com/sites/jeannemeister/2018/04/10/future-of-work-how-using-
artificial-intelligence-creates-a-best-in-class-employee-experience/#4d99d113620c
[Accessed 10 December 2018].
O'Brien, . J. A. & Marakas, G. M., 2005. Management information systems. 6 ed. New Delhi: McGraw-Hill
Irwin.
pressbooks.com, 2019. Chapter 6: Information Systems Security. [Online]
Available at: https://bus206.pressbooks.com/chapter/chapter-6-information-systems-security/
[Accessed 9 March 2019].
Raymond, . L. & Bergeron, F., 2008. Project management information systems: An empirical study of
their impact on project managers and project success.. International Journal of Project Management,
26(2), pp. 213-220.
Stair, . R. & Reynolds, G., 2013. Principles of information systems. 11 ed. Boston: Cengage Learning.

Information System Design 14
Swar, B., Moon, J., Oh, J. & Rhee, C., 2012. Determinants of relationship quality for IS/IT outsourcing
success in public sector. Information Systems Frontiers, 14(2), pp. 457-475.
Thomas, G., Duessel, P. & Meier, M., 2017. ETHICAL ISSUES OF USER BEHAVIORAL ANALYSIS THROUGH
MACHINE LEARNING. Journal of Information System Security, 13(1).
Tkáč, M. & Verner, R., 2016. Artificial neural networks in business: Two decades of research. Applied Soft
Computing, pp. 788-804.
Wright, . S. A. & Schultz, A. E., 2018. The rising tide of artificial intelligence and business automation:
Developing an ethical framework. Business Horizons, 61(6), pp. 823-832.
Zagorin, E., 2019. Artificial Intelligence in Insurance – Three Trends That Matter. [Online]
Available at: https://emerj.com/ai-sector-overviews/artificial-intelligence-in-insurance-trends/
[Accessed 22 April 2019].