1. Improve the Introduction part. It has to answer all the set questions in regard to the technology chosen (risk assessment technology). These are the question:
Give a brief background/history of the technology.
What is the technology?
Why is it interesting?
How is it used and who uses it, etc.?
How does the technology compare to previous technologies that served a similar purpose?
2. Improve Problem Statement section.
The section has to describe the problem and end with a clearly articulated Problem Statement.
Writer’s Name
Institute Name
Course
Date
How Car Insurance Company Earns Money?
The car insurance companies heavily involve in the risk assessment activities, which refer to the process using which the risks associated with each client may be identified. Without conducting efficient risk assessment, the car insurance companies may face severe financial losses as they are always obliged to pay for insured cars. Since the events of car accidents and damages have considerably increased in the present times (Bian, Yang, Zhao & Liang), the car insurance providers have been using advanced risk assessment technology. The technology of risk assessment heavily relies on the math concepts of probability and optimization. In future, the technologies of big data and artificial intelligence will further support the processes of risk assessment for the insurance service providers.
How it Works
Efficient use of probability and optimization techniques aid the insurance companies to assess risk of each of the policy holders as well as the prospective investors. Based on this analysis, the insurance companies become able to identify the most suitable stakeholders which reduces the chances of loss for them.
Problem Statement
Car insurance providers always risk financial losses due to the nature of their business. These companies charge a monthly premium from the customers against which they are obliged to pay for any damage or loss happened to the customer’s vehicle. It would never be possible for the car insurance companies to operate without calculating the probabilities of generating profits. The companies always conduct risk assessment for each of the plans they are offering to the consumers (Osafune, Takahashi, Kiyama, Sobue, Yamaguchi & Higashino). The risks and the probability of loss is calculated based on the profile and history of each customers. Similarly, the car insurance companies need to invest in multiple places in order to sustain their business. When it comes to investing, the companies always conduct market analysis, do market survey to find out the best investment options and subsequently math is used to identify the probabilities associated with loss or success.
Concepts of Math
The insurance companies do not only generate the profits by charging premium from the customers. These companies often invest their amount in the businesses which come out to be most profitable. Furthermore, these companies often reject the application for car insurance; for example, if the company detects that a person who has applied for the insurance has a frequent history of accidents, the company rejects his insurance application; again, for this initial or periodic assessment of the consumers, it is important for the company to be able to conduct efficient risk assessment. The two important concepts of math which are most relevant for the car insurance companies are probability and optimization.
Probability is defined as the chance of occurrence and it is calculated based on the number of factors. For example, when a person applies for car insurance, the company would include various factors into account for conducting the risk assessment. These factors would most probably include age of the applicant, his/her income, previous history of accidents, health condition, etc. Each of this factor would be assigned specific probability and subsequently, the risk assessment would be conducted. The value of probability for each factor would be associated based on the past experience of the company or market research. This way, the concept of probability can be used to identify the chances of loss or profit for the company.
On the other hand, the concept of optimization is also often used while conducting the risk assessment. The optimization problems generally target at minimizing the loss or maximizing the profits for the company. For example, a company may design a problem for identifying the optimum price of premium per month for customers, if it desires to keep the profit at maximum. Since, it is not possible to achieve 100% profit, the optimization problems generally seek combined optimization of profit and loss. Hence, optimization helps the insurance companies to decide premium cost efficiently.
Future
Although the concepts of math and physics have heavily been used by the car insurance companies for the process of risk assessment, it is expected that the risks would be analyzed more accurately in the near future. The accuracy of the risks calculated by the car insurance companies is expected to improve due to the rapid growth in the information technology. Various fields of computing relate to risk assessment and prediction of profits or loss. For example, the emergence of big data would offer the car insurance companies with a chance to do more accurate risk assessment as compared to present. The companies would be able to identify the patterns of losses they or similar companies have faced in the past. Furthermore, the concepts of big data would aid the car insurance providers to have an insight about the driving patterns of each driver they are issuing policy to (Zhang, Xu, Cheng, Chen, & Zhao). Since big data is based on huge collection of data, the car insurance companies would become able to analyze different scenarios which had occurred in the past and could identify the risk associated with each issued policy or investment.
The big data that is expected to revolutionize the car insurance industry relates to the sensors installed in the car or wearable by the drivers. The technology of risk assessment by the car insurance companies would be directly linked with the concepts of vehicular networks or internet of everything (Soleymanian, Weinberg, & Zhu). The sensors installed in the car would be collecting data about the driver’s speed as well as his health conditions (through monitoring heart rate, blood glucose level and other vital parameters). This data from the sensors can then be used by the car insurance companies to make informed decisions about whether or not issue/continue the policy for a specific driver.
Also, the technology of using math for car insurance is expected to be continued over next 50 years. As the purchasing power of consumers have been increasing, there is a strong likelihood that the number of cars on the roads would increase significantly; in turn, the insurance companies would also be getting more requests for car insurances. Due to the increase in the number of drivers, the companies would have to analyze a number of factors based on which they can make the decision on whether or not a policy should be granted. Clearly, the companies would continue using mathematical models integrated with computing technologies in order to assess the risk associated with each consumer.
Conclusion
The car insurance companies heavily rely on math concepts of probability and optimization for conducting their risk assessment activities efficiently. These concepts are used to identify the customers whom the policy should be issues, as well as to identify the most feasible investment options. the probability helps to provide a comparative insight about different options of customers and investment. Also, optimization helps the companies to understand that what should be the cost of premium if they want to ensure a certain value of profit and loss. It is expected that in future, the technologies of risk assessment would further advance for the car insurance companies, due to emergence of fields such as big data and artificial intelligence. In conclusion, it is not possible for the car insurance companies to conduct risk assessment without using concepts of math.
Works Cited
Bian, Yiyang, et al. “Good drivers pay less: A study of usage-based vehicle insurance models.” Transportation research part A: policy and practice 107 (2018): 20-34.
Osafune, Tatsuaki, et al. “Analysis of accident risks from driving behaviors.” International journal of intelligent transportation systems research 15.3 (2017): 192-202.
Soleymanian, Miremad, Charles Weinberg, and Ting Zhu. “Sensor data, privacy, and behavioral tracking: does usage-based auto insurance benefit drivers.” Marketing Science, University of British Colombia (2017).
Zhang, Heng, et al. “Big data research on driving behavior model and auto insurance pricing factors based on UBI.” International Conference On Signal And Information Processing, Networking And Computers. Springer, Singapore, 2017.
Term Paper
AMS 103, Fall 2019
Description
Over the course of the semester we will explore how mathematical concepts underlie many modern technologies.
The goal of this paper is for you to extend this type of analysis to a technology of your choice. As discussed below,
your choice of technology must be approved and cannot be one covered in lecture. I encourage you to look at the
table of contents from The Princeton Companion to Applied Mathematics for ideas (a link is posted on Blackboard
in the “What is Applied Mathematics?” folder).
The paper will be submitted twice. The first submission will undergo a round of peer review, after which you will
have the opportunity to revise your paper. The second (final) submission will be graded by the instructor or a TA.
The same rubric (given below) will be used throughout. The target audience of the paper is an AMS 103 student.
Grade Breakdown
In total, the term paper is worth 50% of your final grade in AMS 103: 20% for the “process” and 30% for the final
draft. The 20% for the “process” will be allocated as:
• 20%: Submit a choice of topic on time.
• 15%: Submit the first draft on time.
• 25%: The first draft is a “good-faith” submission (see below).
• 40%: Participation in the peer review process.
The final draft will be scored using the rubric. If not submitted on time, the first draft will be scored (assuming it
was submitted).
Important Dates
These dates are tentative. Any changes will be announced both in lecture and via Blackboard/email.
• September 19 2019: Your choice of technology is due. You will be notified by June 11 whether your topic
is approved or if you need to make a different selection.
• October 17 2019: First draft of your paper is due.
• October 31 2019: Your (anonymous) reviews of classmates’ papers are due.
• November 14 2019: Your final draft is due.
Paper Outline
Your paper should address the following points. These bullets may be used as section headings in your paper, but
are not required to be.
• Introduction: Give a brief background/history of the technology. What is the technology? Why is
it interesting? How is it used and who uses it, etc.? How does the technology compare to previous
technologies that served a similar purpose?
AMS 103, Fall 2019 Page 2/4
• How It Works: Give a high-level description of how the technology works. Of course, you are not expected
to understand or discuss all details of the technology.
• Problem Statement: Give, as clearly as possible, a description of a role mathematics has in the technology.
Try to formulate it as a precise problem statement or question. For example, in our discussion of GPS, we
formulated the precise problem of determining the number of satellites needed to identify your location.
• Math Concept(s): What math concept(s) can be/are used to address your problem statement? You do not
necessarily need to solve the problem statement; but you should discuss how these math concept(s) work
toward solving it. You are encouraged to illustrate each concept with a small example.
Make sure your math concept is not a physics or engineering concept in disguise (for example), and is
discussed at a level suitable for AMS 103 (e.g., familiarity with calculus cannot be assumed). Math concepts
include geometry, statistics, number theory, coordinate systems, optimization problems, information theory,
inverse problems, algorithmic analysis, graph theory, integrals, differential equations, and many others. An
equation is too trivial of a math concept for this assignment.
• Future: Speculate about the future of the technology, if it seems appropriate. How might it develop or
improve? In your opinion, will it still be relevant in 50 years?
• References: List your sources! These are likely to be webpages, but may not be. Wikipedia should not be
used; it may be a great place to find general information, but should not be cited. Verify the information
on wikipedia from other sources and cite them instead. At least three or four sources should be cited.
You should use MLA or APA formats for your references (your choice, but only pick one). Make sure to
include the title, URL, date accessed, and author (if known) for each webpage. References must be written
in English. You should have in-text citations to your works cited list throughout your paper to indicate the
specific source of a statement in your discussion.
You should target the text of your paper to be between 3 and 4 pages in length (double-spaced, 12pt font, 1”
margins). The “text” does not include headers, titles, images, or references, etc. The absolute minimum is 2.5 full
pages of text. The text may extend onto a fifth page—especially if you use figures or illustrations—but should not
go onto a sixth page.
Milestone: Choice of Technology
You must submit your choice of technology for approval. At the same time, you will be asked for a short justification
of your choice: Why are you interested in this technology and what mathematical concept(s) do you anticipate
discussing in your paper? You may not use a technology that we discuss in lecture (consult the syllabus for a list).
Within a week of the due date, either your choice will be approved or you will be asked to submit a different
choice. You will be awarded full credit for this milestone by submitting your choice and justification before the
deadline, regardless of the initial outcome.
Milestone: First Draft
Your first draft must be submitted by the deadline so that it can be peer reviewed. It is expected that your first draft
is a “good-faith” submission, meaning it is not a placeholder that you plan to replace in the second submission.
In addition to the peer review, the instructor/TAs will examine your paper to determine if it is a “good-faith”
submission. “Good-faith” submissions will receive full credit for this milestone; other submissions will receive
partial or possibly no credit.
Do not include your name, student ID, or any personally identifiable information in your first draft. The peer
review is to be double blind. The instructor/TAs will know, through Blackboard, which submission is yours. Full
AMS 103, Fall 2019 Page 3/4
credit for this milestone will not be awarded if your paper is identifiable to other students.
Milestone: Peer Review
You will review approximately 4 of your classmates’ first drafts using the rubric presented below. You will not
know whose submissions you are reviewing, nor will they know your identity. You will also perform a selfreflection on your own first draft after reviewing your classmates’ papers. Logistics of the review process will be
discussed at a later time.
The goal of this step is for you to critically assess your paper, as well as your classmates’. Sometimes the best
introspection is accomplished after seeing what worked (or didn’t work) for other people. Bear in mind: although
this step requires you to be critical, you should always be constructive in your criticism. How would addressing
your criticism(s) help the author improve his/her paper? To ensure that thoughtful/useful/constructive peer reviews
are provided, the instructor/TAs will audit the peer reviews for quality and tone. Full credit will not be given for
the peer review if the comments you provide are deemed unprofessional or unconstructive. Note that the scores
you receive from your peers will not impact your grade.
To help you provide more useful comments to your peers when you review their papers, I list here some common
problems that have appeared in previous semesters.
• The paper focuses on an interesting science or engineering problem, but not a technology. The goal is not
to find interesting applications for math, but to discuss interesting technological applications for math.
• The problem statement is absent or implied. In almost every case, this statement will help you focus the
various components of the paper to produce an easy-to-read document. Make the problem statement clear!
• The discussion of math concepts is too detailed. Remember that your paper should target other AMS 103
students. It’s perfectly okay to use (for example) “integral calculus” as a math concept, so long as you
explain both
1. what it is (conceptually),
2. how it helps you address your problem statement.
Equations are not required, and in many cases are unnecessary. If you choose to include equations, make
sure you explain what they represent and how they relate to the problem statement.
• The math concepts are physics concepts (for example) in disguise. From the GPS unit, the speed-distancetime equation is not a math concept. Having an equation as the math concept usually indicates this mistake.
• The math concepts and technology are seemingly unrelated. In most cases, this is a consequence of not
effectively formulating the problem statement (see above).
• In-text citations are missing.
• Items in the bibliography do not contain URLs or are otherwise incomplete.
• Images are improperly used. If you think it necessary, it is fine to include images (along with proper citation
and attribution). However, make sure you discuss the image in your text. Why did you include it? Images
are distracting, and potentially confusing, to the reader if only included for visual stimulation.
Milestone: Final Draft
After receiving comments from your peers, you will be given some time to revise your paper. You will then submit
a final draft that will be scored by the instructor/TAs.
AMS 103, Fall 2019 Page 4/4
Rubric
Each category will be equally weighted towards your assessment.
Category Excellent (4) Good (3) Mediocre (2) Poor (1) Fail (0)
Formatting,
Length, &
Citations
Formatting
guidelines were
followed and
in-text citations were used
appropriately.
Most formatting
guidelines were
followed.
Some formatting guidelines
were followed
or in-text citations were
inconsistently
used.
Few formatting
guidelines were
followed.
Formatting
guidelines were
not followed,
the paper was
too short or too
long, or in-text
citations were
missing.
Content:
Technology
The technology
was introduced
well and its uses
were sufficiently
discussed.
Small issues
need clarification.
Some major
questions regarding the
technology or
its uses are not
addressed.
The technology or its uses
are hardly
discussed.
It is not possible
to understand the
technology or its
uses from the paper.
Content:
Math
Concepts
The math concepts are relevant and well
discussed.
The math concepts are mostly
clear.
The math concepts are somewhat unclear.
The math concepts are mostly
unclear or are
not “math concepts”.
The math concepts (if present)
are unclear.
Content:
Overall
The paper provides a focused
discussion of the
technology and
the math concepts related to
it.
An adequate discussion is provided but small
parts need additional clarification.
The paper is unfocused at times
and the link between technology and math
is somewhat unclear.
The connection between
technology and
math is mostly
unclear.
The paper is unfocused with no
connection between technology and math.
Writing Quality
and/or
Grammar
The paper is well
written with few
(if any) grammar
mistakes.
Errors are noticeable but do
not interfere
with understanding.
Errors make
parts of the
paper difficult to
understand.
Large portions
of the paper are
difficult to understand.
The paper is undecipherable.
References At least 3–4 suitable references
are provided.
At least 3–4 suitable references
are incompletely
provided.
1–2 suitable references are provided.
1–2 suitable references are incompletely provided