THE APPLICATION OF MARKOV CHAIN AND MONTE CARLO SIMULATION ON THE DETERMINATION OF THE RISK PREMIUM OF A CYBER INSURANCE WITH A LOGIT-NORMAL DISTRIBUTION APPROACH
Along with the development of information technology, the need for the internet has become one of the most important things. With the increasing number of internet users today, the insurance industry is exposed to new opportunities relating to the protection of digital data. A new type of insuran...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/55197 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Along with the development of information technology, the need for the internet
has become one of the most important things. With the increasing number of
internet users today, the insurance industry is exposed to new opportunities relating
to the protection of digital data. A new type of insurance emerged called cyber
insurance. This final project discusses a financial loss model for cyber insurance
using Markov Chain. In this final project, the financial losses due to cyber-attacks
is assumed to be a proportion of a certain value. A probability distribution for
the proportion used in this final project is a Logit-normal distribution. The cyber
insurance model is then used to determine the risk premium with the help of the
Monte Carlo simulation. The determination of the risk premium uses three risk
measures, namely: the Standard Deviation Principle; Value-at-Risk or VaR; and
Tail Value-at-Risk or TVaR. |
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