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Auto Mobile Insurance Auto Mobile Insurance The regulatory framework that assesses the risk measurement in most companiesfocus on the New Capital Accord. According to Coughlin & Schneider (2014), the Basel Committee the concept of operational risk requires financial institutions to cover the loss with capital. According to Keeton (2010), it is crucial to identify value enterprise operational risk that has potential operative faults to hinder successful business. This paper will highlight complexities that associate with product life cycle to cause operational risk.

The paper has three parts split as follows (1) definition and description operational risk, (2) the present stare of insurance sector against losses of car theft, and (3) probability distribution to reflect number of stolen cars and loss suffered. The study uses Monte Carlo Simulation to evaluate car theft losses. Majka (2012), Cook (2010), and Zavadil (2011) believe that simulation can work in both education and business sector and can predict best solutions to the decision problems. Coughlin & Schneider (2014) defines simulation as the procedure of building a logical-mathematical model to represent the observable fact to allow people experiment with it.

Simulation can solve problems and events that have uncertainty. Cook (2010) show that economic loss by operational risk can generalize other distributions. One can insure economic losses and other estimations that include stochastic analysis for insurance firms. Majka (2012) defines operational risk as a potential loss that arises from failure or shortages of information systems in the internal control systems or errors in the processing investment. Weisburd (2014) defines operational risk that arises from failure or weakness in strategic planning, business management, or external events that include legal risk.

Concerning operational risk assessment, companies measure and process data efficiently. Currently the government sectors regulate and formalize the idea that include rigor to collect and control operational risk events. Weisburd (2014) defines risk as the volatility of expected results that relate to the value of assets and liabilities.Events that associate with Insurance Management in Colombia The insurance industry takes a lead in Columbian economy due to its presence as an institutional investor.

Columbian Federation of Insurers called the FASECOLDA is a nonprofit making institution that provides technical, legal, and economic support to its partners. Year 2012 data of Fasecolda reveal a theft of close to 5000 cars. Different authors illustrate how insurance fraud is misconduct. The National Institute for Research and Prevention of Fraud (INIF) main objective is to build a culture of antifraud among insurance users and give partner companies with apt solutions to reduce fraud risk through internal policies leading to efficiency in car insurance.

According to Coughlin & Schneider (2014), cars, vans, and heavy vehicles are most affected by theft. The allegations known to theft are known to the INIF. The prosecution office allows Fasecolda to access statistics on most stolen cars in the country. Simulation models cite that Mazda, Chevrolet Aveo, Clio,Renault Twingo, and Corsa are some of the most wanted by thieves. The criminals use a carousel scheme to commit the theft that entails securing a car, committing fraud and charging the fraud to the insurance company.

They later recover the car and take it to another insurance company so that they can repeat the process. At the onset, the process since companies’ works in solitude against fraud since there was no legislation that links insurance companies, police enforcement, and prosecutors to help detect fraud. Different authors state that Columbia has different kinds of fraud that include carousel, gemeleo, planned, and inflated losses. Planned fraud entails fake accidents to collect insurance, while gemeleo entails placing a legal car plate on a stolen car and circulate the car to a different city.

Carousel fraud entails reporting a car as stolen to different insurance companies where multiple claims for collection are submitted. Inflated losses have real losses the issue is that claims do not match the real damage to the vehicle. An insured uses this opportunity to fix a previously damaged car.Keeton (2010) assert that a high percentage of companies in Columbia have a poor concept of operational risk. The management performs audit actions and internal controls in a bid to identify the sources of operational risk exposure and not their quantification.

Keeton (2010) use a fit of parametric distribution to update losses that use update inflation. The procedure permits one to express the economics of loss to a base year 2010. The estimation of the loss distributed aggregated using operational risk combined with discrete variables and continuous variables. A simple MS uses an analytical method to permit convolution of the distributions of thefts and losses to produce aggregate loss distribution. Some of the methods in use to estimate Operative Risk that exist including Fuzzy Logic, MS, and Extreme Value Theory.

One uses the techniques depending on the historical data of car theft in Columbia. The author adjusts probability distribution function and the severity of loss on the thefts that occur. The Operational Risk for car theft is greater as number of issued policies increase in cities of Bogota and Medellin. The rest of the country shows a rising trend as time lapses. Theft increases as December approaches, firms need a process of risk management approved by management. In future cars should have distinct color to set boundaries that permit development of different rates of cities.

Companies can run the model in different cities, regions, or departments to identify the influence of successful companies and permit them to lower risk by increasing reinsurance, premiums, and the rejection of the business line in different cities. Insurance companies can apply statistical and mathematical methods to measure Operational Risk. ReferencesA report to the Senate of the 62nd Legislature State of Texas. (2011). Austin: [The Committee].Connell, J., & Wilson, W. (2009). Car insurance and consumer desires.

Urbana: University of Illinois Press.Cook, M. (2010). Personal risk management and property-casualty insurance. Malvern, Pa.: The Institutes.Coughlin, G., & Schneider, J. (2014). You and your car insurance; the dos and donts of automobile accident claims and insurance,. New York: Morrow.Frank, M., & Roehrig, P. (2012). Code halos: How the digital lives of people, things, and organizations are changing the rules of business.Keeton, R. (2010). Crisis in car insurance. Urbana: University of Illinois Press.Majka, P. (2012).

You can save a bundle on your car insurance. New York, N.Y.: St. Martins Press.Weisburd, S. (2014). Identifying Moral Hazard in Car Insurance Contracts. Review of Economics and Statistics, 140321095115002-140321095115002.Zavadil, T. (2011). Do the Better Insured Cause More Damage? Testing for Asymmetric Information in Car Insurance. Journal of Risk and Insurance, N/a-N/a.