ABSTRACTThe regulatory framework for assessing and risk measurement in most companies focuses primarily on proposals of the New Capital Accord (Basel II). The Basel Committee gives importance to the concept of operational risk and requires that financial institutions cover possible loses with capital. The goal is to identify expected losses because of different events that might arise in firm management. This work develops a model to estimate the monetary loss due to car theft for Columbian insurance companies. We estimate the probability functions of monetary losses for car theft. First we estimate the distribution functions of the number of car thefts and for the monetary loss. Then, we use Monte Carlo simulation to identify the severity of expected losses. The results and conclusions will be useful for insurance firms. Using the results here, they can set up guidelines to improve risk management.JEL: G22; C15KEYWORDS: Insurance, Operational Risk, Simulation, Loss Distribution Aggregated.AbbreviationsAMA Advanced Measurement Methods / Advanced Measurement ApproachesANPR: Notice of Proposed Rulemaking / Advance Notice of Proposed Rulemaking(ProQuest: ... denotes formulae omitted.)INTRODUCTIONIs important to identify and value enterprise operational risk. Potentially, the operative faults affect all businesses. Manufacturing enterprises, commercial, financial services both large and small could experience monetary losses caused by their workers, internal and external frauds, human and technical wrongs, government policies or economic cycles. Company exposure to monetary loss may be higher or lower for several reasons. We find some conflicts between interests between rapid growth, internal changes, financial condition, weak culture control and corruption in the country or region. Not only do giants like Enron and governments have losses because of fraud but also small financial institutions and small businesses experience losses (Sivirichi, 2010). In Colombia, manufacturing companies, services and financial markets enterprises undergo constant development and transformation that dramatically increases the likelihood of adverse events. This creates an unending dynamic, marked by mergers and takeovers, internal streamlining and technical upgrading.In addition, the complexity of transactions associated with product life cycle cause exposure to operational risk. This paper supplies a knowledge base to build an organized view of management. We quantify operational risk and measure risk events. This work is split into three parts: The first focuses on generic ideas and definitions of operational risk, based on the Basel Committee approach. In the second phase we show the present state of the insurance sector against losses because of car theft in the region. The third part shows how to use probability distribution functions to model the number of stolen cars and monetary losses - from 2004 to 2009-. Finally, we use Monte Carlo Simulation (MS) to identify the severity of expected car theft losses for 201 1.LITERATURE REVIEWSimulation is accepted widely in both an educational and business context. It helps us to explain and predict and identify best solutions to decision problems. It also provides an in depth analysis when we want to assess events with high degree of uncertainty. In addition, the simulation provides comprehensive vision of the event under study and overcomes limits of analysis based only on historical data. It describes the behavior by a probability distribution function and therefore considers the probabilities of events happening.Evans (1998) define simulation as the procedure of building a logical-mathematical model that represents an observable fact and allows us to experiment with it, to understand behavior and help us make decisions. It is important to identify inputs and their probability distribution function. We must also define interdependencies to describe behavior by means of covariance or correlation analysis to explain the expected behavior. …