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RISK DATA Nature of risk and uncertainty Concept of insurance and risk assessment Measurement of risk

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CONCEPT OF INSURANCE AND RISK ASSESSMENT Techniques for identification of risk: Ascertaining causes and consequences of events but... Events are not all equally likely do not hold the same potential cost

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MEASUREMENT OF RISK Objective Judge whether the insurance premium is reasonable

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QUANTITATIVE METHODS Insurance relies on accurate use of numbers The business world is becoming more and more quantitative Encouragement towards a disciplined pattern of thought

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ACCURATE USE OF NUMBERS Collection of data Tabulation of data Description of data Analysis and interpretation of data Likelihood estimation Calculation of premiums Payments of insurance Arrangement of reinsurances

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BUSINESS WORLD MORE AND MORE QUANTITATIVE Advent of computers Computer literacy Need for numeracy

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DISCIPLINED PATTERN OF THOUGHT Study of quantitative concepts Logical approach to problem Elimination of invalid arguments

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FEATURES OF RISK DATA FREQUENCY (Likelihood of risk) SEVERITY (Cost of risk)

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PROFILES High frequency / low severity E.gFire losses (High level of predictability) Low frequency / high severity E.g Losses at sea (High level of uncertainty)

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Figure 4.1 Right-hand end Decide on the strategy for funding the risk Take steps to be protected from the consequences Purchase some kind of insurance

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Figure 4.1 Left-hand end Make reasonably accurate estimates of the cost of losses Devise some form of self-funding

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DATABASES They help to Make good decisions Make accurate forecasts Improve judgement

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INSURANCE DATABASES Fire Theft Accidental damage

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DATABASES PROVIDE Number of variables Nature of variables (discrete / continuous) Category of variables (qualitative / quantitative)

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USE OF EXISTING DATABASES (Disadvantages) Collected for some entirely different purpose Incompleteness of data Lack of control Inheritance of faults Outdated Limitations and inadequacies unknown

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USE OF EXISTING DATABASES (Advantages) Less time-consuming Less expensive

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