Data Analytics Risk Transfer Data Analysis

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Data analytics, cyber capabilities, climate change, and the most recent pandemic have fundamentally altered the way insurance is disseminated around the world. For one, the uncertainty surrounding insurance clauses such as “Force Majeure,” have caused insurance companies to pay higher costs related to business disruptions and legal expenses. Likewise, the widespread nature of claims, in certain instances, threaten the solvency of insurance companies who did not appropriate model large business disruptions throughout the world. As a result, there is fundamental shift in the way management engages with insurance companies, how insurances companies retain clients, and how risk is effectively transferred to avoid solvency issues.To begin, the recent COVID-19 pandemic has reshaped many definitions related to insured perils. This is heavily related to insurance contracts who often did not include epidemics or pandemics within the contract. As a result, insurance contracts now include specific language related to these perils and how they will apply to the “force majeure” standard. This is particularly important for insurance related to small businesses or other “Mom and Pop” operations which often have very low working capital buffers to support a prolonged business disruption. Therefore, managers of these operations are looking to pay for coverage that clearly provides indemnification for unforeseen circumstances related to pandemics or epidemics. This will be a trend of future insurance contracts which will look to further clarify definitions, provide specific claim limits, and eliminate obscure language (Dercon, 2003).Data analytics has also significantly impacted the overall insurance industry.

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Data analytics, when utilized properly, heavily reduces the loss ratio for insurance companies. With lower losses, insurances companies can increase profitability by maintaining relatively modest returns on their float and invested premium. Companies such as Progressive and Geico have heavily utilize data analytics to further segment their insured population.…

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…will typically protect the business from bankruptcy, default, or other perils agreed to within the contract. Businesses engage in this form of insurance to protect their cash flow and maintain adequate working capital to run the business in the event of a major customer default. This is ideal for small business, who typically have one or two major customers. As such, a default, could endanger the overall continuing operations of the business. Here, government involvement helps the market to the extent that capital dries up or insures are unwilling underwrite policies. Here government intervention can ensure consumer confidence, maintain the integrity of the market, and provide an emergency backstop in the event of many defaults within the business environment. This maintains the market as insures are more confident that the government can intervene on their behalf. Likewise, the insured have assurances that the contracts will be maintain and upheld….....

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"Data Analytics Risk Transfer" (2022, May 25) Retrieved May 20, 2025, from
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