智能財務核保整合系統

In traditional insurance underwriting and actuarial science, we have been constantly searching for meaningful information indicators to clearly determine the corresponding pricing according to risk characteristics. The insurance company's risk assessment of customers is generally based on the information disclosed by the applicant, including health notices, financial statements and other information.This research project extends the results of the previous successful project, and proposes to develop an Intelligent Underwriting System for Insurance Approval. At present, when the insurance company undertakes the insurance application of its customers, it needs to further analyze the underwriting items and underwriting risks through various information provided by the customers. The underwriter needs to manually assess the total value of the customer's financial assets and real estate, and confirm that the customer's financial ability must be in line with its insurance status (insured amount or premium). However, the evaluation and assessment process requires manual inspection of its financial or income details, or connection to the real price log-in system to determine the possible price of real estate, which is not only time-consuming, but also error-prone due to different experiences in underwriters. The Intelligent Underwriting System can provide insurance companies with an automated and standardized underwriting process. The main objectives of this research are how to effectively use multiple technologies such as machine learning ( data mining ) , natural language processing ( including statistics and symbols or semantics ) , and artificial intelligence (intelligent systems) to develop an intelligent financial underwriting system.