| 摘要(英) |
The Taiwanese government established the "Taiwan Health Insurance Arrears and Late Fees Installment Method" in 2003, so that people who cannot pay off the arrears will have another payment option and the eligibility is very loose, as long as the total arrears exceeds NT$2,000.
Even so, there are still 8,000 cases (approximately 56.43%) of default cancellation due to failure to pay fees on time every year. However, according to the current handling method prescribed by the public authorities in Taiwan, only the minimum threshold and the number of fee periods can only be handled according to the undertaker.
The subjective handling of arrears instalment application cases completely ignores the applicant’s financial status, which leads to problems such as administrative inefficiency and customer litigation disputes.
This research uses an objective basis to evaluate the application phases to effectively reduce human interference and increase the contract performance rate.The basic data variables that may affect personal credit are classified as Logistic regression ModelⅠand the personal behavior that may affect installment payments are classified as Logistic regression ModelⅡ, using Logistic Regression analysis, KS test and ROC respectively Curve analysis, after estimating the significant variables, summarize the significant variables as Logistic regression Model Ⅲ, and perform Logistic regression analysis and model verification again to obtain age, gender, insurance type, number of installments, amount of installment, and number of installments and other 6 significant impact factors.
Finally, it is recommended that the public sector fully introduce the FICO (Fair Isaac Corporation) scoring system, by converting the FICO scoring system into an objective scoring mechanism for insurance premium installment applications, and the first to introduce the scoring mechanism into the public sector in a systematic way, which can effectively improve efficiency.
In addition, public sector agencies can extensively establish risk mechanisms in their core business, and have moved towards warning before the incident, reducing remedial actions after the incident or incurring a large amount of administrative costs.
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