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The Researches on Calculating Method of Insurance Premium of Residential Mortgage Loan

2011· article· en· W1950238674 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian social science · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSafety and Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsActuarial scienceBusinessInsurance policyBond insuranceAuto insurance risk selectionLoanPaymentGeneral insuranceMortgage insuranceCasualty insuranceKey person insuranceStochastic gameFinanceEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

As an effective means to stir up residential consumption, residential mortgage loan insurance is developing very quickly in recent years. However, there are still some inevitable risks, how to calculate insurance rate has been a magnitude task for insurance companies. Based on discrimination between residential mortgage loan insurance and other insurances, the thesis analyze insurance structures of United States, we find that insurance institute in USA can often establish its corresponding insurance structure (include insurance payment mode, number of insurance rate, disposal method when pre-payoff) according to clients’ specific circs (such as sum of loan, term of loan, loan to value), so the controlling of risk of regional mortgage loan insurance is become easy, the rights and interests of insurance institute can be well protected. On the contrary, most insurance companies in China adopt single insurance structure, they require all clients must pay insurance by means of once-payoff method, and they will not send back insurance when the client pre-payoff. This method have some problems, on the one hand it is not benefit to controlling risk of insurance business, on the other hand, it is not benefit to exploit market because it cannot make clients to choice appropriate insurance project according to their specific circs. So insurance structure of regional mortgage loan in China will transit from singularity to diversity in the future. It means that insurance payment mode will include 2 types: once-payoff and annual payment; when borrower want to pre-payoff it can be decided into 2 types: insurance sending back and not sending back, so we will have 4 kinds of insurance structures. on the basis of it, we present new insurance structures which suit for china, and then present a new calculating method which can calculate insurance premium in different insurance structures by using expected return equals the expected loss. Key words: Insurance premium structure; Insurance premium calculation; Residential mortgage loan Resume: C’est un moyen efficace pour attiser la consommation residentielle, l'assurance pret hypothecaire residentielle se developpe tres rapidement depuis ces dernieres annees. Cependant, il y a encore quelques risques inevitables, comment calculer le taux d’assurance a ete une tâche grandeur pour les compagnies d’assurance. Base sur la discrimination entre l’assurance pret hypothecaire residentiel et d’autres assurances, la these d’analyser les structures d’assurance des Etats-Unis, nous constatons que l’Institut d’assurance aux Etats-Unis peuvent souvent etablir sa structure d’assurance correspondant (notamment le mode de paiement d’assurance, le nombre de taux d’assurance methode d’elimination, lors du pre –gain) selon circs clients specifiques (comme la somme du pret, la duree du pret, pret a la valeur), de sorte que le controle des risques de l’assurance pret hypothecaire regional est devenu facile, les droits et les interets de l’Institut d’assurance peuvent etre bien protege . Au contraire, la plupart des compagnies d’assurance en Chine d’adopter la structure unique des assurances, ils exigent que tous les clients doivent payer l’assurance par le biais d’une fois gain methode, et ils ne renverra pas d’assurance lorsque le client pre-paiement. Cette methode a quelques problemes, d’une part, il n’est pas benefique pour la maitrise des risques des activites d’assurance, d’autre part, il n’est pas beneficier d’exploiter le marche car il ne peut pas faire aux clients de projet d’assurance choix approprie en fonction de leur circs specifiques. Par consequent la structure d’assurance de prets hypothecaires regionales en Chine transite par la singularite dans la diversite a l’avenir. Cela signifie que le mode de paiement d’assurance comprennent deux types : le paiement une fois gain et annuels, lorsque l’emprunteur souhaitez pre-gain il peut etre decide en 2 types : l’assurance de renvoyer et de ne pas renvoyer, alors nous aurons quatre types de structures d’assurance . Sur la base de celui-ci, nous presentons les structures d’assurance nouvelle qui conviennent pour la Chine, et ensuite presenter une nouvelle methode de calcul qui permet de calculer la prime d’assurance dans les structures d’assurance differents en utilisant le rendement attendu est egal a la perte attendue. Mots cles: La Structure des primes d'assurance; Le calcul des primes d'assurance; Prets hypothecaires residentiels

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.877
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.299
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it