Calificación crediticia y morosidad de tarjetas de crédito en clientes del Banco Interbank tienda Cusco periodo 2016.
Bibliographic record
Abstract
This research work entitled "CREDIT EVALUATION AND MORTALITY OF CREDIT CARDS IN CUSTOMERS OF THE BANK INTERBANK SHOP CUSCO FIRST QUARTER PERIOD 2016". Its purpose is to describe the credit \nassessment of a customer with delinquency due to the use of credit cards of Bank Interbank Store Cusco in the first quarter of 2016. \nChapter I discusses the introduction, formulation of problem formulation and specific objectives of credit assessment and credit card delinquency. \nChapter II provides the background to the research, as well as the conceptual framework, hypotheses and variables. \nChapter III uses research approaches and tools. \n Chapter IV shows the tables and figures, to reflect the studies of the investigation that came to be realized. \nChapter V presents the results and relevant findings of the research carried out \non credit cards. \nThe research is a quantitative approach, since data collection is used to test the \nhypothesis, to establish behavior patterns and to test theories, the data collected in the field work will be processed in an Excel sheet and in the SPSS program. \nThe contribution of the research work is to make known the importance of performing a demanding evaluation, to review with responsibility and giving due \nimportance to each one of its aspects, both the willingness to pay and ability to pay. Knowing all these aspects will tell the financial representative to know your \ncustomers and warn you about your willingness to pay and determine your ability to pay. \nThus the good and rigorous evaluation of credit cards will generate in the long term a portfolio of quality. \nIt has been concluded that the credit assessment of credit cards is reflected inthe willingness to pay and ability to pay; And delinquency will be reflected in the delinquency levels according to their days of arrears at Interbank Bank Cusco store in the first quarter of 2016.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".