ПОТРЕБИТЕЛЬСКОЕ КРЕДИТОВАНИЕ В РОССИИ: ОСНОВНЫЕ ПРОБЛЕМЫ НА СОВРЕМЕННОМ ЭТАПЕ
Bibliographic record
Abstract
This article is devoted to the current state and problems of consumer lending in Russian commercial banks. As a result of the research, it was found that during the analyzed period, the volume of consumer lending in Russia increased, reaching the level of 17 475 billion rubles in December 2019. Almost half of the working population of Russia has consumer loans. In January - February 2020, 2.61 million consumer loans were issued. The identified problems in the sphere of consumer lending included: unsecured loans, a decrease in the solvency of the population, a fairly rapid spread of Express lending (from January 2018 to January 2019, the growth in the volume of issued POS loans amounted to 8.8%), high interest rates on consumer loans, and as a result, a high percentage of non-repayment of loans. The share of overdue debt on consumer loans is still quite high, although it has a reduction dynamics. in the 4th quarter of 2019, the decrease in the share of overdue debt on consumer loans is typical for almost all regions. In January 2020, the reduction of consumer loan debt (15.5%) continued.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.313 | 0.000 |
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.
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 teacher head, 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".