PEER-TO-PEER LENDING PLATFORM: FROM SUBSTITUTION TO COMPLEMENTARY FOR RURAL BANKS
Bibliographic record
Abstract
This study aims to examine the impact of the growth of peer-to-peer (P2P) lending on the growth of rural bank lending. Further, this study investigates the outcome of the partnership agreement between the Rural Bank Association and Financial Technology (FinTech) Association in the last quarter of 2017 on the effect of P2P lending on rural bank lending by analyzing the impact separately in 2018 and 2019. The publicly available data from the Financial Services Authority and Bank of Indonesia were examined using panel data regression. The results show that P2P lending’s growth is a substitute for the growth of the rural bank loan in 2018. However, the partnership between the Rural Bank Association and FinTech Association changed the effect of substitution into complementary in 2019. Moreover, the impact of P2P lending was more prominent in provinces with a higher number of rural banks and regions with lower economic growth. The restricted number of publicly available data becomes the limitation of this study to obtain the best results.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".