The Modern Market of Neo Banks and their Role of Fintech Companies’ Financing
Bibliographic record
Abstract
This study analyzes the modern market of neo banks in different countries in order to determine their role in financing fintech companies. It is believed that the modern neo bank market requires a correction of strategic development, namely the growth of financing transactions (including lending to fintech companies from small and medium-sized businesses), which contribute to the turnover of intellectual and digital financial assets as collateral. The purpose of the study is to substantiate the feasibility of financing secured by intellectual and digital financial assets of Russian and Moscow fintech companies. Based on the analysis of the neo bank market in the world market and in the Russian Federation, the authors developed recommendations for improving the financing mechanism, including lending, secured by intellectual and digital financial assets, taking into account possible regional (Moscow) support. Theoretical analysis of scientific methods involving analysis, synthesis, and generalization of existing literature are utilized to meet the aim of the study. The article presents recommendations for improving the existing system of fintech companies’ financing based on the developed tools and mechanisms for attracting financial resources using intellectual and digital financial assets (DFA) to enhance the activities of fintech companies in Russia in general and the city of Moscow in particular.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".