THE TRANSFORMATION OF THE MORTGAGE BROKER'S ROLE AMID THE DIGITALIZATION OF FINANCIAL SERVICES
Bibliographic record
Abstract
The article presents an analysis of the transformation of the mortgage broker’s role in the context of the digitalization of financial services. The study is based on an interdisciplinary approach, combining insights from financial economics, digital business, banking innovations, and behavioral research. Particular attention is paid to the thematic analysis of scholarly publications covering competitive changes in the lending market, the institutional functions of brokers, and the adoption of FinTech platforms. Key mechanisms of influence are identified, including the reduction of interest rates in broker channels, the extension of amortization periods, the expansion of access for borrowers with less stable profiles, and the intensification of competition among lenders due to digital platforms. A comparative analysis shows that traditional brokers continue to affect loan parameters and risk structures, while digital intermediaries assume the functions of information aggregation and reduction of asymmetry in the interests of clients. The need is substantiated for a rethinking of business models and regulatory practices that account for the transition of brokers from the role of “navigators” to that of “digital mediators.” Promising avenues for future research are presented, including the assessment of platform competition’s impact on the sustainability of the mortgage market, borrower behavioral characteristics, and the effectiveness of supervisory measures in the digital ecosystem. The article will be useful to researchers in financial economics, specialists in digital transformation, regulators, and mortgage market practitioners interested in understanding institutional shifts and developing new intermediation strategies.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".