Data & Replication

All data, scripts, and outputs are available in the project repository for full replication.

Repository

GitHub: Digital-AI-Finance/Systemic-Risk-Channels-in-Digital-Finance

Clone and run the scripts to reproduce all tables, rankings, and sensitivity analyses reported in the paper.

Key Data Files

File Description
output/data/channel_rankings.json Composite scores, sub-scores, and ranks for all 14 candidate channels (unscreened corpus)
output/data/channel_rankings_filtered.json Rankings recomputed after removing off-topic papers identified by relevance screening
output/data/sensitivity_analysis.json Four alternative weight schemes with per-channel composite scores and ranks
output/data/filtered_vs_unfiltered_comparison.json Side-by-side comparison of filtered and unfiltered rankings with rank changes
output/data/corpus_contamination_audit.json Audit of off-topic papers per channel: counts removed, reasons, and papers remaining
output/data/openalex_merged.json Merged OpenAlex corpus with all 2,433 papers, metadata, and channel assignments
output/data/per_paper_scoring_detail.json Per-paper scoring breakdown: relevance flags, citation counts, channel membership
output/data/key_papers.json Curated list of high-impact papers per channel used for narrative synthesis

Key Scripts

Script Purpose
scripts/channel_mapper.py Computes composite scores and rankings for all 14 channels from the unscreened corpus
scripts/channel_mapper_filtered.py Recomputes rankings after removing off-topic papers; produces filtered comparison
scripts/openalex_search.py Queries OpenAlex API with Boolean keyword expressions; retrieves and deduplicates papers
scripts/sensitivity_analysis.py Tests four weight schemes and reports rank stability across configurations
scripts/verify_all_papers.py Validates every paper in the corpus against OpenAlex metadata (DOI, title, year)
scripts/hostile_review.py Automated adversarial review: checks for citation errors, data inconsistencies, and methodology gaps
scripts/reference_audit.py Cross-references every in-text citation against the bibliography; flags orphans and phantoms

Paper Downloads

Full Paper
95 pages, 1.1 MB
Download PDF
Journal Version
~30 pages, 570 KB
Download PDF

Citation

Osterrieder, Jörg (2026). Systemic Risk Channels in Digital Finance: A Comprehensive Taxonomy. Working Paper. University of Twente.