Credit-Risk-Scorecard
Explainable credit scorecard (WoE and logistic regression) on 307,511 Home Credit applicants: AUC 0.754 on holdout; 47% fewer credit losses at 80% approval
What XERJ indexed
Snapshot
The whole repository at commit bac2dde102 (2026-10-17). main is 42 commits ahead.
Selected work
“Rebuild the live case-study page from the executed outputs”. 3 files, 306 lines in demo, the project root.
Licence
The repository
LICENSE file checked at the pinned commit; the author agreed to inclusion.
The XERJ corpus
The author agreed by email on 2026-10-28. Same terms as the repository. Answers name the repo, the commit and the file:line.
selected for the XERJ Corpus Hublicence clearedsuggested use: adapt with attribution
credit-riskcredit-scorecardhome-creditjupyter-notebooklogistic-regressionpythonweight-of-evidencefintech
Example questions
- How does Credit-Risk-Scorecard implement credit-risk?
- Where does Credit-Risk-Scorecard handle “Rebuild the live case-study page from the executed outputs”?
- What does demo do in Credit-Risk-Scorecard?
Inside the indexed corpus
- 78 files, 4.6 MB in total, about 60.7 KB per file.
- The selected commit changed 3 of those files (3.8%).
- Languages by size: Jupyter Notebook 86.7%, Python 13.3%.
- On GitHub since 2026-07-17, last push 2026-10-29, 79 commits on main.
- The pin is 42 commits behind main; the corpus answers from the pinned code, not the newest.
Licence on GitHub and in the corpus
GitHub reported MIT for alvenyuka/Credit-Risk-Scorecard on 2026-10-29, and the LICENSE file at commit bac2dde102 was reviewed as MIT. They match, so answers from this corpus carry the same terms as the live repository.
Contributors
Alven Yuka (@alvenyuka) has 1 selected repository on the hub.
Using XERJ with Credit-Risk-Scorecard
- Search Jupyter notebooks (.ipynb) and the .py beside them Jupyter Notebook is 86.7% of the code by size.
- Search an OpenAPI spec so an agent can find endpoints The hub files it under API design and specification.
- ripgrep vs a code index for coding agents: 30 tasks
- Best MCP servers for local code search in 2026, compared
The prompt
Paste it into your AI agent. It clones alvenyuka/Credit-Risk-Scorecard at the pinned commit and indexes it on your machine.
Search the GitHub repository alvenyuka/Credit-Risk-Scorecard with XERJ (https://hub.xerj.org/corpus/alvenyuka--credit-risk-scorecard). Run these in a shell, in order, and check each result before the next: 1. xerj --help (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh 2. git clone https://github.com/alvenyuka/Credit-Risk-Scorecard Credit-Risk-Scorecard && git -C Credit-Risk-Scorecard checkout bac2dde102160f532c4728dafdbd8a7c47142cc0 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./Credit-Risk-Scorecard --url http://127.0.0.1:9200 --prefix credit-risk-scorecard --progress plain 5. xerj autoindex map --url http://127.0.0.1:9200 Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt Licence: MIT. Keep the copyright notice and credit the authors.
Related
Alven YukaAPI design and specification corporajsonformeranthropic-cookbookguidanceorgoca/CompileMLFahadBinHussain/cse220FahadBinHussain/cse330
Stats: GitHub API, fetched 2026-10-29. Snapshot: the git tree at the pinned commit. Selected work and consent: the XERJ registry.