How It Works

This demo runs the exact same screening logic used in the national 1328(f) analysis. It operates on a small anonymized sample dataset (70 cases, 30 debtors) embedded in this page. Click "Run Screening" to execute the algorithm in your browser.

Statutory Framework

11 U.S.C. 1328(f): (f)(1): No discharge if debtor received a discharge in a case filed under chapter 7, 11, or 12 within 4 YEARS before the current Ch.13 filing. (f)(2): No discharge if debtor received a discharge in a case filed under chapter 13 within 2 YEARS before the current Ch.13 filing. Key: The window runs from PRIOR FILING DATE to CURRENT FILING DATE. The prior case must have resulted in a discharge. See In re Blendheim, 803 F.3d 477 (9th Cir. 2015).

Algorithm Steps

Group cases by debtor name (normalized: lowercase, suffix-stripped)
For each debtor with 2+ cases, find discharged cases and Ch.13 filings
For each Ch.13 filing dated after Oct 17, 2005 (BAPCPA effective):
Check each prior discharged case's filing date
If prior was Ch.7/11/12 and gap <= 4 years: flag as (f)(1) violation
If prior was Ch.13 and gap <= 2 years: flag as (f)(2) violation
Deduplicate hits by (prior_case, current_case, section)

Results Summary

Cases Loaded

Unique Debtors

Repeat Filers

(f)(1) Violations

(f)(2) Violations

Detailed Results

Violations Found

Safe Cases

All Cases

Debtor	Prior Ch.	Prior Filed	Ch.13 Filed	Gap (days)	Window	Section

Debtor	Prior Ch.	Prior Filed	Ch.13 Filed	Gap (days)	Window	Status

Case ID	Debtor	Chapter	Filed	Discharged	Dismissed

Methodology Notes

Name matching: Debtor names are normalized (lowercased, suffixes like Jr./Sr./III stripped, "NMN" removed). Joint cases ("A and B") produce two name keys each.
Date gap: Measured from prior case filing date to current Ch.13 filing date. NOT from discharge date. This follows the majority interpretation per In re Blendheim.
BAPCPA filter: Only Ch.13 cases filed on or after October 17, 2005 are screened. 1328(f) did not exist before BAPCPA.
43% bar rate: In the national FJC analysis, we estimate that 43% of prior-filer discharges involve gaps within the statutory window. This demo checks exact gaps, so it finds the precise violations in the sample.
No false positives from name collisions: This sample uses unique debtor labels (Debtor_001, etc.) to eliminate name collision risk. In real data, fuzzy name matching introduces a small false positive rate (~2-3%) which is addressed by manual verification on flagged cases.