Alternative Credit Scoring and Borrower Dignity

Sofia Bennett

Alternative Credit Scoring and Borrower Dignity

Author(s)	Dr. Sofia Bennett
Country	United States
Abstract	Alternative credit scoring has expanded the informational possibilities available to lenders by incorporating data beyond conventional credit histories, including cash-flow information, rent and utility payments, transaction behavior, psychometric indicators, and selected digital footprints. Such approaches can improve the assessment of thin-file or previously difficult-to-score applicants, yet broader data availability also creates significant questions concerning privacy, relevance, discrimination, explainability, and the borrower's ability to challenge consequential decisions. This study examines alternative credit scoring through the concept of borrower dignity, defined as a condition in which applicants can seek credit without unnecessary informational extraction, arbitrary profiling, unexplained adverse treatment, or loss of meaningful procedural agency. Because no verified borrower-level dataset was supplied, a transparent simulation-based design involving 160 synthetic credit-assessment cases was developed. Five dimensions were incorporated: Access Gain, Data Minimization, Explanation and Appeal, Human Review, and Governance Maturity. The cases were categorized into four governance stages: Extractive, Access-Led, Rights-Aware, and Dignity-Centered. The simulated analysis produced a Pearson correlation of r = 0.835 between governance maturity and borrower dignity. Mean Borrower Dignity increased from 47.9 under Extractive scoring to 57.5 under Access-Led scoring, 66.5 under Rights-Aware governance, and 77.0 under Dignity-Centered arrangements. The findings illustrate that broader credit access alone is insufficient to establish responsible inclusion. Alternative scoring becomes more dignity preserving when predictive expansion is accompanied by proportionate data use, meaningful reasons for consequential decisions, accessible correction and appeal procedures, and accountable human oversight. The study proposes that high-quality alternative credit scoring should be evaluated through a dual standard of predictive inclusion and procedural dignity. The paper contributes a borrower-centered governance framework suitable for subsequent empirical validation in fintech, consumer credit, microfinance, and small-enterprise lending contexts.
Keywords	alternative credit scoring; borrower dignity; alternative data; financial inclusion; algorithmic lending; credit fairness; explainability; data minimization; fintech lending; borrower rights
Field	Engineering
Published In	Volume 6, Issue 3, May-June 2025
Published On	2025-05-21

View / Download PDF File

About AJAMIR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+1-872-302-3851	editor@ajamir.com

American Journal of Advanced Multidisciplinary Innovation and Research

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Alternative Credit Scoring and Borrower Dignity

Share this