Papers Credit score
“Credit score” 태그가 달린 논문 20편 · 필터 해제
SocialCredit+
SocialCredit+ is AI powered credit scoring system that leverages publicly available social media data to augment traditional credit evaluation. It uses a conversational banking assistant to gather user consent and fetch …
Credit scoreEthicsRetrieval-augmented GenerationMulti-Agent Performative Prediction Beyond the Insensitivity Assumption: A Case Study for Mortgage Competition
Performative prediction models account for feedback loops in decision-making processes where predictions influence future data distributions. While existing work largely assumes insensitivity of data distributions to sma…
Credit scoreEnhanced Credit Score Prediction Using Ensemble Deep Learning Model
In contemporary economic society, credit scores are crucial for every participant. A robust credit evaluation system is essential for the profitability of core businesses such as credit cards, loans, and investments for …
Credit scoreDeep LearningCredit Scores: Performance and Equity
Credit scores are critical for allocating consumer debt in the United States, yet little evidence is available on their performance. We benchmark a widely used credit score against a machine learning model of consumer de…
Credit scoreCredit and Voting
There is a tight connection between credit access and voting. We show that uncertainty in access to credit pushes voters toward more conservative candidates in US elections. Using a 1% sample of the US population with va…
Credit scorevalidRacial and Ethnic Disparities in Mortgage Lending: New Evidence from Expanded HMDA Data
This paper investigates gaps in access to and the cost of housing credit by race and ethnicity using the near universe of U.S. mortgage applications. Our data contain borrower creditworthiness variables that have histori…
Credit scorePeeking Inside the Schufa Blackbox: Explaining the German Housing Scoring System
Explainable Artificial Intelligence is a concept aimed at making complex algorithms transparent to users through a uniform solution. Researchers have highlighted the importance of integrating domain specific contexts to …
Credit scoreExplainable artificial intelligenceLife after (Soft) Default
Soft default, defined as a delinquency of 90 days or more, is a relatively common event in the credit market, in 2010 such episodes affected about 3 million individuals. Yet we lack a detailed understanding of what happe…
Credit scoreKnow, Grow, and Protect Net Worth: Using ML for Asset Protection by Preventing Overdraft Fees
When a customer overdraws their bank account and their balance is negative they are assessed an overdraft fee. Americans pay approximately \$15 billion in unnecessary overdraft fees a year, often in \$35 increments; user…
Credit scoreA Machine Learning system to monitor student progress in educational institutes
In order to track and comprehend the academic achievement of students, both private and public educational institutions devote a significant amount of resources and labour. One of the difficult issues that institutes dea…
Credit scoreManagementSocial Bias Meets Data Bias: The Impacts of Labeling and Measurement Errors on Fairness Criteria
Although many fairness criteria have been proposed to ensure that machine learning algorithms do not exhibit or amplify our existing social biases, these algorithms are trained on datasets that can themselves be statisti…
Credit scoreFairnessInstant Loans Can Lift Subjective Well-Being: A Randomized Evaluation of Digital Credit in Nigeria
Digital loans have exploded in popularity across low and middle income countries, providing short term, high interest credit via mobile phones. This paper reports the results of a randomized evaluation of a digital loan …
Credit scoreUnintended Selection: Persistent Qualification Rate Disparities and Interventions
Realistically -- and equitably -- modeling the dynamics of group-level disparities in machine learning remains an open problem. In particular, we desire models that do not suppose inherent differences between artificial …
Binary ClassificationCredit scoreFairnessMachine Learning-Based Empirical Investigation for Credit Scoring in Vietnam’s Banking
In thons for credit scoring in Vietnam with machine learning models based on our submissions for the Kalapa Credit Score Challenge. We conduct experiments with modern machine learning methods based on ensemble learning m…
BIG-bench Machine LearningCredit scoreEnsemble LearningregressionLabor Informality and Credit Market Accessibility
The paper investigates the effects of the credit market development on the labor mobility between the informal and formal labor sectors. In the case of Russia, due to the absence of a credit score system, a formal lender…
Credit scoreApplications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics
In [1], we have explored the theoretical aspects of feature selection and evolutionary algorithms. In this chapter, we focus on optimization algorithms for enhancing data analytic process, i.e., we propose to explore app…
Computational EfficiencyCredit scoreDimensionality ReductionEvolutionary Algorithms+2R\'eint\'egration des refus\'es en Credit Scoring
The granting process of all credit institutions rejects applicants who seem risky regarding the repayment of their debt. A credit score is calculated and associated with a cut-off value beneath which an applicant is reje…
Credit scorees-enA Scoring Method for Driving Safety Credit Using Trajectory Data
Urban traffic systems worldwide are suffering from severe traffic safety problems. Traffic safety is affected by many complex factors, and heavily related to all drivers' behaviors involved in traffic system. Drivers wit…
Credit scoreGeneral ClassificationActionable Recourse in Linear Classification
Machine learning models are increasingly used to automate decisions that affect humans - deciding who should receive a loan, a job interview, or a social service. In such applications, a person should have the ability to…
ClassificationCredit scoreDecision MakingGeneral ClassificationMachine learning application in online lending risk prediction
Online leading has disrupted the traditional consumer banking sector with more effective loan processing. Risk prediction and monitoring is critical for the success of the business model. Traditional credit score models …
BIG-bench Machine LearningCredit scorePrediction