# Enhanced Credit Score Prediction Using Ensemble Deep Learning Model

arXiv: https://arxiv.org/abs/2410.00256 · HTML: https://mlsanity.com/paper/2410.00256/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 46 of its 71 references that are in the map.
- First posted on arXiv 30 Sep 2024.

## Builds on (most cited first, 30 of 46)

- [XGBoost: A Scalable Tree Boosting System](https://mlsanity.com/paper/1603.02754/) (2016)
- [TabNet: Attentive Interpretable Tabular Learning](https://mlsanity.com/paper/1908.07442/) (2019)
- [Deception Detection from Linguistic and Physiological Data Streams Using Bimodal Convolutional Neural Networks](https://mlsanity.com/paper/2311.10944/) (2023)
- [Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate](https://mlsanity.com/paper/2402.02769/) (2024)
- [Contextual Hourglass Network for Semantic Segmentation of High Resolution Aerial Imagery](https://mlsanity.com/paper/1810.12813/) (2018)
- [Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformers](https://mlsanity.com/paper/2406.12199/) (2024)
- [APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking](https://mlsanity.com/paper/2406.14449/) (2024)
- [The FacT: Taming Latent Factor Models for Explainability with Factorization Trees](https://mlsanity.com/paper/1906.02037/) (2019)
- [Harnessing XGBoost for Robust Biomarker Selection of Obsessive-Compulsive Disorder (OCD) from Adolescent Brain Cognitive Development (ABCD) data](https://mlsanity.com/paper/2407.00028/) (2024)
- [CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables](https://mlsanity.com/paper/2403.01673/) (2024)
- [CU-Net: a U-Net architecture for efficient brain-tumor segmentation on BraTS 2019 dataset](https://mlsanity.com/paper/2406.13113/) (2024)
- [Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach](https://mlsanity.com/paper/2408.06634/) (2024)
- [Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective](https://mlsanity.com/paper/2312.01397/) (2023)
- [In-context Time Series Predictor](https://mlsanity.com/paper/2405.14982/) (2024)
- [Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation](https://mlsanity.com/paper/2206.01369/) (2022)
- [Towards Resilient and Efficient LLMs: A Comparative Study of Efficiency, Performance, and Adversarial Robustness](https://mlsanity.com/paper/2408.04585/) (2024)
- [A Comparative Study on Enhancing Prediction in Social Network Advertisement through Data Augmentation](https://mlsanity.com/paper/2404.13812/) (2024)
- [Real-Time Pill Identification for the Visually Impaired Using Deep Learning](https://mlsanity.com/paper/2405.05983/) (2024)
- [Research on Autonomous Driving Decision-making Strategies based Deep Reinforcement Learning](https://mlsanity.com/paper/2408.03084/) (2024)
- [Evaluating Modern Approaches in 3D Scene Reconstruction: NeRF vs Gaussian-Based Methods](https://mlsanity.com/paper/2408.04268/) (2024)
- [Predicting Stock Prices with FinBERT-LSTM: Integrating News Sentiment Analysis](https://mlsanity.com/paper/2407.16150/) (2024)
- [Attention Mechanism and Context Modeling System for Text Mining Machine Translation](https://mlsanity.com/paper/2408.04216/) (2024)
- [Twitter Sentiment Analysis of Covid Vacciness](https://mlsanity.com/paper/2311.04479/) (2023)
- [DeepGI: An Automated Approach for Gastrointestinal Tract Segmentation in MRI Scans](https://mlsanity.com/paper/2401.15354/) (2024)
- [Development and Application of a Monte Carlo Tree Search Algorithm for Simulating Da Vinci Code Game Strategies](https://mlsanity.com/paper/2403.10720/) (2024)
- [Utilizing the LightGBM Algorithm for Operator User Credit Assessment Research](https://mlsanity.com/paper/2403.14483/) (2024)
- [Application of Multimodal Fusion Deep Learning Model in Disease Recognition](https://mlsanity.com/paper/2406.18546/) (2024)
- [Research on Driver Facial Fatigue Detection Based on Yolov8 Model](https://mlsanity.com/paper/2406.18575/) (2024)
- [Optimizing Distributed Networking with Big Data Scheduling and Cloud Computing](https://mlsanity.com/paper/2311.04482/) (2023)
- [Predict Click-Through Rates with Deep Interest Network Model in E-commerce Advertising](https://mlsanity.com/paper/2406.10239/) (2024)

## Built on by (most cited first, 2 of 2)

- [LProtector: An LLM-driven Vulnerability Detection System](https://mlsanity.com/paper/2411.06493/) (2024)
- [CIB-SE-YOLOv8: Optimized YOLOv8 for Real-Time Safety Equipment Detection on Construction Sites](https://mlsanity.com/paper/2410.20699/) (2024)

## Abstract (arXiv)

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 commercial banks and the financial sector. This paper combines high-performance models like XGBoost and LightGBM, already widely used in modern banking systems, with the powerful TabNet model. We have developed a potent model capable of accurately determining credit score levels by integrating Random Forest, XGBoost, and TabNet, and through the stacking technique in ensemble modeling. This approach surpasses the limitations of single models and significantly advances the precise credit score prediction. In the following sections, we will explain the techniques we used and thoroughly validate our approach by comprehensively comparing a series of metrics such as Precision, Recall, F1, and AUC. By integrating Random Forest, XGBoost, and with the TabNet deep learning architecture, these models complement each other, demonstrating exceptionally strong overall performance.