금융 데이터 및 텍스트 데이터를 활용한 금융 기업 조기 경보 모형 개발 : 부실은행 예측을 중심으로

Development of Early Warning Model for Financial Firms Using Financial and Text Data : A Case Study on Insolvent Bank Prediction
  • 송서하
  • 김준홍
  • 김형석
  • 박재선
  • 강필성

초록

The early warning model, one of the risk management models for financial companies, was introduced to detect inadvance the capital adequacy crisis of financial institutions. The existing early warning models have mainly usedpredictive models with structured data-based variables such as various macroeconomic indicators and enterpriseinternal indicators. The purpose of this study is to further improve the performance of the early warning models byapplying customer complaints data and news articles related to individual financial institutions to machinelearning-based model. As a result of applying this technique to actual data over the period of 2001 to 2017, themethodology proposed in this study has demonstrated a performance improvement up to 20%p compared to theexisting methodology in certain evaluation metrics.

키워드

Early Warning ModelUnstructured Text DataText MiningMachine Learning
제목
금융 데이터 및 텍스트 데이터를 활용한 금융 기업 조기 경보 모형 개발 : 부실은행 예측을 중심으로
제목 (타언어)
Development of Early Warning Model for Financial Firms Using Financial and Text Data : A Case Study on Insolvent Bank Prediction
저자
송서하김준홍김형석박재선강필성
DOI
10.7232/JKIIE.2019.45.3.248
발행일
2019
저널명
대한산업공학회지
45
3
페이지
248 ~ 259