Zero-Revelation RegTech: Detecting Risk through Linguistic Analysis of Corporate Emails and News

33 Pages Posted: 2 Feb 2017  

Sanjiv Ranjan Das

Santa Clara University - Leavey School of Business

Seoyoung Kim

Santa Clara University

Bhushan Kothari

Google Inc.

Date Written: April 27, 2017

Abstract

In this paper, we demonstrate how an applied linguistics platform may be used to parse corporate email content and news to assess factors predicting escalating risk or the gradual shifting of other critical characteristics within the firm before they are eventually manifested in observable data and financial outcomes. We find that email content and news articles meaningfully predict increased risk and potential malaise. We also find that other structural characteristics, such as the average email length, are strong predictors of risk and subsequent performance. We present implementations of three spatial analyses of internal corporate communication, i.e., email networks, vocabulary trends, and topic analysis. Overall, we propose a RegTech solution by which to systematically and effectively detect escalating risk or potential malaise without the need to manually read individual employee emails.

Keywords: Fintech, RegTech, Corporate governance, Text mining, Email analysis, Email networks, Mood and net sentiment

JEL Classification: G00, G01, G28, G38

Suggested Citation

Das, Sanjiv Ranjan and Kim, Seoyoung and Kothari, Bhushan, Zero-Revelation RegTech: Detecting Risk through Linguistic Analysis of Corporate Emails and News (April 27, 2017). Available at SSRN: https://ssrn.com/abstract=2960350

Sanjiv Ranjan Das

Santa Clara University - Leavey School of Business ( email )

Department of Finance
316M Lucas Hall
Santa Clara, CA 95053
United States

HOME PAGE: http://algo.scu.edu/~sanjivdas/

Seoyoung Kim (Contact Author)

Santa Clara University ( email )

500 El Camino Real
Santa Clara, CA California 95053
United States

Bhushan Kothari

Google Inc. ( email )

Paper statistics

Downloads
45
Abstract Views
108