Say It Right: IS Prototype to Enable Evidence-Based Communication Using Big Data

Abstract

Financial investors face an increasing information abundance when making their valuation decisions of financial assets. As Information Systems research demonstrated, valuation not only builds on quantitative facts, but also on qualitative information such as the language used in financial disclosures and the readability of the texts. As an originator of financial disclosures, e.g. a company, it is thus essential to thoughtfully steer the creation of new textual information. While regulators provide guidelines on what content to publish, corporate communication departments can flexibly steer how they communicate. We have developed an IS prototype that accounts for the importance of textual information and provides corporate communications with a decision-support tool to assure a high readability and a positive sentiment. Our IS prototype builds on a two-step process. First, we extract a dictionary with the most relevant words for investors from a large inventory of regulatory filings with Bayesian learning algorithms. Second, we use this dictionary as input for a Microsoft Word add-in that highlights positively or negatively connoted words and suggests alternative words with a more positive investor perception to corporate communications professionals.