Text mining applications in financial market monitoring: lessons from the Central Bank of Nigeria
Conference
64th ISI World Statistics Congress - Ottawa, Canada
Format: IPS Abstract
Keywords: big data, financial-market, textmining
Abstract
In recent years, the Central Bank of Nigeria (CBN) has made significant progress in utilizing social media data to improve its functions and policies. It has developed a social media analytics dashboard that allows the CBN to monitor financial market conduct and address consumer complaints as they emerge. This paper discusses the social media analytics tool developed by the Central Bank of Nigeria for improving its consumer protection, risk management, and corporate communication functions. The tool utilized textual data collected from various social media platforms. These datasets were analyzed using appropriate text mining techniques to identify the inherent sentiments and themes in the social media posts.
To make the results accessible for prompt policy and regulatory interventions, the results are presented in a tool named the CBN “Social Media Analytics Dashboard – SMAD”. The SMAD tracks thirteen metrics useful for addressing customer complaints, detecting fraud, identifying emerging reputational risks, and designing policies. These metrics are being tracked by the relevant departments and incorporated in standard econometrics models for policy analysis and forecasting. The SMAD is interactive, dynamic, and equipped for daily, monthly, and annual analyses. It is hoped that the paper will help promote the adoption of big data and data analytics among central banks, especially in African countries.