This study aims to recognize customers’ real sentiment and then discover the data-driven insights for strategic decision-making in the financial sector of Saudi Arabia. The data was collected from the social media (Facebook and Twitter) from start till October 2018 in financial companies (NCB, Al Rajhi, and Bupa) selected in the Kingdom of Saudi Arabia according to criteria. Then, it was analyzed using a sentiment analysis, one of data mining techniques. All three companies have similar likes and followers as they serve customers as B2B and B2C companies. In addition, for Al Rajhi no negative sentiment was detected in English posts, while it can be seen that Internet penetration of both banks are higher than BUPA, rarely mentioned in few hours. This study helps to predict the overall popularity as well as the perception or real mood of people by identifying the positive and negative feelings or emotions behind customers’ social media posts or messages. This research presents meaningful insights in data-driven approaches using a specific data mining technique as a tool for corporate decision-making and forecasting. Understanding what the key issues are from customers’ perspective, it becomes possible to develop a better data-based global strategies to create a sustainable competitive advantage.

Abstract
1. Introduction
2. Literature Review
    2.1. Financial sector and Sustainable Growth inSaudi Arabia
    2.2. Predictive Data Mining with Social Media
3. Research Methods and Materials
4. Results and Discussion
5. Conclusions and Limitations
References

• Young-Eun PARK(Management Department, College of Business Administration, Prince Sultan University) Corresponding Author.
• Yasir JAVED(Computer Science Department, College of Computer & Information Sciences, Prince Sultan University)