A Data Driven Financial Industry
Why Financial Institutions need text analytics to drive marketing, human resources, and investment strategies.
The volume, variety, velocity, and veracity of unstructured data for firms in the financial industry can be tackled through text analytics and augmented intelligence. Machine learning with natural language processing enable banks, financial service firms, and fintech companies to measure customer and employee sentiment, customer profiles, and market sentiment from textual data. The insights gained from text analytics drive marketing, human resources, and investment decisions in the financial industry that affect profitability.
Learn More about how text analytics can help with:
- Market Sentiment Analytics
- Customer Profiling
- Customer & Employment Sentiment
Stratifyd, established in 2015, has quickly become a leader in data science and big data analytics. By enabling key business lines - including marketing, customer experience, HR, and research analytics - the Stratifyd platform excels in speed, accuracy, and usability.
"Sentiment Analytics is the study of customer opinions and attitudes. Sentiment is a score of the overall positive, neutral, or negative perception of a product, service, topic, or brand. Optimizing overall sentiment is a primary goal of every marketing campaign. The high volume of unstructured data that financial institutions and their customers generate on a daily basis can now be extracted, analyzed, and summarized conveniently to provide quality insights."
“The insights gained from text analytics drive marketing, human resources, and investment decisions in the financial industry that ultimately affect profitability.”