Sentiment analysis is an excellent way to better understand financial markets, gain more accurate insights, and prepare for changes. It is conducted using artificial intelligence and natural language processing systems to extract insights from textual data sources. Do you want to learn more? Then keep reading!
Table of Contents
What Is Sentiment Analysis?
Before we discuss sentiment analysis in the financial sector, let’s define this approach. It is the act of gathering information from unstructured, textual sources using AI and NLP. Thanks to sentiment analysis software, you can analyze, for instance:
- social media feeds,
- news articles,
- customer reviews.
As a result, you can uncover customer sentiment, their opinions on certain topics, and product types or services. This enables you to prepare your offer better and proactively seek solutions to customer problems, helping you acquire and retain customers.
Do you need a sentiment analysis system for your organization? See our generative AI services for finance!
The Three Types of Sentiment Analysis
In general, we can distinguish between three types of sentiment analysis: opinion, emotion, and intent. Let’s look at them more closely.
- Opinion sentiment analysis—This particular type revolves around the opinions expressed in text data. It may include segmenting them into positive, negative, and neutral ones, as well as finding bottlenecks and areas for improvement in your financial services.
- Emotion sentiment analysis—In this case, you analyze textual data to find the emotions expressed by the users. Understanding the reactions of consumers to your marketing materials will be especially useful for increasing sales.
- Intent sentiment analysis—The last type of sentiment analysis focuses on understanding the intent behind expressed sentiments, such as purchases, customer service inquiries, or even churning. It will mostly be helpful for your customer service team.
How Can You Use Sentiment Analysis in Financial Markets?
Sentiment analysis is a powerful tool for organizations operating in financial markets—it offers new insights that you would not access otherwise. How can you use it to your advantage? Here are a few examples.
Selecting the Right Assets in Wealth Management
Predictive analytics in finance are always important, but they gain extra value when it comes to wealth management. With sentiment analysis, you can, for instance, research public opinion about a given company that your client wants to invest in. Based on that, you can calculate the risk and evaluate whether the investment matches your client’s criteria.
Developing New Services
Another way you can use sentiment analysis to gain an advantage in financial markets is to add new services to your portfolio. Analyzing reviews and opinions will help you identify your clients’ pain points and come up with solutions to them in the form of innovative banking services.
Build software solutions for your new services quickly with our digital process automation services!
Predicting Market Shifts
Finally, you can use sentiment analysis to quickly analyze the potential changes to the market in the form of taxes and legal regulations. What matters here is that you gain access to information on public opinions about proposed changes, which makes it easier for you to define which ones will come into force and which ones will be abandoned. This will help you protect your business from market shifts and outperform your competitors.
The Takeaway
Sentiment analysis is an approach that will help you make better-informed decisions in financial markets. Therefore, we recommend implementing it in your organization – it will give you a real advantage!
You may also read: Customer data platform as an answer for new data-driven challenges?
