Emotion Recognition Technology in the Financial Sector

Forecast financial trends and movements through emotion recognition technology? This possibility definitely proposes leaving behind the statistics and financial projections made for years at a global level, but it goes further than just creating an algorithm designed to recognize emotions to generate the desired economic gains.

Ensuring economic recovery is everyone's concern, since it translates into the reduction of social gaps, in the generation of better economic and government policies that benefit more than only a few, as well as promotes the development of the financial and economic market.

In this sense, it is necessary to affirm that all the required tools to guarantee a healthy financial environment are valid, especially when dealing with technological platforms that every day demonstrate their sophistication and high sense of response to daily challenges.

In the software development industry, the issue of detection and recognition of emotions in the financial sector is somewhat delicate, since it is about taking technological resources further to predict and dictate conjunctural scenarios to promote economic growth, and at the same time ponder user privacy.

Origin and application to the financial sector

Before bringing emotions to the financial sector, it is necessary to point out that this technology was born as a non-profit tool, focused on stimulating social empathy and better emotional understanding, thus promoting a better relationship environment between people.

Using Artificial Intelligence as its main ally, emotion recognition technology is based on the analysis of facial expressions and tone of voice to predict the emotional condition of users. Using audiovisual resources, emotion recognition technology is carried out through an algorithm that is capable of distinguishing between the most popular emotions such as happiness, anger, fear or disgust, since it is believed that they are the ones that people share the most universally regardless of their gender or origin.

But, how to use the recognition of these emotions in the financial sector and how can it benefit society?

It is a very well known secret that finances are considered one of the most complex issues that people and organizations of all kinds have to deal with. Decision-making is even more complex when it comes to economic scenarios, and beyond statistics and projections, it has been shown that emotions play a fundamental role in this process.

A few years ago, the first software developments dedicated to the emotion recognition technology began through telephone calls from customers requesting attention, so it was easier to channel them according to the degree of alteration and emotions identified by the agent.

Later on, this same emotion recognition technology was used to accurately detect fraud, so it continued to advance until it reached the development of algorithms, which represents great advances but also great challenges.

Technology reaches where the user wants

As expected, and especially when it comes to the financial field, this technology contrasts in terms of its accuracy and the veracity of the data it provides, especially since the knowledge of the existence of these programs, users find every time more cunning ways to deceive these tools, which compromises its usefulness and operation.

On the other hand, one of the most controversial issues surrounding emotion recognition technology is the user's right to privacy, which in this case is not only about their financial information, but also about their person and integrity as an individual.

The more it advances, the more emotion recognition technology is required to report on the use of collected images or videos, as well as request user consent.

Since the algorithm used by this technology applied to the financial sector is based on artificial intelligence such as the K-means clustering algorithm and the SVM recognition algorithm, they have the ability to generate increasingly accurate data.

Solving doubts on its own

Being the financial sector one of the most unpredictable and full of uncertainty, technology has been pushed further to implement statistical methods that contribute to the demystification of emotions once the information is received.

This technology responds to these demands through controlled and real-time optimizations, which must consider all the aspects that the financial market implies to reach a reliable prediction point, so these systems must guarantee a complete and consistent vision with current financial trends.

Like all reliable technology that is based on Artificial Intelligence, learning from the data collected is something that cannot be left out of the optimizations to seek improvement in the production processes and processing of hard data.

However, there is still a long way to go to use emotion recognition algorithms to foster economic growth and development, but there is no doubt that the operational advantages it offers at the moment are vast and viable if what is sought is an analysis to carry out a financial forecast in the short and medium term.

This emotion recognition technology can be translated as a significant advance in the digital transformation of the financial sector, and at Icalia Labs we are eager to continue developing this and new technologies that contribute to new strategies to achieve financial stability for our clients and the society.

Through the creation of dedicated software for the financial sector and sheltered under agile methodologies, we are committed to creating new opportunities for our clients with solutions that range from the management of users' financial operations to portfolio management tools for accurate data analysis and achieve viable forecasts.

There is no better time than now, and we want to help you use this technology to your benefit to make the most of the capabilities of your staff. Enter here and consult our trajectory in this area, some of our success stories and get ready to take your company beyond the conventional.

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