Best credit classification and fraud prevention
The speed, variety and volume of data associated with the financial market has grown at an impressive rate. Activities such as social networking, mobile application transactions, server logs, market data in real-time, transaction data and metadata, investments, and so much more.
With a digitalization services trend, this is only the beginning. To benefit from this huge amount of information, large companies are investing in Big Data and hiring and preparing the so-called data scientist professionals. These professionals must be able to:
Sentiment analysis applies NLP techniques (Natural Language Processing), text analysis and computational linguistics to evaluate what customers think of your company.
Thanks to providing a wealth of information on the Internet, a new generation of financial companies (known as fintechs) are finding different ways to approve loans and risk management.
Until recently, financial institutions were affected by the delay time between data collection and data analysis. With real-time analytics, this issue is addressed. Moreover, it offers new ways of working.
Like any other industry on the planet, banks and financial institutions have the need to know more about the people who use their products and services. With Big Data you can use various tools to create a 360-degree view of your customers.
This type of customer segmentation allows them:
To help your business data leverage your business results, Semantix's team has several qualified experts to implement a complete solution for Big Data from the infrastructure state up to the data ingestion and analytics in real-time with complex algorithms, such as Machine Learning techniques.