In today’s increasingly digitally-driven world, financial institutions are leveraging the power of social media and news trends monitoring to create comprehensive customer insights and increase their competitive edge. Social media offers an unprecedented opportunity for businesses to interact with customers, build relationships, and gain insights that can be used to improve their overall experience. Furthermore, companies can use news trends monitoring to identify industry changes and make well-informed decisions that can support their overall growth. One of the primary advantages of social media for the financial sector is the ability to build relationships with customers. With the use of social media, financial companies can collaborate with customers to gain a better understanding of their needs, preferences, and concerns. This enhanced communication and collaboration provides financial companies with the opportunity to craft personalized services and experiences that better meets customer needs. Social media also allows companies to effectively manage their online reputation, with timely responses and constructive dialogue. By understanding customer expectations, companies can provide better solutions and achieve a competitive edge in the industry. News trends monitoring also provides financial companies with key insights to stay up-to-date with industry changes and formulate business strategies that support their growth. Through news trend monitoring, financial companies can track any changes occurring in the sector, enabling them to take decisive actions and better adjust to the environment. By responding quickly to changing conditions, companies can remain competitive and anticipate opportunities in the market. Overall, social media and news trends monitoring offer numerous advantages to the financial sector. By embracing these tools, financial companies can gain customer insights, build customer relationships, and track industry changes.
The Problem
Professionals are looking for social media and news trends monitoring alternative data insights to gain a competitive advantage. Those data are hard to access, unstructured, not easy to monitor.
Analysts spend as much as 35% of time just processing data, while only 20% is spent on interpreting the analytical results.
Our Solution
Event-driven, serverless cloud-based analytical pipelines. Each function takes a request from an analytical engine as an input and then fetches and processes relevant data. In data engineering pipelines we used Apache technologies such as Airflow and Beam. For NLP tasks transformer-based model BERT has been used which is state-of-the-art for Named Entity Recognition tasks.
Outcome
Platform with active API for on demand/scheduled customer query - company, sector key-words. Ready to get actionable insights based on millions of articles, posts, comments from social media and news data, discover the undiscovered market anomalies and test hypotheses.
Key Takeaway
Analyst can spend up to 3x more time on interpreting social media and news trends.
Technology Keywords
Python, Apache, PostgreSQL, Cloud-based, NLP/BERT