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incryptr .
Decorative
Artificial Intelligence Platform

BFSI

Machine learning algorithms build models based on sample data to

make predictions or decisions without being explicitly programmed.

Clients

The customer is an US based FinTech firm, dedicated to providing a stock trading platform as a virtual assistant. It handles approximately 300K clients. The company was keen on adopting Machine Learning in their trading style, allowing the customer to feel that they are interacting with a trading expert or a broker, who showcases recommendations on which stocks to invest in. They have a commission based revenue model, that is whenever a customer gains a profit, they take a small commission out of the transactions.

Machine Learning Illustration
Robotic Process Automation

Problem statement

The trading platform followed a process that involved severe amounts manual trading, making the process as a whole, very complex for the customers. Due to the dynamic nature of the stock market, the firm wanted an easier method of predicting/suggesting stocks for/to their customers.

Mitigating the problem

A hybrid AI solution was proposed which solved the problem

  • Talking to an AI bot which was trained specifically for stock-market trading purposes made their communication easy.
  • Automating the task of verifications and trading operators.
  • Reinforcement Learning and Time Series analysis was implemented on live streaming stock ticker data.
  • Recommendation system was setup which would analyse the behaviour of user in trading and would recommend to go for specific stock based on analysis.
Data Mining Cleaning and Labelling
Big Data Analytics

Solution delivered

  • The bot integration gave customers a feeling that they were interacting with industry experts. This solved the problem of the users and it increased the number of users by 32% in past 2 quarters.
  • The stock market predictions and recommendation system showcased accuracy which pulled the market by 13% in past 2 quarters.
  • The ROI increased by 18% as automating the entire process let to quick decisions.