AI Data Science Accelerators for Financial
Services, Banking and Insurance (BFSI) Sectors.

Following the success of Symbiosis’s AI Accelerators focused on Automation, Symbiosis’s Data Science experts have developed a powerful set of Accelerators that allow Financial Services, Banking and Insurance (BFSI) firms to understand causation, visualize investment research, create more informed investment strategies, better manage customer complaints, and predict credit risk related to mortgages. Symbiosis’s Data Science Accelerators offer financial services and insurance firms powerful platforms for advanced statistical analysis of structured and unstructured data. By leveraging Symbiosis’s unique combination of expertise in business consulting, technology, and digital experience, its Data Science Accelerators have been developed with an expert knowledge of Data Science and Machine Learning techniques, as well as the context behind the data in order to build domain specific applications. The program includes powerful data causation and correlation platform and applications for automated research generation (both buy-side and sell-side) and investment management recommendations.

AI Data Science Accelerators

Symbiosis applies its Digital, Business Consulting and Technology expertise to deliver Data Science solutions that solve real-world problems. Our Accelerators focus on four business problems and apply AI to address them:

Visual Research
/ Visual Research

Comprehensive solutions for sell-side and buy-side research analysts

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Informed Investing
/ Informed Investing

Enabling pro-active and informed investing decisions

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Credit Risk
/ Credit Risk

Proactively manage credit portfolios

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Customer Complaints Management
/ Customer Complaints Management

Fully automated and proactive customer complaints management

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6 Industry Solutions using Blockchain

Symbiosis’s AI Data Science Accelerators are based on the following cutting-edge platforms:

Syn-AI for Signal Discovery
/ Syn-AI for Signal Discovery

Discovering meaningful relationships

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Granger Causality
/ Granger Causality

Retrieve, transform and analyze historical data sets in real-time

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