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Opensee Platform Provides Self-Service Big Data Analytics for Business Users

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Paris-based ICA, a provider of big data analytics, has rebranded as Opensee, marking its evolution from an innovative capital markets data analytics platform to a market challenger. The company’s offer is to make hundreds of terabytes of structured data accessible to business users easily and quickly through self-service data analytics tools.

The company was initially established in 2015 as Independent Calculation Agent (ICA). It provided a solution designed to calculate prices and risk metrics for derivative instruments in less time and at lower cost than traditional solutions, but couldn’t find a commercial big data analytics solution able to underpin the solution and perform what-if analysis on huge volumes of data. Under the auspices of ICA founder Stéphane Rio, the company decided to build its own analytics platform.

Rio, now founder and CEO at Opensee, says: “Financial institutions have huge amounts of internal data, such as risk and market data. It is typically stored in data lakes like Hadoop. Over the past few years, firms have been trying to make better us of the data, but it has been difficult for business users to interact with the data and carry out analytics.”

ICA first built a vertical risk management system as a service for capital markets. It pivoted to Opensee when enterprise clients wanted to use their own data to solve broader business problems. Rio notes that many firms were using old technology such as in-memory OLAP, which does not scale well and can become unaffordable as data volumes rise. Traditional and cloud data warehouses are generic and not designed for specific use cases in financial markets, he adds, and BI acceleration platforms are data heavy, slow to access raw data, and do not adapt well to real-time data.

“We understand the technical environment of banks and the use cases they are trying to solve,” says Rio. “We believe there is a better way to help business users across financial institutions analyse very large amounts of available data deeper and faster, without killing the institution’s database.”

The Opensee platform democratises self-service analytics of all stored data. Use cases include risk management – users can explore all underlying data in real time and build user defined functions to manage risk more efficiently and proactively, as well as improve their response to regulations such as FRTB using targeted analytics. The platform can also be used to access all trade and order data to improve market intelligence and execution, or to analyse customer behaviour based on all related data.

In technical terms, the platform uses open source components, is written in Scala, and is based on ClickHouse, an open source big data analytical column oriented database to which the company has added functionality including tools to extract, aggregate, analyse and visualise data. It also includes generic APIs to integrate with bank information systems and ingest large volumes of data at high speed, as well as a low code API that allows users to write code in Python and interrogate data autonomously. The platform can be deployed on premise, in private or public clouds, or in a hybrid environment, with scaling supported by commodity hardware.

Rio says: “Users can go from high level data aggregation down to much greater detail based on underlying billions of data.”

While Opensee got started in capital markets with banks – the company says it is working with a few European Tier-1 banks, next stages include provision of the data aggregation and analytics platform for asset managers and trading platforms wanting to optimise their data.

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