How it works
Source and normalize the data from your different algos
Push the algorithms data (orders, trades, market data, static data) to our api.
Apply Expert Rules & Artificial Intelligence
Leverage Machine Learning algorithms to extract insights for your data-driven strategy
Get the right report for your committee
Build reports to identify potential market manipulation patterns (spoofing, ping orders, marking the close…) while organizing the backlog of the monitoring team at the same time.
What you get
Identify all the critical risks for your algo trading in real-time
The board needs to be fully engaged to understand the critical risks facing the algo trading. Detect highs risks that threaten the trading strategies.
Apply the Model Risk Management procedures to Algo Trading
Articulate an enterprise-level e-trading governance framework to oversight the risk management including control execution, monitoring / testing and reporting.
Make the risk management the priority of your algo trading risk committees
Every decision regarding release or change of parameters that can impact a market needs to be on the risk dashboard. Discover manipulative activity before enforcement investigation.
Connect the algo trading data
Normalize the data from multiple algos from different teams to expose the data to your risk committee in a readable format with data visualization
Enrich your committees with insights on data
Drill down the information to have a clear view on your risk with algo trading. These risks include day-to-day operations and the validation of implementation of algo trading.
Understand better and detect anomalies
Oversee risk management to visualize unexpected outliers in the execution of the algorithms to quickly analyze if a corrective action is necessary.
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