“R” Integrated Analytics

Machine Learning + advanced statistics + EDM= Smart Analytics

The ability for businesses to be able to make predictions based on their data is imperative for making the right future decisions.

Our integrated data analytics solution helps the leading financial institutions meet their analytics needs to understand the true behavior of data in order to make predictions and improve processes.

It uses the R language and includes features like machine learning, anti-fraud analysis and risk management prediction, making Irion the right choice.

Advantages

All-in-one Analytics

Use just one tool. With Irion, analytic capabilities are already included in the platform, so you can avoid the complexity of having to adopt many different tools, which completes your EDM organization strategy.

Machine Learning & Statistics

Use standard statistics to solve financial issues and gain, for example, an Equity Prices Linear Regression Model. Or, use advanced Machine Learning algorithms to gain, for example, Random Forrest Loan classifications.

Data Simulation

Our user lab lets you test and simulate your machine learning algorithms, so you can prepare data, select features, partition data, use predictive modelling, have a score for that model, and then evaluate it, giving you the most refined and optimized algorithms.

Features

R Engine

Use our powerful R engine to write your own analytic rules or algorithms, from simple technical rules, to complex business rules. The R engine is easy to use since it is a standard, open and well-known language.

Integrated Analytics

Our analytic capabilities are completed integrated with the Irion platform so that your other data management processes, like acquisition and quality, are full integrated with your analytics.

Scalability and Performance

The Irion approach is always rapid and agile, so data simulation is easier than ever. Also, executions can be simply scaled from local-client environments to server executions, making it easy to scale solutions from more simple data management problems to a big data analytic projects.