Predictive Analytics – Using Machine Learning

Powering OpportunitiesMachine Learning

Risk Edge’s Predictive Analytics helps you make sense of your enormous data – with an objective of finding answers to some of your most critical strategic and operational issues. With Risk Edge, you can see how several data models can help you gain futuristic insights into Prices, Risks, Supply Chain Opportunities and Risks, Consumer Preferences and many other such areas.



Operations: Apply Actionable Insights

  • Understand which parts of operations affect your organization’s strategic objectives the most
  • Learn how correlated are your inventory levels, vessel movements, delivery schedules with your profitability
  • Optimize the most critical parts of your operations first to deliver best results


Enterprise Risk Management: A Complete picture of risks across verticals

  • correlations - pearsonDon’t just track Market or Credit Risks, but also other risks associated with business
  • Avoid Operational Risks, Detect Fraud using advanced predictive capabilities


Cash Flows: Optimize and Integrate with Operations

  • View every part of operations in conjunction with Cash Flows
  • Utilize deeper insights to reduce Cost of Capital and improve Profitability


Consumer Preferences: Understand hidden & changing Trends

  • Analyze Demand, Supply patterns to see hidden trends in changing Consumer preferences
  • Use competitor / lateral company’s sales data to drive your product research / new product launches


Profitability: Use Predictive Analytics on Market Data

  • Use historical Market Data (Fundamental, Price Data) with other variables to predict prices to aid trading profits
  • Amongst hundreds of variables that affect your organization’s business, identify those which are most critical
  • Understand the behaviour of most critical variables and quantify their impact on profitability.
  • Download our Whitepaper on Predicting Crude Oil Prices

credit defaultCredit Defaults: Predict and Prevent Counter-party Defaults

  • Use subjective and numeric data to evaluate default probability of Counter-parties / Loan portfolios.
  • Several different kinds of Classification Models built-in to help you predict defaults with 80-90% accuracy.
  • Classify new counterparties based on the data into various risk buckets.
  • Download our Whitepaper on Predicting Credit Defaults.



Our Machine Learning Center of Excellence (CoE) has built and deployed many such applications after analyzing client requirements in depth. There are multiple methods of deploying and accessing these applications – from Private servers to Cloud, which we’ve used for our clients depending on their need. Our typical projects are deployed within 2 months.

Tell us about your requirements and we’ll give you deployment, technology, pricing and timelines based on your preferences ! 

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Our Clients

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