The Banking and financial services industry was recently identified as the industry most likely to be disrupted and transformed by millennials at the global level.Financial institutions are being continuously challenged by shrinking revenues and need to improve operational cost efficiencies.

Financial institutions have the benefits of large customer bases and access to rich transactional data.The convergence of machine and human intelligence is disrupting traditional decision-making by equipping organizations with knowledge and insight to predict and prescribe business outcomes.Advances in big data and analytics have led to new products,solutions and services making financial institutions smarter,agile and more competitive.Some trends reshaping the financial services industry include extremely large data sets to analyze to reveal patterns,trends and correlations,real-time predictive and prescriptive analytics for driving deep actionable insights,risk and compliance demanding timely availability of trustworthy,measurable and secure data and so on.Winning in this dynamic market will be determined by how the financial institutions can derive value from data.

banking & finance

The challenge for banks is not being ‘Digital’- it’s providing value that is perceived to be in line with the cost, or better yet, providing value that customers are comfortable paying for. Financial institutions must be able to deliver an easy to navigate, a seamless digital platform that goes far beyond a miniaturized online banking offering.


  • Crossing selling opportunities

    Predictive modeling to identify cross selling opportunities

  • Fraud detection

    Machine learning technology can be used to differentiate between legitimate and fraudulent transaction.

  • Risk Management

    Risk management of the customers by having holistic view about his holding / portfolio.

  • Portfolio Management

    Analytics based portfolio management for Private wealth outfits, Investment advisors and Brokers.

  • Compliance and Regulatory requirements

    Financial markets operate under heavy regulatory requirement. Data mining would help in surveillance and in identifying abnormal trading behavior.

  • Sentiment analysis

    Gathering sentiment of customers at different touch points, performing analytics to identify associated sentiment to enhance customer service.





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