The magnitude of data dynamics in banking is phenomenal; so are the opportunities. If data is well analyzed and managed you can increase revenue per account, strategize to enhance services, personalize delivery through technology. Operational efficiencies and risk compliance are major outcomes of a well implemented decision analytics technology. All departments can realize the benefits of applying well oiled analytics strategies. View our offerings, use cases, solutions and advantages:

  • Professional Services
  • Technology Expertise

Key Use Cases

Compliance and regulatory reporting, Risk analysis and management, Fraud detection and security analytics, CRM and customer loyalty programs, Credit risk, scoring and analysis, High speed arbitrage trading, Trade surveillance Abnormal trading pattern analysis, Profitability Analytics, Customer Life Time Value, Risk Management

Retail Banking

  • Market Mix Modeling, Credit Risk Management, Channel Optimization, Customer Lifetime Value, Cross-sell Analytics


  • Acquisition Analytics, Collections Management, Web Analytics, Fraud Management

Commercial Banking

  • Credit Risk Management, Risk Measurement, Compliance / Monitoring,

Investment Banking

  • Portfolio Optimization, Risk Management, VaR Modeling, Regulatory Compliance, Debt Management

Analytics Solutions

  • Big Data Banking
  • Descriptive Analytics
  • Predictive Analytics
  • Prescriptive Analytics
  • Data Management and Banking Governance

Analytics Advantages

  • Facilitate visual exploration and pattern discovery of big data
  • Exploit social "content" and make new insights that foster greater collaboration
  • Facilitate better sharing, guided analysis and decision making
  • Utilize mobile for presentation on any devices, as well as location-based intelligence
  • Embrace cloud; offering flexibility for licensing and deployment

Partnership Strategy

Karvy Analytics partners with you throughout the following strategic recommendations by analysts:

  • Determine your use case before investing in big data technology
  • Experiment and pilot to validate the value of the use cases
  • Leverage cloud solutions for experimentation to simplify initial deployments

Tools and Technologies

  • R, Python, Mahout
  • SAS, Dell Statistica
  • Visualization: Tableau, Spotfier, Pentaho, ClickView
  • Big Data: Hortonworks, Splunk, Greenplum, Terradata Aster
  • IBM Mimic, I-Log Elixir, Stamen, Juice Analytics, VE Videosynthesis, Photosynth, Predixon
  • SSSAP HN< SSP Big Data, Oracle Exalytics, Datamirror, Revolution Analytics
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