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Financial Services enterprises are keen to drive efficiencies and deliver more value to their clients by building automation, advanced data analytics and machine learning capabilities into their business. AI and Machine Learning has become become a default requirement to deliver capabilities such as fraud detection, financial modelling, risk calculations and client analytics. Without the knowledge of how to build and deploy modern data analytics platforms, most companies struggle with old, legacy on-premise technologies and ever increasing volume and velocity of data.

Kushagramati has accumulated decades of technical and domain expertise to accelerate the path for enterprises to adopt powerful technologies to transform and modernize their business.

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We help enterprises develop an actionable road map to building enterprise data analytics capabilities

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Help accelerate their transition to the cloud securely and in a scalable manner

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Retool and reskill their staff to give them strategic advantage over competition


Fraud Detection and Prevention


With ever-increasing online transactions and production of a large volume of consumer data, financial fraud has become increasingly widespread. Research showes 80% of all banks had been victims of fraud. The estimated losses due to fraud are up to 5% of total revenue, and the global loss is reported to be $42 Billion.

At Kushagramati we recognise that each industry would require a tailor-made solution within the domain of the industry. Using machine learning and artificial intelligence in tandem with the silos of collected data, we engineer a veritable solution.


  •  ML-based predictive analytics to spot fraudulent activities

  •  Fraud detection and analysis

  •  Risk management and mitigation

Financial Modelling and Recommendations


Financial Models are a staple in assessing the performance of the business. The incorporation of data analytics would greatly improve not only the accuracy of the model but also the process of generating it. At Kushagramati, the insights generated from analyzing data would make the assumptions in the model more precise and would aid in performing sensitivity analysis to measure the array of outcomes as they change.


  •  Automation in detailed free cash flow forecasts

  •  Automation in valuations with key inputs

  •  Improvement in accuracy and mitigation of errors

  •  ML models for multiple scenarios and sensitivities

  •  Optimisation of return for investors

Regulatory and Compliance Analysis


A tremendous amount of sensitive data is generated by the finance industry daily. The austere laws that govern the industry leave little room for error. Any type of mistake, fraud and malpractice in banks, insurance firms, or even stock market companies will lead to major monetary losses. A data storage and analysis infrastructure can greatly ease the checking of compliance with the ever-changing regulations.


  •  Real-time analysis of the regulatory framework

  •  Ascertain internal compliance of regulations

  •  Lower cost of compliance reporting

  •  Investigate the insights to predict variation in the regulations

Marketing and Omni Channel Engagement


Marketing has evolved with industry 4.0 and insights are imperative in customer acquisition. Even with the right product, it is difficult to get the right customer at the right point in his/her journey. Omnichannel engagement will aid in creating a seamless experience for your customers and hence improve their satisfaction. It will also be highly beneficial to customer retention. With a comprehensive understanding of the target audience and omnichannel optimisation, we can help you turn your product into a household name.


  •  Predict consumer behaviour

  •  Targeted marketing and advertising

  •  Personalized engagement of customers

  •  Enhance customer experience and store operations

  •  Lower cost of customer acquisition

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