IT Compliance

IT Compliance identifies risks that an organization faces and advises on how to avoid or address them. Organizations are using predictive analytics and AI to sift through datasets to ensure data stored is compliant with all personally identifiable information rules.

IT Compliance

  • View the status and availability of the servers by referring to the uptime and downtime
  • Improve performance by identifying the downtime reason
  • Poor server availability can have a negative impact on the company
  • Calculate the cost bearing due to breakdown in the systems
  • Categorize the system to know where frequent breakdowns occur
  • Optimize the cost by predicting breakdown behaviours
  • Keep a track of the tickets logged, number of tickets solved and number of tickets unsolved
  • Improve operations for a better business flow
  • Reduce the ticket count by identifying the root cause
  • Measure the ROI generated of the IT Department
  • See the trend over a period of time
  • Identify reasons for change in ROI and take business decisions to improve revenue
  • Compare the Revenue generated by the IT expenditure over a period of time


  • Average Cost per Insurance Claim
  • Categorize based on type of claims
  • Properly assess the risk associated with each policy type and adjust pricing accordingly
  • Number of claims in a period
  • Irrelevant products or difficulties in claiming affects customer satisfaction
  • Business management can be improved with thorough understanding of the incurred claims ratio
  • Average time to settle a claim by Policy Type
  • Identify the policy type that takes a longer period of time to settle and find out ways to reduce the time
  • Automation of processes can lead to a better customer experience
  • Sales generated per Broker over a period of time
  • By identifying your top sales performers, you can ensure that the tentative leads are sent to the experts to be converted
  • Can lead to workforce decisions
  • Measures the amount of policy renewals and new policy sales over a period of time
  • Track impact on profitability
  • Identify big ticket value opportunities

Predictive analytics

  • Accuracy of the prediction
  • Factors to be considered For predictive analytics
  • Improvements needed to be implemented for higher Accuracy
  • Determining possible number of frauds
  • How likely to fraud happen
  • Detects new and evolving fraud attacks
  • Areas which more likely have fraud incidents
  • How demand varies with Time, Money
  • Needs of customer
  • Improvements to be implemented to Fulfil the customer demands
  • How a customer has contributed
  • Forecast profitability
  • Determining the region of improvement for growth
  • Customer Acquisition budget
  • How fast orders of customer are processed
  • Measures that can be taken for faster processing the orders
  • Factors that delay the order cycle time

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