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Case Studies

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Enhance customer claims experience through advanced analytics

Enhance customer claims experience through advanced analytics

Enhance customer claims experience through advanced analytics

How predictive models enhanced customer experience and increased operational efficiency

How predictive models enhanced customer experience and increased operational efficiency

High impact

Significant EBITDA gain

Cost-saving insights

More accurate predictions

The challenge

Building a data-driven foundation to improve claims and customer experience

A leading Property & Casualty (P&C) insurer aimed to establish a market-leading analytical foundation to capture growth opportunities and drive profitability. The goal was to identify micro-drivers influencing customer satisfaction, profitability, costs, and ROI, enabling improved claims settlement performance and enhanced customer experience.

Key challenges

  • Identifying micro-drivers of customer satisfaction and profitability

  • Predicting and improving claims and customer experience

  • Capturing whitespace growth opportunities efficiently

  • Using analytics for better performance

The solution

Driving revenue and efficiency through analytics in claims settlement

Understanding the organization

Conducted multiple interviews

Analyzed current state

Focused on key areas

Identifying opportunities

Prioritized multiple use cases

Used issue trees for insights

Assessed data and processes

Implementation approach

1

Roadmap development

  • Aligned roadmap with goals

  • Ensured vision alignment

  • Integrated short- and long-term plans

2

Use case breakdown

  • Defined use cases

  • Prioritized impact and readiness

  • Addressed business needs

3

Data and process evaluation

  • Evaluated processes and data

  • Identified improvement gaps

  • Focused on changes

The impact

Boosting profitability and efficiency with analytics-driven insights

Revenue growth

  • High revenue from multiple use cases

  • High EBITDA growth

  • Analytics-driven revenue boost

Efficiency and cost savings

  • Cost-saving opportunities

  • Boosted efficiency

  • Enhanced customer experience

Predictive accuracy

  • Multiple data sources

  • Better prediction accuracy

  • Fewer inaccuracies

Looking ahead

Future data integration

  • Expand data sources for deep insights, accurate predictions

Continuous improvement

  • Refine predictive models for better operational efficiency

Enhanced customer focus

  • Use analytics to improve customer experience and satisfaction