Insurance

The insurance industry is confronting important challenges that affect profitability, portfolio allocation and customer loyalty. Big Data and digitalization allow for more segmented customer management and higher sales productivity. It is also possible to implement more robust and precise price management while simultaneously improving internal processes and reducing fraud.

Cognodata assists in the creation of new management methods applied to business based on Big Data Analytics, enabling significant increases in profitability.

Transformation is necessary to maintain profitability and the loyalty of customer portfolios.

  • Marketing

    The amount and quality of information allows insurance companies to design actions that are more precise and efficient at increasing sales and improving customer experience.

    • Planning for commercial operations and implementation through marketing automation and customer experience optimization
    • Optimization of digital capture through attribution, simulation and optimization models
    • Development of customer and product intelligence with Machine Learning techniques
  • Sales

    The digital transformation we are experiencing, as well as the new consumer profile who interacts through non-traditional channels, are also impacting insurance entities, where a network of agents are confronted with new challenges: new capabilities, the use of digital tools, targeted campaigns, multichanneling, etc.

    • Industrialization and automation of sales activity
    • An omnichannel sales model, to take advantage of the new digital channels in a synergic way
    • Enhancement of direct networks, optimizing contacts and protocols with the objective of increasing productivity
  • Actuary and Operations

    The information accumulated from all customer interactions through various channels, as well as Machine Learning techniques, allow greater levels of efficiency to be achieved for the management of customer value and operational efficiency.

    • Advanced pricing models for optimal capture, renewal and value
    • Detection and reduction of customer fraud and collaborators with Big Data Analytics techniques

The amount and quality of information allows insurance companies to design actions that are more precise and efficient at increasing sales and improving customer experience.

  • Planning for commercial operations and implementation through marketing automation and customer experience optimization
  • Optimization of digital capture through attribution, simulation and optimization models
  • Development of customer and product intelligence with Machine Learning techniques

The digital transformation we are experiencing, as well as the new consumer profile who interacts through non-traditional channels, are also impacting insurance entities, where a network of agents are confronted with new challenges: new capabilities, the use of digital tools, targeted campaigns, multichanneling, etc.

  • Industrialization and automation of sales activity
  • An omnichannel sales model, to take advantage of the new digital channels in a synergic way
  • Enhancement of direct networks, optimizing contacts and protocols with the objective of increasing productivity

The information accumulated from all customer interactions through various channels, as well as Machine Learning techniques, allow greater levels of efficiency to be achieved for the management of customer value and operational efficiency.

  • Advanced pricing models for optimal capture, renewal and value
  • Detection and reduction of customer fraud and collaborators with Big Data Analytics techniques

Investing in customer acquisition, loyalty and value management using machine learning is no longer an option. The challenge lies in exploiting data throughout the value chain. The insurers that will lead the way in the future are already making great strides in this direction.

Natalia Medrano Barraza Senior partner of the Financial Services practice
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