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How AI And Data helps Insurance: A Data use case

AI meet Data - Who wants to go up to 50% faster, anyone? This changes how we work with data and produce outputs. 

The Common needs for Reporting in insurance are:

  • Operational

  • Regulatory

  • Exceptions

  • And Insights

Doing valuations at clients, the common themes in the data teams are:

  • Getting the data from source to a target environment

  • Wrangling and making sense of the data

  • Creating data repositories (warehouse) to make it more accessible

  • Apply business rules and logic to the data

  • Documentation

  • Reporting and Insights activities on the data.

Working through multiple use cases with AI and tie them to business domains, my clients continue to get remarkable results. Using #EnterpriseAI technology enables secure environments to business problems. Using #GoogleVertexAI and #AzureAI and the fine tuned AI specifically for data is the key to unlocking the innovation with data solutions #GeminiCode #GitHubCopilot

🔔 The key is prompting - and knowing what you want. 

So what can we do with AI and Data, grounded on a business problem or requirement we can:

Simplifies the main components of data analysts and data engineers:

- Explain code

- Create code (SAS, SQL, Python etc)

- Rewrite code (From one language to another)

- Documentation (yes all of it)

Advanced AI and Data allows us to:

- Translate requirements into code 

- Generate new insights and business recommendations

- Use Natural language to solve the business problem


  • Up to 50% efficiency in explaining code and logic

  • Up to 60% efficiency in documentation of Source to Target , Impact Assessments, Business Rules and Documentation

  • Up to 30% Faster Code generation

  • Up to 30% faster code re-write from one language to another

  • Overall Improvement in User Experience and satisfaction

If you want to get your data team moving quicker, and using technology to augment their outputs, send us a message and we will love to work with you.

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