You’ve likely heard—or even participated in—the ongoing debate: spreadsheets or Python? Spreadsheets offer flexibility and ease, while Python provides scalability and power.
But as your insurance models and datasets grow—sometimes into the tens or hundreds of millions of records—both options often struggle to handle increased complexity.
Calculations slow down. Scripts time out. Delays become frequent frustrations.
What if you didn’t have to choose between ease and performance?
Coherent Spark’s Batch APIs combine the flexibility of spreadsheets with the performance and scale of cloud-native engineering—empowering you to run heavy computations across massive datasets, fast.
In fact, some insurers are already running Excel-based models across millions of records—with turnaround times that defy expectations. We’ll show you how.
The Growing Challenge of Scale
As an insurer, scaling your business inevitably means dealing with vast amounts of data and complex calculations. Maybe you've experienced spreadsheets slowing dramatically under thousands of policy records, or Python scripts timing out during large computations.
When timely insights directly influence pricing, risk assessment accuracy, and customer satisfaction, scaling efficiently becomes an absolute necessity for business success.
Batch APIs: Efficient Processing at Scale
Batch APIs transform the way insurers handle large-scale data.
Instead of processing records one by one—which can be painfully slow—you can handle millions at once. One insurer processed 30 million records in under an hour using Coherent Spark’s Batch APIs. That kind of scale unlocks rapid recalibration of mortality assumptions, dynamic rate dislocation analysis, or large-scale scenario testing—without the lag time.
With Batch APIs, you gain:
- Effortless handling of large-scale periodic tasks
- Fast, parallel processing to minimize delays
- Reliable results without manual intervention
These capabilities transform data processing from a bottleneck into a competitive advantage. Let's explore how Coherent Spark makes this possible.
How Coherent Spark's Batch APIs Work
Coherent Spark makes batch processing straightforward, especially if you're already comfortable with Python. Using the intuitive Coherent Python SDK, you effortlessly integrate batch processing into your existing workflow.
Automatic Scalability
Spark dynamically adjusts resources based on workload demands. Whether you're processing a thousand records or tens of thousands, the Batch API scales automatically—no manual adjustments required.
Faster Results, Less Waiting
With parallel processing, Spark significantly reduces calculation time, turning tasks that once took hours into quick, manageable steps.
Simplified Integration
Integrating Spark's Batch APIs into your current workflow is straightforward. You don't have to overhaul your processes—just enhance them, even with minimal Python experience.
Watch It In Action
Seeing is believing—so let's take a quick look at how batch processing works in action.
In this short demo, Ralph Florent from Coherent’s field engineering team walks you through using the Coherent Python SDK for batch processing.
With just a few straightforward lines of code, Ralph shows how you can submit over 1,000 records simultaneously, run computations in parallel, and receive clear, structured results in seconds.
No more manual intervention or tedious waiting—just efficient, scalable processing.
Transforming Insurer Operations: A New Approach to Scale
Imagine an insurer previously struggling with slow spreadsheet calculations for mortality figures, taking hours and impacting timely decision-making.
After adopting Coherent Spark’s Batch APIs, the same tasks were completed in minutes, significantly improving efficiency and allowing actuarial teams to focus on analysis and strategy—not waiting for computations.
Today, scaling your insurance models doesn’t have to mean choosing between flexibility and firepower. Batch APIs provide the flexibility of spreadsheets, the power of Python, and the scalability insurers need to succeed.
Curious how Batch APIs might enhance your operations?
