How I Learned to Find the Most Recent Policy Version

One of the most valuable lessons I’ve learned in insurance data work is how to consistently identify the most recent version of a policy. It sounds simple, but getting it wrong can lead to outdated reports, misleading metrics, and failed downstream processes.

If you’re working with transactional policy data — where each update (ADD, CHG, CNL) is stored as a separate row — this problem will feel familiar. In our case, every policy event created a new record, and we needed to report only the latest version of each policy.

In this post, I’ll walk you through the exact problem I faced, how I first attempted to solve it, and how the ROW_NUMBER() window function ended up being the most elegant and reliable solution.

The Problem

Let’s say you’re working with the following tables:

• policies: each row represents a transaction (ADD, CHG, CNL)

• policy_versions: each row links to a policy_id and possibly a quote_id

Here’s a simplified query I tried:

SELECT * FROM policies WHERE creation_date = ( SELECT MAX(creation_date) FROM policies p2 WHERE p2.policy_number = policies.policy_number );

This worked... until i realized it didn’t scale well when I started joining it to the policy_versions or quotes tables. But the deeper issue came to light when I started grouping and aggregating policies with other transactional tables.

In one real-world example, I needed to:

• Join policies to quote versions, venues, and coverages

• Aggregate values like maximum daily attendance and coverage limits

• Calculate adjusted premiums across versions

  
  

That’s when I found myself writing a complex report that needed to return only the latest version of a policy while computing premiums and merging event information — and the MAX() function simply couldn't handle that workload.

The issue was subtle: creation dates weren’t always a clear or unique indicator of the “most recent version.” I needed a way to find the latest transaction per policy, without breaking joins or losing access to the full row.

Enter ROW_NUMBER()

I’d used basic window functions before (like RANK() and COUNT()), but hadn’t really appreciated their full power until this moment.

The beauty of ROW_NUMBER() is that it assigns a unique sequential number to each row within a group — based on your sort criteria. So, instead of trying to wrangle MAX() in a subquery, I could do this:

SELECT policy_id, policy_number, transaction_type, creation_date, ROW_NUMBER() OVER ( PARTITION BY policy_number ORDER BY creation_date DESC ) AS row_num FROM policies;

policy_id	policy_number	transaction_type	creation_date	row_num
72183a12-6758	ABC100019	CHG	2024-02-22	1
72183a12-6758	ABC100019	CHG	2024-01-23	2
72183a12-6758	ABC100019	ADD	2023-12-24	3

This ranks every transaction for a policy_number. The most recent one (by creation_date) gets a row_num of 1.

To filter only the most recent:

WITH ranked_policies AS ( SELECT , ROW_NUMBER() OVER ( PARTITION BY policy_number ORDER BY creation_date DESC ) AS row_num FROM policies ) SELECT  FROM ranked_policies WHERE row_num = 1;

This query worked not only because it identified the latest transaction, but because it preserved the full detail of the row in a way MAX() never could.

Why ROW_NUMBER() is superior in Grouped Queries

In a more advanced report, I had to:

• Join policy transactions with quote details, venues, and coverages

• Aggregate values like attendance limits and premiums

• Compare each transaction to its previous version

  
  

With ROW_NUMBER(), I could do this cleanly:

ROW_NUMBER() OVER (
  PARTITION BY PO.ID
  ORDER BY V.DATE_BOUND DESC
) AS transaction_version

Then compare changes with a self-join:

LEFT JOIN filtered_policy_version P1
  ON P2.POLICY_ID = P1.POLICY_ID
  AND P1.DATE_BOUND < P2.DATE_BOUND
  AND P1.transaction_version = P2.transaction_version + 1

This enabled version-to-version comparisons — something MAX() just can't handle.

Joining to policy_versions

Once I had the latest policies, I could join safely:

WITH ranked_policies AS (
  SELECT *, ROW_NUMBER() OVER (
    PARTITION BY policy_number
    ORDER BY creation_date DESC
  ) AS row_num
  FROM policies
)
SELECT rp.*, pv.quote_number, pv.version_status
FROM ranked_policies rp
LEFT JOIN policy_versions pv
  ON rp.policy_id = pv.policy_id
WHERE rp.row_num = 1;

This gave me one clean, current row per policy, with all related metadata.

Practical Use Cases

• Generating reports of all active policies

• Matching policies to their latest quotes, coverages, and events

• Identifying orphaned policies (e.g., those without a corresponding PAY transaction)

• Calculating premium adjustments across transactions

• Cleaning up duplicate entries in staging tables

  
  

Takeaways

• Policies evolve through multiple transactions (ADD, CHG, CNL), making it hard to know which version is the most current.

• Creation_date alone isn’t always reliable, especially in large datasets or when clients retroactively submit changes.

• Use ROW_NUMBER() with PARTITION BY policy_number ORDER BY creation_date DESC to rank transactions.

• Filter where row_num = 1 to get the most recent policy version.

• Join to policy_versions and other tables after filtering to reduce joins and improve performance.

• Use row rankings to support comparison logic, calculate premium differences, and maintain clarity across complex joins.