Shrinking Insurance Policies

PandasMediumMid level~10 min

Problem

You are given one DataFrame `policy_history` (loaded from `policy_history.csv`), a full history of policy changes with columns `change_id`, `holder_id`, `change_date`, `change_kind` ('open', 'upgrade', 'reduce', or 'close'), `tier_name`, and `monthly_premium` in force after that change. Flag the shrinking policies: holders whose policy is still in force (their most recent change is not a 'close'), who have reduced coverage at least once (at least one 'reduce' change), whose current monthly premium is below half of the highest premium they ever paid, and who have been a holder for at least 60 days (from their first to their latest change). Return a DataFrame with the `holder_id` of each flagged holder. Order by tenure in days descending, then by `holder_id` ascending.

Input data

Example rows — the live problem includes the full dataset.

policy_history

change_id	holder_id	change_date	change_kind	tier_name	monthly_premium
1	100	2024-01-01	open	platinum	80.0
2	100	2024-02-15	reduce	gold	50.0
3	100	2024-03-20	reduce	silver	30.0
4	200	2024-01-05	open	gold	60.0
5	200	2024-02-10	reduce	silver	35.0

Expected output

Your answer should return 2 rows with the columns holder_id.

Starter code (Pandas (Python))

import pandas as pd

def find_shrinking_policies(policy_history) -> pd.DataFrame:
    # Your code here
    return policy_history

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