Which Home Insurance in India is best for apartment owners?
Beginner
60 min
66 views
0 solutions
Overview
Compare home insurance policies covering structure and contents, considering coverage for natural calamities, theft, and alternative accommodation expenses for apartment dwellers.
Case Details
# Aplly.xyz Case Study Submission
## Title
Which Home Insurance in India is best for apartment owners?
## Type
Multi-Criteria Product Comparison
## Difficulty
Intermediate
## Estimated Time
60 minutes
## Overview
Compare home insurance policies covering structure and contents, considering coverage for natural calamities, theft, and alternative accommodation expenses for apartment dwellers.
## Case Details
Function Focus: Multi-Criteria Product Comparison — manual reasoning, decomposition, and critical judgment (no spreadsheet or AI tool permitted in Phase 1)
Scenario:
You are the analyst at a fictional consultancy ("Praxis Advisors") tasked with answering: Which Home Insurance in India is best for apartment owners?. You have a clean, synthetic dataset described below. You must produce a defensible answer using structured reasoning — no tool-assisted shortcut on the first pass.
Dataset Structure:
- insurer
- plan_name
- type
- coverage_amount_lakhs
- annual_premium
- claim_settlement_ratio_pct
- waiting_period_months
- network_hospitals
- co_payment_pct
- room_rent_cap_rs
- pre_existing_wait_months
- critical_illness_cover
- renewability
Tasks:
1. Define the evaluation criteria for the choice and assign weights to each, justified explicitly.
2. Score each alternative by hand against the criteria using the dataset columns.
3. Compute a weighted total and rank the alternatives; show the arithmetic.
4. Run a sensitivity check: change the top two weights by +/10 points and note whether the winner changes.
5. After the manual scoring, redo it in a spreadsheet and reconcile any ranking differences.
Expected Output:
A one-page recommendation memo: criteria & weights, scorecard table, final ranking, sensitivity result.
Evaluation Criteria:
Explicit and justified weights, arithmetic correctness, meaningful sensitivity analysis, defensible final ranking.
## Data Sources
| insurer | plan_name | type | coverage_amount_lakhs | annual_premium | claim_settlement_ratio_pct | waiting_period_months | network_hospitals | co_payment_pct | room_rent_cap_rs | pre_existing_wait_months | critical_illness_cover | renewability |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Star Health | Star Comprehensive | Health | 10 | 12450 | 94.8 | 24 | 12500 | 10 | 10000 | 36 | True | Lifetime |
| HDFC Ergo | Optima Secure | Health | 10 | 11500 | 96.2 | 24 | 13500 | 0 | 15000 | 36 | True | Lifetime |
| ICICI Lombard | Health Saver | Health | 5 | 8200 | 93.5 | 24 | 11000 | 10 | 7500 | 36 | True | Lifetime |
| Max Bupa | Health Reassure | Health | 10 | 13100 | 95.1 | 24 | 12800 | 5 | 12000 | 36 | True | Lifetime |
| New India | MediShield | Health | 5 | 6800 | 97 | 24 | 14000 | 0 | 5000 | 48 | False | Lifetime |
| Reliance General | Health Infinity | Health | 10 | 9800 | 82.5 | 18 | 9500 | 15 | 10000 | 24 | True | Lifetime |
| LIC | Jeevan Arogya | Health | 5 | 7500 | 91 | 30 | 10000 | 10 | 6000 | 48 | False | Age 70 |
| Bajaj Allianz | HealthGuard | Health | 5 | 7800 | 94.5 | 18 | 11500 | 10 | 8000 | 24 | True | Lifetime |
| LIC | Jeevan Umang | Life | 10 | 18500 | 95.5 | N/A | 10000 | 0 | N/A | True | Age 99 | |
| HDFC Life | Click2Protect | Life | 25 | 28500 | 94.8 | N/A | 10000 | 0 | N/A | True | Age 85 | |
Full dataset: https://github.com/arora200/aplly_case_db/datasets/050-insurance-products (synthetic, 16 records)
## Solution Frameworks
Multi-criteria weighted scoring, pairwise trade-off analysis, cost-benefit decomposition, sensitivity/robustness check
## Solver Guidance & Tutorials
_Solver guidance added by the pipeline (tutorial links) — see `solver_guidance` field._
## What You'll Learn
- Turn vague preferences into weighted criteria
- Build a transparent scorecard
- Test how fragile your winner is
## Tags
Home Insurance, Apartment, India
## Registration Links
Register as Solver / Register as Evaluator
## Title
Which Home Insurance in India is best for apartment owners?
## Type
Multi-Criteria Product Comparison
## Difficulty
Intermediate
## Estimated Time
60 minutes
## Overview
Compare home insurance policies covering structure and contents, considering coverage for natural calamities, theft, and alternative accommodation expenses for apartment dwellers.
## Case Details
Function Focus: Multi-Criteria Product Comparison — manual reasoning, decomposition, and critical judgment (no spreadsheet or AI tool permitted in Phase 1)
Scenario:
You are the analyst at a fictional consultancy ("Praxis Advisors") tasked with answering: Which Home Insurance in India is best for apartment owners?. You have a clean, synthetic dataset described below. You must produce a defensible answer using structured reasoning — no tool-assisted shortcut on the first pass.
Dataset Structure:
- insurer
- plan_name
- type
- coverage_amount_lakhs
- annual_premium
- claim_settlement_ratio_pct
- waiting_period_months
- network_hospitals
- co_payment_pct
- room_rent_cap_rs
- pre_existing_wait_months
- critical_illness_cover
- renewability
Tasks:
1. Define the evaluation criteria for the choice and assign weights to each, justified explicitly.
2. Score each alternative by hand against the criteria using the dataset columns.
3. Compute a weighted total and rank the alternatives; show the arithmetic.
4. Run a sensitivity check: change the top two weights by +/10 points and note whether the winner changes.
5. After the manual scoring, redo it in a spreadsheet and reconcile any ranking differences.
Expected Output:
A one-page recommendation memo: criteria & weights, scorecard table, final ranking, sensitivity result.
Evaluation Criteria:
Explicit and justified weights, arithmetic correctness, meaningful sensitivity analysis, defensible final ranking.
## Data Sources
| insurer | plan_name | type | coverage_amount_lakhs | annual_premium | claim_settlement_ratio_pct | waiting_period_months | network_hospitals | co_payment_pct | room_rent_cap_rs | pre_existing_wait_months | critical_illness_cover | renewability |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Star Health | Star Comprehensive | Health | 10 | 12450 | 94.8 | 24 | 12500 | 10 | 10000 | 36 | True | Lifetime |
| HDFC Ergo | Optima Secure | Health | 10 | 11500 | 96.2 | 24 | 13500 | 0 | 15000 | 36 | True | Lifetime |
| ICICI Lombard | Health Saver | Health | 5 | 8200 | 93.5 | 24 | 11000 | 10 | 7500 | 36 | True | Lifetime |
| Max Bupa | Health Reassure | Health | 10 | 13100 | 95.1 | 24 | 12800 | 5 | 12000 | 36 | True | Lifetime |
| New India | MediShield | Health | 5 | 6800 | 97 | 24 | 14000 | 0 | 5000 | 48 | False | Lifetime |
| Reliance General | Health Infinity | Health | 10 | 9800 | 82.5 | 18 | 9500 | 15 | 10000 | 24 | True | Lifetime |
| LIC | Jeevan Arogya | Health | 5 | 7500 | 91 | 30 | 10000 | 10 | 6000 | 48 | False | Age 70 |
| Bajaj Allianz | HealthGuard | Health | 5 | 7800 | 94.5 | 18 | 11500 | 10 | 8000 | 24 | True | Lifetime |
| LIC | Jeevan Umang | Life | 10 | 18500 | 95.5 | N/A | 10000 | 0 | N/A | True | Age 99 | |
| HDFC Life | Click2Protect | Life | 25 | 28500 | 94.8 | N/A | 10000 | 0 | N/A | True | Age 85 | |
Full dataset: https://github.com/arora200/aplly_case_db/datasets/050-insurance-products (synthetic, 16 records)
## Solution Frameworks
Multi-criteria weighted scoring, pairwise trade-off analysis, cost-benefit decomposition, sensitivity/robustness check
## Solver Guidance & Tutorials
_Solver guidance added by the pipeline (tutorial links) — see `solver_guidance` field._
## What You'll Learn
- Turn vague preferences into weighted criteria
- Build a transparent scorecard
- Test how fragile your winner is
## Tags
Home Insurance, Apartment, India
## Registration Links
Register as Solver / Register as Evaluator
What You'll Learn
- Problem-solving and analytical thinking
- Data-driven decision making
- Business strategy development
- Professional report writing
0
Solutions Submitted
Difficulty
Beginner
Estimated Time
60 minutes
Relevance
Fresh
Source
Market Research 2026