Which Critical Illness Insurance in India provides the most comprehensive coverage?
Intermediate
90 min
62 views
0 solutions
Overview
Evaluate critical illness policies covering major illnesses like cancer, heart attack, stroke, and kidney failure. Compare sum insured options, survival period clauses, and premium rates across insurers.
Case Details
# Aplly.xyz Case Study Submission
## Title
Which Critical Illness Insurance in India provides the most comprehensive coverage?
## Type
Multi-Criteria Product Comparison
## Difficulty
Intermediate
## Estimated Time
60 minutes
## Overview
Evaluate critical illness policies covering major illnesses like cancer, heart attack, stroke, and kidney failure. Compare sum insured options, survival period clauses, and premium rates across insurers.
## 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 Critical Illness Insurance in India provides the most comprehensive coverage?. 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
Critical Illness Insurance, Health Insurance, India
## Registration Links
Register as Solver / Register as Evaluator
## Title
Which Critical Illness Insurance in India provides the most comprehensive coverage?
## Type
Multi-Criteria Product Comparison
## Difficulty
Intermediate
## Estimated Time
60 minutes
## Overview
Evaluate critical illness policies covering major illnesses like cancer, heart attack, stroke, and kidney failure. Compare sum insured options, survival period clauses, and premium rates across insurers.
## 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 Critical Illness Insurance in India provides the most comprehensive coverage?. 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
Critical Illness Insurance, Health Insurance, 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
Intermediate
Estimated Time
90 minutes
Relevance
Fresh
Source
Market Research 2026