Vivita Insurance

Vivita is a major Asian term life insurer considering a bold new initiative — Project Wapple — that would offer premium discounts to new customers who purchase a fitness tracker and maintain minimum exercise levels. The case requires candidates to evaluate the financial impact of better risk segmentation, model profit before and after the program, and assess whether the initiative should also be extended to existing customers. It is a BCG online case format, heavy on quantitative modeling and business judgment.

Client: Vivita, a major insurer in Asia that sells term life insurance. Policy structure: $100 yearly premium; $100,000 lump-sum payout if the policyholder dies within the year. Current Approach: Vivita traditionally estimates claim risk using broad demographic data — age, gender, and smoking status. This is an industry-standard but imprecise segmentation method. Project Wapple: A proposed program offering a premium discount to new policyholders who volunteer to purchase a fitness tracker and engage in at least moderate physical activity throughout the year. The hypothesis is that these individuals have lower mortality risk, allowing Vivita to price more accurately and attract lower-risk customers while improving its risk pool.

Should Vivita implement Project Wapple? What is the estimated profit impact of the program, and should the discount be extended to existing customers as well as new sign-ups?

Step 1 — Define the profit model: Identify all required variables (A, B, D, F, G from the case) and build a two-scenario profit model — pre-Wapple and post-Wapple. Step 2 — Quantify program impact: Calculate the change in revenues (driven by new volume and new average price) and the change in costs (driven by lower claim rate × volume). Determine net profit impact. Step 3 — Existing customer extension analysis: Model the profit impact of extending the discount to existing customers separately. Compare the revenue loss (discounting renewals) vs. the cost savings (if fitness reduces claim rates among existing customers). Step 4 — Competitive dynamics: Assess whether the program creates adverse selection for competitors (healthier customers moving to Vivita) and whether this constitutes a durable moat or a temporary advantage. Step 5 — Implementation risks: Evaluate data privacy concerns around wearable data, customer trust issues, program compliance monitoring, and potential regulatory considerations across Asian markets. Key Insight: The core financial logic of Wapple rests on the new claim rate (B) — if active customers have materially lower mortality, the premium discount pays for itself through cost reduction. The opt-out rate among existing customers is the key risk: if 600K opt out, Vivita retains a large pool of unimproved-risk, full-premium customers — which is actually beneficial to margins as long as those customers do not defect to competitors offering the program.