A lapsed policy is a product defect
Indian life insurers treat persistency as a sales and service measure, chased with renewal calls after customers have already decided to stop. Most lapses are designed in at the point of sale, so the product team should own them.
Every Indian life insurer reports persistency. It appears in investor presentations, regulatory returns and the public disclosures insurers publish, usually as the share of premiums still being paid in the 13th, 25th, 37th, 49th and 61st months after sale. Analysts watch the 13th-month figure closely, because a second premium is the first real evidence that a sale was sound. Distributors watch it too, since renewal commission depends on it.
Inside most insurers, persistency belongs to sales and service. When it falls, the response is a renewal drive: reminder calls, text messages, branch follow-ups and occasionally a bonus for distributors who bring customers back. Those efforts recover some premiums, and I would not abandon them. But they treat lapse as forgetfulness or inconvenience, and in my experience most lapses are nothing of the sort. A customer who stops in year two has usually concluded, rightly or wrongly, that the policy is not worth its cost. Very often that conclusion was built into the sale.
Lapse is decided at the point of sale
My first lapse study, as a young pricing analyst in 2005, examined regular-premium unit-linked policies. About a third had stopped before their third year, and the customers who stopped clustered among those whose premium was large against their declared income. I have seen the same pattern in every book I have studied since. When we analysed Varunashree's savings business by age in 2022, older bank customers on long-pay plans lapsed at nearly twice the company rate. When we sorted policies by the week they were sold, those written in a quarter's last fortnight persisted worse than the rest. When we launched a term plan for traders, yearly premiums falling due in a lean month lapsed far more than those due after the festive season.
Not one of these lapses was caused by a weak reminder call. Each followed a decision taken earlier: a premium set too high for the income behind it, a product sold to someone it did not suit, a sale pulled forward to meet a quarter, a payment date chosen for the insurer's convenience. These are features of the product and its sales journey. They are therefore the product team's responsibility, and a product team that does not own them will go on designing them in.
Measure persistency where it is caused
The company-wide persistency ratio is a weak management tool for the same reason. It blends healthy business with business that is failing, and it tells nobody where to act. When I became chief product officer in 2021, our 13th-month figure was 78.4 per cent. That single number concealed a spread from above 90 per cent for some agency-sold protection to 66 per cent for older bank customers on our largest savings plan.
We now measure persistency by product, by channel and partner bank, by branch cluster, by the ratio of premium to declared income, by customer age and by the week of the quarter in which the policy was written. Each product owner in my team reviews those cuts monthly and presents them to our management product committee every quarter. The board's policyholder protection committee sees the same cuts for our largest products and channels.
The quarter-end pattern deserves particular attention, because it is the one most often explained away. At Varunashree, policies written in the final fortnight of a quarter persisted about four percentage points worse at the thirteenth month than those written earlier, and the gap was widest in branches with the steepest quarterly quotas. Nobody in those branches set out to sell unsuitable policies. A sale pulled forward by two weeks is simply a sale made with less time to ask whether the customer can keep paying. We did not abolish quarterly plans, which any sales organisation needs, but we stopped paying branch incentives on policies that lapse before their second premium, and the gap has since narrowed to a little over one point.
The measurement changes behaviour because it places responsibility. A branch cluster with weak persistency on one product can be traced to a manager, an incentive or a habit. A band of premium-to-income ratios that lapses heavily can be closed with an eligibility rule. A product that persists poorly in every channel probably has a design fault that no distributor can repair.
Owning the second premium
Owning persistency has led us to decisions that a sales-owned measure would never have produced. We restricted long-pay savings plans for older bank customers in 2022 and accepted a fall of ₹290 crore in APE. We introduced an affordability check that limits regular premiums to a share of declared income unless a reviewer approves more. We let traders pick premium dates that suit their trading year. And we moved part of first-year commission into later years, so that distributors share the cost when a policy stops early.
The results have been steady rather than dramatic. Thirteenth-month persistency has reached 85.2 per cent, and 61st-month persistency 58.6 per cent, up from 49.0 per cent in 2021–22. Our value of new business margin has risen over the same years, partly because policies that persist earn the margins they were priced to earn.
There are honest objections. A product team that owns persistency can grow too cautious and refuse sales that would have persisted perfectly well. Eligibility rules are blunt: a sixty-five-year-old with a generous pension may suit a long-pay plan entirely, and our rule makes her purchase slower. Some customers we turned away bought similar products from competitors with fewer restrictions. I accept those costs and try to measure them, including how often reviewers approve premiums above the standard limit.
What I would ask of any insurer's board is to stop reading persistency as a single figure reported by the sales function. Ask to see it by product, channel and type of customer. Ask who owns the weakest cohort and what has changed in its design since the last meeting. And treat a product whose customers keep failing to pay a second premium as a defect to be repaired or withdrawn, not a distribution problem to be chased with reminders.