EARLY DEATH OF LIFE INSURANCE POLICIES IN INDIA

Insurance is a long-term business in which customers and the industry benefits if the policies are held for long. But given the poor persistency performance, huge costs and fat commissions, customers haven’t benefited in a meaningful way, while insurers and distributors have. The Indian life insurance industry continues to manufacture and sell products that die early. According to the Handbook of Statistics published by the insurance regulator, in FY17, the life insurance industry was able to retain an average of 65% of its policies after the first policy year and 34% after the fifth policy year. This means that one in three policies sold don’t survive 5 years. These numbers compare poorly with the global average, where life policies retain close to 90% of their customers after a year of sale and about 65% after 5 years. In insurance parlance, policy retention is known as ‘persistency’ and ‘persistency ratio’ measures how long customers stay with their policies, by looking at the number of policy renewals year after year. These numbers don’t bode well as life insurance is in the business of selling long-term products, of 10 years or more, and so it benefits if customers renew their policies year after year. Poor persistency doesn’t just hurt the insurer; you as a customer stand to lose much more largely because of the way life insurance policies are designed. Tracking persistency is, therefore, important, but the way persistency ratios are disclosed at present is not precise enough to give a true picture.

Life insurance is a long-term contract and the costs are built keeping this in mind. Costs of a 15- or 20-year product are front loaded on the assumption that the policyholder will stay the course for the full term of the policy. However, the latest persistency numbers released by the insurance regulator point out that the industry on an average is unable to retain even a third of its customers at the end of five years of a policy. Excessive delay in payments and servicing of the policy leads to the policy being dead or lapsed. However, a lapsed policy may be revived by fulfilling the terms and conditions as per the policy statement. To avoid losses to all parties, generally the revival and reinstatement is encouraged and facilitated. The combination of economic slowdown and mis-selling of policies has hit the Indian insurance industry where it hurts the most. One of the reasons behind the high lapse ratio is the slowdown that gripped India. Reeling under financial stress, many policyholders chose not to renew their policies. But experts also blame “rampant mis-selling” by some private insurers. Many policies were sold without adequately explaining features to policyholders, leading to non-renewal of policies. Almost the entire industry has lower than 50% persistency in the 61st month. This means that half the policyholders left within five years. Internationally, this is over 65% on an average.

EARLY COLLAPSE OF LIFE INSURANCE PLANS:

Even as persistency is important for insurers to make money, heavy penalties on early exits and lapses ensures that they still made money. It’s the policyholder who loses money invested. Persistency numbers are still improving but are still far below global averages of 90% after one year and 65% after 5 years. Although still a long way to go, persistency numbers are improving slowly. In FY16, the average persistency ratio in the 13th month was 61%; in FY17, this number has improved to 65%. For the 61st month (the regulator doesn’t publish persistency beyond 5 years), persistency in FY16 was just 29% which improved to 34%. Increase in ticket size by selling policies to more affluent customer segments is perhaps the main reason behind improvement in the 13th month persistency. In the case of 61st month persistency, new ULIPs, where most customers continue to pay premiums even after 5-year lock-in period, is the main reason. But the industry has a long journey ahead as actuarial experts say persistency of less than 80% can impact profitability over the long run since fixed costs get spread over a smaller base, keeping the expense ratio high. Changing products and distribution can bring about improvement faster. Persistency will improve if traditional plans undergo reform similar to unit-linked insurance, or if a higher proportion of products is sold through direct channels like the online medium. Systemic changes like training agents to sell in a need-based manner takes place relatively slowly. Life insurance is a long-term contract and the costs are built keeping this in mind. Costs of a 15- or 20-year product are front loaded on the assumption that the policyholder will stay the course for the full term of the policy. However, the latest persistency numbers released by the insurance regulator point out that the industry on an average is unable to retain even a third of its customers at the end of five years of a policy.

WHOSE MONEY IS LOST ?

Poor persistency is largely reflective of the hygiene standards of the industry. But insurers also hold the way life insurance products are constructed responsible. ULIPs that were sold six years ago had a feature that allowed policyholders to exit after three years, and most of these did not have surrender penalties after the 5th year. This led to customers prematurely closing these policies rather than staying longer with them. LIC, however, feels consumer behaviour is responsible. Some of the factors that can be attributed to low persistency are unexpected change in policyholder’s financial position, uncertainty in job market and failure to pay premiums on time. Some policies have auto-cover facility and policyholders have the option to pay premiums as per their convenience. This is not reflected in persistency ratios. Even as persistency is important for insurers to make money, heavy penalties on early exits and lapses ensures that they still made money. It’s the policyholder who loses money invested. In 2010, IRDAI stepped in to cap surrender penalties in ULIPs, which is what the industry was selling till then (the cap is maximum of Rs.6,000 in the first year to Rs.2,000 in the fourth year, and nil thereafter). The industry moved to selling traditional plans, prompting the regulator to review these as well. But even under the new regulations, traditional plans continue to have high exit charges in the initial years. So, you lose money if you quit a traditional plan midway. How long customers stay with their policies is determined by the persistency ratio, which indicates the number of policies that continue to generate renewal premiums that are due to be paid. Almost the entire industry has lower than 50% persistency in the 61st month. This means that half the policyholders left within five years. Internationally, this is over 65% on an average.

PERSISTENCY RATIO:

Currently, only five insurers from a total of 24 have upwards of 70% in the 13th month persistency ratio. Eighteen have improved their numbers from FY16 while six insurers have seen a drop in this bucket. The sharpest drop was witnessed by HDFC Standard Life Insurance Co. Ltd, which got listed last year. Its 13th month persistency fell from 71% in FY16 to 67% in FY17. As per its red herring prospectus, the drop is largely due to the poor persistency of its health insurance portfolio. In the 61st month ratio, HDFC Life was able to retain at least half the policies, which is more than what we can say about most insurers. A poor persistency means that you are losing money by way of exit penalties. Most of what the insurance industry sells now is traditional plans, which have high exit penalties—100% of the premium in the first couple of years. So, when you decide to opt out of a policy, you actually end up forgoing your premiums. To give you an idea of the magnitude of loss to customers, here are some rough calculations. In FY17, the industry sold 26.4 million policies. Given an average persistency rate of 65% after a year of sale, only 17.2 million policies were renewed. This means 9.26 million policies dropped out, and since the industry is dominated by traditional policies, it means that a large part of these policies didn’t give any money back to the customers. Persistency has not shown a marked improvement and if the insurers are not able to retain even 50% of their customers after 5 years, then the products being sold are really not long-term products. Some policies have auto-cover facility and policyholders have the option to pay premiums as per their convenience. This is not reflected in persistency ratios.

PEOPLE END UP BUYING PRODUCTS:

This brings us to an important point: how insurers currently report persistency figures. Some insurers include group policies -that are largely single-premium policies- and single-premium retail policies in their persistency calculation. Including this inflates the persistency reported as these are one-time payment policies and don’t lapse. Reporting persistency on the basis of retail regular premium policies will reflect true customer retention, and that needs to be standardised. What’s also required at this point is further slicing of this number. It’s important to break persistency numbers by policy type and channel of distribution. Term plans have a retention rate of more than 90%, and even if you lapse, you don’t lose anything in them because you are only paying the cost of insurance. Poor persistency is primarily the result of policyholders surrendering or lapsing their policies midway. This behaviour is largely caused by poor sales practices followed by the insurance industry. Poor persistency is mainly on account of lapses. A lapse occurs at the point of sale when a policy is mis-sold or bought with poor understanding. Some of the factors that can be attributed to low persistency are unexpected change in policyholder’s financial position, uncertainty in job market and failure to pay premiums on time:

Even in ULIPs, the exit load is minimal, but it’s very high in non-linked plans. So there is a lot of merit in slicing the persistency numbers across product categories because insurers still manage to make profits through policy lapses in non-linked plans but customers lose the entire capital. Persistency in ULIPs has improved a lot owing to a better product construct. Charges are capped and exit penalties are minimal. There is no motivation to surrender the policy, but the same is not true for traditional plans where policyholders sometimes prefer to lapse than continue with a plan they don’t understand. Persistency ratios need to get cleaner and sharper as they are a commentary on the selling practices of an insurance company. For you, this is what poor persistency indicates. Majority of the plans are investment plans and a poor persistency indicates that people end up buying products they don’t need or understand. Stick to a term plan for now.

WHEN DO INSURANCE POLICIES LAPSE?

Lapsed policies show market immaturity where product manufacturers and buyers are still figuring out the right product mix. Poor persistency is primarily the result of policyholders surrendering or lapsing their policies midway. This behaviour is largely caused by poor sales practices followed by the insurance industry. Poor persistency is mainly on account of lapses. A lapse occurs at the point of sale when a policy is mis-sold or bought with poor understanding. A policy lapses when you skip paying its premium, not just on the due date but even within the grace period—which is typically a month. However, not all policies lapse automatically. For instance, a term insurance policy lapses if you skip paying the premium. In this case, you forfeit the insurance benefit as well as the premium paid towards the policy thus far.  In the case of a unit-linked insurance plans if you skip paying the premium in first 5 years, or during the lock-in period, the policy is considered lapsed and the insurer moves the money (or the fund value) to the discontinuance fund and levies a discontinuance charge—which is a maximum of Rs 6,000 if discontinued in the first year, and reduces to Rs 2,000 in the fourth year, and nil thereafter. If you skip paying premiums after the lock-in period, the insurer lets you choose between surrendering the policy, reviving it or converting it into a paid-up policy with reduced sum assured. In the case of traditional plans, if you don’t pay the premiums before policy becomes paid-up—that is, before it acquires a surrender value—you risk forfeiting all the premiums. However, once the policy is paid-up, the policy doesn’t lapse but automatically continues with a reduced sum assured. Life insurance companies offer a small window of opportunity to revive the policy during the revival period.  The rules state that insurers need to offer a revival period of at least 2 years within which you can reinstate your policy.

HOW TO REVIVE A LAPSED POLICY?

Lack of transparency and data in life insurance does not give us a handle on getting a proper break-up of lapsation from all the parts of the life insurance industry; therefore it is difficult to see the full picture of the lapsation story. But it is clear that lapsation has been a tool for profits for some insurance companies. With thousands of crore of profits coming from lapsed policies, would we be wrong to wonder if lapsation, as a deliberate means to pad up profit, is not a considered strategy for the insurance companies? In all of these cases, insurers may give you a window of at least 2 years to revive the policy. In the case of ULIPs, insurers will reverse the discontinuance charges that were levied upon revival. After 2 years, insurers may not entertain a request for revival, especially if it’s a term plan because it comes with a very high insurance cover. But insurers do relax these rules on a case-to-case basis. The ease of reviving a policy will depend on the time that’s passed since the policy lapsed. In case of an early lapse, that’s within 6 months, insurers may even allow you to revive the policy online on the basis of a declaration of good health. However, if the policy has lapsed for more than 6 months, then insurers may insist on fresh medical check-ups. This will also depend on the sum assured and your age; of course, the older you are and the higher the sum assured, more are the chances of being sent to medical tests. In order to revive the policy, you will need to pay all the due premiums, along with penalty interest. But insurers sometimes waive these conditions, especially during revival campaigns. They may also waive the need for medical check-ups, and reduce the penalty charge or waive it completely. Poor execution capabilities of insurers constitute the biggest roadblock to improving persistency.

CUSTOMER ACQUISITION & CUSTOMER RETENTION:

The elements of customer acquisition and customer retention matrices are different in life insurance business, as customer retention for a long period of 7 to 10 years is critical for earning a profit from customer life-time value. Customer retention in life insurance is measured in terms of persistency rate, or the percentage of policies renewed every year over the policy period. In 2015-16, the average persistency rate for life insurance policies in the 13th month was just 61%. More than two-thirds of life insurance policies in the 61st month had lapsed during the year as policyholders did not pay renewal premium. Globally, the persistency ratio is close to 90% in the 13th month and above 65% after 5 years. The acceptable persistency rate in life insurance is 80% for 3-year-old policies and 60% for 10-year-old policies. Life insurance persistency in India is acutely low and is clearly hurting life insurance companies. The influencers of persistency rate are all the three stakeholders: life insurers, agents, and customers. The customer contact points of life insurers are limited and customers tend to lose interest after the initial purpose of tax savings; lacking awareness that the utility of life insurance is over a much longer term. Furthermore, the focus of agents is largely on their upfront commission income. The fundamental cause of the low persistency rate is that individuals still largely perceive life insurance as a tax-saving investment instruments and not as a financial protection tool. A large chunk of life insurance is sold in the last quarter of every financial year. This is the period when tax assessors rush to make investments to reduce tax liabilities. All the three stakeholders suffer losses from the current situation: insurers do not make profits on customers who decide to lapse policies within 6 to 7 years. Customers lose money if they do not persist with their policies long enough, with the entire investment lost if policies are persisted for less than 2 years. The focus of the agents on the high upfront commissions makes them lose out on opportunities of deepening relationships with customers.

PERSISTENCY CALCULATION:

Persistency ratio shows the leakages in year-on-year renewals of life insurance policies and can be calculated both in terms of the amount of premium and the number of policies. The Insurance Regulator believes that if persistency is calculated based on premium, the number gets skewed if one policy with a large premium gets lapsed. Leakages on account of death or maturity are not factored in, so this ratio primarily indicates leakages on account of lapse or surrender. Insurers calculate the persistency ratio in two ways. The first method is to calculate persistency on a cumulative balance basis. This method calculates the leakages of the policy from the base year or the year in which the policies were sold. So, if the insurer sold 100 policies and 70 of these were renewed after a year or in the 13th month, the 13th month persistency will be 70%. After the second year, or in the 25th month, if 60 policies were renewed, the 25th month persistency will be 60%. If renewal after three years or in the 37th month is only for 50 policies, the 37th month persistency ratio will be 50%. Even as these are different groups, persistency ratios under the cumulative balance method normally decreases in the subsequent years, so the number for the 25th month will be lower than that for the 13th month. But there could be a minor variation. It’s a possibility that persistency of 25th or 37th month may look better simply because these are calculated on different cohorts of policies—25th month being policies sold two years ago and 37th month being policies sold three years back. But this difference will be rather gradual on a cumulative balance basis. A sharp variation, especially upwards, could perhaps mean that the ratio is calculated on a reducing balance basis. The other method—reducing balance—calculates the leakage from the preceding year and not from the base year. In the example taken earlier, the 13th month persistency will continue to be 70% but the 25th month persistency will be 85% as 60 of the 70 policies in the 13th month got renewed in the 25th month. Similarly, the 37th month persistency will be 83%. The challenge with the reducing balance method is that it can show firms with poor performance in better light. For instance, in the example above, despite losing half the policies by the third year, the persistency ratio stands at 83%. Insurers have used the reducing balance method to report persistency in the past and despite IRDAI standardizing that the calculation should only be on cumulative balance basis, some insurers continue to report it on a reducing balance basis. For instance, insurers such as Canara HSBC Oriental Life Insurance Co. Ltd and Shriram Life Insurance Co. Ltd have reported their persistency numbers on a reducing balance basis.

Life insurance persistency in India is acutely low and is clearly hurting life insurance companies. The influencers of persistency rate are all the three stakeholders: life insurers, agents, and customers. Greater digitization of the entire sales process can enhance customer experiences while also allowing effective monitoring of agents and other sales channels. This trend towards a richer customer experience and an assisted self-service model is seen in insurance markets around the world and it is arriving in India too. There also needs to be greater emphasis on training of employees and agents so they become financial or risk advisers for customers rather than just sellers Insurers can enhance the understanding past insurance behaviour of customers through a unified view of customer risk profiles, which is possible only if life insurers share data amongst themselves. There’s an opportunity to use advanced analytics to identify customer life-stages and thereby their insurance needs. This will help in pitching the right products to customers, identifying policy lapsation patterns using predictive modelling and surrogate data like credit scores. The Indian life insurance industry is increasingly becoming aware of this persistency malaise and efforts are moving towards collaboration, and smart use of technology-driven solutions. However greater efforts are required to bring cooperation and data consistency amongst insurers. The fundamental cause of the low persistency rate is that individuals still largely perceive life insurance as a tax-saving investment instruments and not as a financial protection tool. A large chunk of life insurance is sold in the last quarter of every financial year. This is the period when tax assessors rush to make investments to reduce tax liabilities. All the three stakeholders suffer losses from the current situation: insurers do not make profits on customers who decide to lapse policies within 6 to 7 years. Customers lose money if they do not persist with their policies long enough, with the entire investment lost if policies are persisted for less than 2 years. The focus of the agents on the high upfront commissions makes them lose out on opportunities of deepening relationships with customers. The root causes of low or declining persistency includes poor unit-linked insurance product performance, mis-selling by agents, poor customer service at the call centre, inadequate customer contact information and lack of robust renewal and collection processes.

One of the key drivers of profitability in life insurance is “persistency” of the existing base of policyholders, a metric that reflects the proportion of policies that continue to generate renewal premiums. Life insurers get new business after spending heavily on marketing and business development and on payment of higher first year commissions. This essentially means the upfront cost of acquiring new customers is very high. For the insurers, the impact of policy lapses is much wider. The lower the persistency ratio, the higher is the operating expense ratio. The operating expense ratio for most life insurers is in double digits. The key to sustainable profitability of life insurers is in reducing their operating expense ratios to low single digits. Smart customer handling is vital to improving the customer relationship and to understanding their propensity to lapse, based on their economic profile, risk identification, life-stage and other factors. The problem of low persistency is deeply entrenched and requires addressing product design, customer relationship management, and agents’ selling practices. More needs to be done to convey to consumers the important protection element of policies. Many efforts have been made to improve persistency. IRDAI has been trying to regulate front-loaded commissions and mandate a protection component, while the insurers have constantly been trying to improve their direct connection with customers. A recent consumer study conducted by LexisNexis Risk Solutions has shown that a large majority of customers (76%) depend on agents to learn about life insurance products before taking a decision. Just over one-third of consumers who participated in the study said they carry out a great amount of research before purchasing life insurance. This suggests a low awareness about life insurance and its purpose, and a need to strengthen the agency relationship and other sales channels. Improving persistency benefits everyone—policyholders, insurance agents, employees and shareholders.

REFERENCES:

  1. https://www.livemint.com/Money/5fIh4IrUV4zsj9H5s5UJwI/Why-are-life-insurance
  2. https://www.financialexpress.com/industry/check-persistency-ratio-before-buyin
  3. A Consumer Study by Lexis Nexis Risk Solutions
  4. Newspapers & Journals
  5. IRDAI Annual Report 2016-17
  6. GIC Yearbook 2017

Author

JAGENDRA KUMAR

Ex. CEO, Pearl Insurance Brokers

71/143, “Ramashram” Paramhans Marg,

Mansarovar, JAIPUR-302020