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2. personal finance
3. insurance

The Definitive Guide for Improving
Insurance Persistency in India
Customer retention is critical to
any insurance business – as
important as new policy sales.
While new policy sales are often
achieved through expensive
marketing
and
business
development costs, retaining
existing customers offers a more
profitable avenue.
The persistency ratio broadly
measures customer retention by
a life insurance company
calculated basis the percentage
of policyholders paying renewal
premiums at the end of one year,
or more years depending on the
tenure of the policy.
Persistency ratio has been a
concern for life insurers in India.
Even reporting of persistency
ratio numbers has been debated
upon.
1
13th month Persistency in India
To remove ambiguities in reporting persistency across life insurers, the
sector regulator, IRDAI, recently made changes to the norms for such
disclosures and put in place a standard formula to be followed by all life
insurers in reporting their 13
th
month persistency ratios. The table
below is the persistency ratio as per Public Disclosure reports by various
life insurers.
Low persistency ratio results in increased pressure on revenue and
reduced profitability. While life insurance companies have taken various
initiatives to reduce lapsation rates, the problem remains deep-rooted
with no quick fix solution. It is a complex issue dictated by a combination
of factors. Some of these include the macroeconomic environment,
product design, policy size, age and gender of policyholder at time of
purchase, mode and method of payment, policy duration, interaction
with the insurer, relationship with the agent, and current life value of the
policyholder.
The table below indicates that Persistency in India on an average is in the band of 50% - 70% which is far below
80% - 90% of their Asian peers.
Company
Aegon Religare
Persistency Ratio based on no. of
policies (for 13th month)
Persistency Ratio based on premium (for
13th month)
FY 12-13
FY 13-14
FY 12-13
FY 13-14
53%
70%
53%
55%
Aviva
58%
56%
58%
61%
Bajaj
49%
-
60%
62%
Bharti AXA Life
Insurance
Birla Sun Life
45%
-
56%
63%
49%
-
60%
81%
Canara HSBC
65%
-
75%
69%
DHFL
44%
41%
46%
45%
Edelweiss
46%
-
57%
56%
Exide
56%
-
65%
66%
Future Generali
40%
-
40%
42%
HDFC Life
69%
-
76%
69%
ICICI Prudential
67%
66%
72%
72%
IDBI Fedral
71%
71%
75%
78%
IndiaFirst Life
65%
65%
65%
65%
Kotak
64%
-
66%
82%
LIC Of India
82%
76%
67%
59%
Max
70%
-
77%
76%
PNB MetLife
71%
-
44%
57%
Reliance
62%
-
54%
56%
Sahara
57%
-
-
-
SBI Life Insurance
67%
66%
76%
72%
Shriram
30%
-
53%
49%
SUD Life
46%
43%
51%
50%
TATA – AIA
55%
54%
65%
71%
Data Source : Public Disclosure Reports on websites of Life Insurers in India
2
Factors that impact lapsation
There are several factors that lead to policy lapsation. All or some of these could be impacting persistency of a life
insurer at any given point of time.
The major factors that impact persistency of life insurance policies, as per work done by
Aureus Analytics in this area, include:
1. Policy Returns (ROI) promised at time of sale versus actual returns received by policyholder
2. Poor need gap assessment at the time of sale
3. Customer service and complaints management experience
4. Churning of channels
5. New product options
6. Ignorance of policyholder specifically on policy terms and conditions
7. Lack of adequate checks at time of financial underwriting
8. Financial crisis of policyholder or adverse market performance
The role of the sales person in life insurance business has always remained key in emerging markets; and accordingly,
it would not be out of place to look at various aspects of business wherein the distributor can play an important part in
arresting the discontinuance of policy contracts. One gets to hear very often that a policyholder has discontinued
payment of premium in dissatisfaction as he or she was sold the wrong product different from what was explained at
the time of entering into the contract.
Impact of lapsation In addition to the insurer, policy lapse impacts multiple other stakeholders as well:
Policy lapse affects the customers in three ways:
Customer
Insurers
Intermediaries
a. On lapse, policyholder loses the insurance coverage and more often than not, the insuranceneed is
acute at the times of lapse (one example is where the insured is out of work due to illness and hence
unable to pay premiums).
b. Customer get a reduced return if any; from the lapsed policy as discount factors tend to get applied
to the paid-up value.
c. As a class, customers will be affected by higher lapse rates as the cost gets passed on to them by way
of higher premiums (in future product pricing) or lower bonuses
Insurers do provide for policy lapses even while designing the policy. The challenge is to accurately
predict the lapse rate for a particular product and for a particular block of policies. For fixed premium
policies, insurer actuaries have to be accurate as possible. If lapse rates are higher than predicted,
insurer stands the risk of losing his margins.
Reducing policy lapse and increasing persistency benefits the field force a lot. If a customer lapses a
policy, not only does the agent lose his renewal commissions, it also becomes tough to sell another
policy to that customer as the losses on his first policy would have created a negative customer
perception.
3
Suggestions to counter Policy Lapsation
The Indian Life Insurance market can therefore be said to operate in a very ordinary persistency range as an industry. To
leapfrog from this level of persistency to that of other Asian markets such as Singapore, which has a 99% persistency,
the following key areas need to be addressed:
1
2
3
4
Regularizing the sales
Ensuring the customer
Alignment of product design
Perceived Present values
process;
has
to a typical Indian person’s
of insurance contracts
life
are not controllable after
digitization
a
better
and monitoring of the
understanding
sourcing channels by
product nature. If the
factors which impact policy
issue.
the insurer. This will
customer understands a
renewal
paying
feature design has to
also help in providing
product well, it will be
ability – education expenses,
take care of embedding
c o n t i n u o u s
that much easier to map
marriage
and
features which get high
knowledge building of
the needs gap. And the
retirement
be
returns. The popularity
the existing field force
realization
addressed via
so
customer of his needs
design. This would yield in
a pointer to this. Better
that
better
positioning
that
target
the
exact
segment
a
the
of
by
product
the
the
is
cycle.
Time
premium
bound
expenses,
–
should
product
prediction
Rather
product
of unit linked products is
of
of
the
product is designed
meeting, will ensure that
“in-danger-of-lapse” policies
product can mitigate the
for and should be
the customer keeps the
and result in sharper focus
effect of return rates on
instructed to sell only
policy in force.
on renewing them.
lapse rates.
to them.
AUPERA from Aureus
The need to address each of the above aspects are to a great extent appreciated by Life Insurers. However the key
disconnect occurs in using the underlying information effectively and in real time. Data analytics, specifically that which
incorporates both structured and unstructured data and combine customer and distribution level interaction has the
potential to impact persistency. AUPERA from Aureus is an advanced persistency control and management framework
which leverage complex algorithms to arrest lapsation significantly by addressing underlying customer and product
issues. Based on policy risk scoring, AUPERA helps insurers reach out to ‘ about to lapse’ customers beforehand and
initiate retention campaigns.
For a demo of AUPERA, contact us now.