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JANUARY 2018GIC ReNEWS

01

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Newsletter of GIC Re

JANUARY 2018

Global Reinsurance Solutions

Reinsurance market is going through a challenging phase in its evolution. On the supply side alternative capital is getting increasingly integrated with the traditional capital sources and thus offering a threat as well as an opportunity to reinsurers-threat to risk

carriers who do not tweak their business models in response to higher supply of capital and opportunity to those who integrate these cheaper capital sources in their business models. 2017 catastrophes will test the alternative capital since this is their first brush with sizable catastrophe activity. Technicalities and fine print will kick in and it would be interesting to see how this capacity modulates its approach. Demand side does not really offer any bailout with nominal growth.

It can be a sign of maturity of the market when premium does not see significant variations post loss events and benign period of loss activity. 1/1 renewal in the new year show quite muted increase in rate increases, essentially for those clients whose programme bore the brunt of catastrophes rather than across the board increases. This is also in line with equity demanding that risk is spread and the burden shared among homogenous category of risks, viz. cat exposed portfolios rather than spreading it over other categories as well.

Stress on the (re)insurance sector from record loss events also forces it to re-evaluate its practices and procedures, assumptions and algorithms and search for more productivity from its industry value proposition. This is where technology has a major role to play. Quite a few of the problems that were quite intractable have become increasingly amenable to resolution thanks to technology. In this regard, the blockchain technology offers tremendous promise, inter alia, for addressing moral hazard. Technology is certainly bringing in more efficiencies in claims handling with significant potential for savings. Technology has always been deployed for this but emerging economies provide new possibilities. It is encouraging that Indian market has taken steps to utilise blockchain technology.

There is some parallel between evolution of Enterprise Risk Management and reinsurance. With price cycles getting muted and competition hotting up, contribution of ERM in enhancing risk management capabilities and as a strategic tool will only increase. Companies who have capital events from 2017 catastrophes would need to look more closely at their ERM function. With significant variations in loss estimates among modelling agencies, modelling capabilities will be under focus again. Catastrophes, given their peculiarities and complexities, continue to challenge three decades old modelling industry. The issue features an article on catastrophe modelling.

Indian insurance sector is entering a new phase of consolidation and players going public with a spate of initial public offer (IPO) of share capital. With one more set of new entrants, market will continue to present competitive challenges. Greater segmentation and niche focus can be expected to emerge and deepen. Product design and customer service will differentiate players. With foreign reinsurer branches expected to scale up their operations on the back of licences acquired in 2017, reinsurance can be expected to see some more activity. GIC Re took public avatar with its IPO, coming a full circle with its birth at the very centre of industry nationalisation. Having scaled two ranks to 12th in 2016-17 among the largest global reinsurers, GIC Re is on the verge of entering the top 10 on the back of handsome growth in 2017-18. Half yearly results were quite promising.

India story is unfolding at its own momentum against the backdrop of recovering global economic climate. Amidst global headwinds, Government has persisted with thrust on reforms, geared more for long-term than short-term. After a long wait and lot of vexation, global ratings agency Moody’s revised the country’s sovereign rating to Baa2 from Baa3 - its first upgrade in almost 14 years - on the back of a series of economic reforms, including demonetization, rollout of the goods and services tax and 30 ranks jump in ease of doing business. The revised rating, the highest since the 1991 reforms, can be considered a belated acknowledgement of India’s potential and creditworthiness. Rating methodologies and role played by rating agencies come under focus from time to time. An article in the issue critically looks at the conundrum of sovereign credit ratings. Happy reading.

- Hitesh Joshi

CMD Mrs Alice G Vaidyan lighting the lamp at the listing ceremony held on 25th October 2018 at NSE. On the dais are Mr Vikram Limaye (NSE), Mrs Usha Sangwan (MD, LIC), Sanjay Sharma (Deutsche Equities), Abhijit Vaidya (Kotak Mahindra).

CMD, Mrs Alice G Vaidyan speaking at the Economic Times - 4th Insurance Summit 2017 held in Mumbai - 11th December 2017.

Asia Insurance Post Event held on 19th December 2017 at Taj President. CMD, Mrs Alice G Vaidyan flanked by Mr Rajni Shah (L), Mr P J Joseph, IRDAI Member Non-Life & Mr G Srinivasan, CMD, New India Assurance Co Ltd.

CMD, Mrs Alice G Vaidyan and Director & GM Mr Y Ramulu flanked by other officials of GIC Re at the SIRC event held in November 2017.

l Abacus l Industry News l Reserved Musings l Risk Feature

l Finance Feature l Post - Data l Public Concern l Family Additions

02 www.gicofindia.com


A very Happy New Year 2018 to all

readers. May the new year bring

good health and prosperity to all.

I’d like to begin this issue with a few lines

by the poet Walt Whitman, “O Captain! my

Captain! our fearful trip is done, the ship has

weather’d every rack, the prize we sought

is won, the port is near, the bells I hear, the

people all exulting”.

Many congratulations to the GIC Re family

on the Corporation’s Initial Public Offering.

With an issue size of over ` 11,000 crore,

our IPO is the third largest ever in India and

largest ever in the country’s financial services

industry including the (re)insurance space.

Over the course of the many international

and domestic roadshows I have undertaken,

I have witnessed unparalleled interest in

our IPO amongst all investor. It is a matter

of immense pride as our Corporation has

received due public recognition for its stellar

performance over the year. Kudos to the GIC

Re family, it is solely due to our continuing

effort and cooperation that the IPO has been

highly successful. Many GICians must now

also be part owners of the corporation. I

congratulate you on your decision to invest

in your own future and assure you that the

future is bright. At the same time, I implore

you to keep up the good work and soldier

on with the same solidarity that you have

displayed over the year. In the process, you

will create value not just for our shareholders

but also for your own selves.

2017 has been a very eventful year for the

Corporation. Our half-yearly financial results

continue to be highly encouraging. GIC Re

continues to traverse the strong growth

trajectory that we have been charting over

the last few years. The numbers speak for

themselves. We achieved 51% growth in

our Gross Premium and 89% growth in

Profit After Tax over the same period of the

previous FY. Very heartening figures indeed

and I expect much of the same in the next FY.

We ascended two spots in the global reinsurer

ranking list to 12th position in 2017. And I am

very optimistic that we will enter the top 10

list by virtue of our strong performance in FY

2017-18. India is one of the brightest spots

on the global economic horizon today. With

consistent 7% plus growth in its economy

over the last few years, much of the growth

has concomitantly, found its way into the

insurance and reinsurance sector and will

continue to do so.

In 2017, GIC Re was entrusted with the

responsibility of functioning as the Technical

Support Unit for the Pradhan Mantri Fasal

Bima Yojana (PMFBY) by the Government

of India. It is a high honour for us indeed,

as it implies that GIC Re will serve as a

repository of data, will assist insurers in loss

cost assessment and actuarial pricing of

risks. GIC Re has for all practical purposes,

been anointed as a valued advisor to the

Government of India as far as PMFBY is

concerned.

We expanded our physical presence to the

GIFT City IFSC in Ahmedabad in April 2017.

This is a reflection of our belief in its potential

as a financial services powerhouse of the

future. We intend to strengthen our IFSC

Insurance Office (IIO) established there in

terms of both staff and resources, so that it

can achieve the objectives we have set for it.

GIC Re got its fair share of public recognition

in the form of multiple industry awards.

We were awarded by ASSOCHAM, SKOCH

Group, Dun and Bradstreet and The Maritime

Standard Organisation for the stellar work

we have been doing in the reinsurance space

over the year.

Moving on to the most recent development,

GIC Re was accorded in-principle approval

to establish a syndicate at Lloyd’s of London.

Lloyd’s is a veritable Mecca for insurance

and reinsurance and the approval is indeed

a great acknowledgment of GIC Re’s profile

as a global reinsurer of repute. The syndicate

will enhance our diversification efforts as

we are granted access to hitherto untapped

sources of business and enable us to deploy

our capital more efficiently.

There is much in store in 2018. India is

significantly under-penetrated in terms

of insurance. With improving disposable

incomes and financial literacy and ever-

increasing adoption of technology, the

Indian populace is expected to take to

insurance in a big way, which will reflect in

the fortunes of reinsurers as well. We can

expect a universal health scheme in the

near future from the Government of India

on the lines of the PMFBY. This will have a

transformative effect on the prospects of

the previously unprotected citizenry. The

insurance industry is expected to churn

out many more IPOs in 2018. Adoption of

technology across all aspects of the value

chain is expected to increase manifold as

well.

Wishing you the best in all your endeavours.

ulu

CMD SPEAKS

From CMD's DeskAlice G. Vaidyan

GIC Re continues to traverse the strong growth trajectory that we have been charting over the last few years. The

numbers speak for themselves. We achieved 51% growth in our Gross Premium and 89%

growth in Profit After Tax over the same period of the

previous FY.

03www.gicofindia.com


GIC Re declared a record dividend of ` 1002 crores for the

year 2016-17 which is the highest in the history of the

Corporation.

The financial results of the Corporation declared for the half

year ended 30th September 2017 showed a healthy growth

with premium increase of 51.4 % year on year with a gross

premium of ` 24,404.37 crores as against ` 16,118.08 crores

declared in September 2016. The premium split between the

domestic and the overseas business was ` 19,227.35 crores and

` 5177.02 crores respectively.

Corporation’s profit before tax for the half year ended on

30th September 2017 was ` 2309.07 crores and profit after tax was

` 1809.23 crores. The Corporation’s assets as on 30.09.2017 was

` 107,034.55 crores.

The net worth of the Corporation stood at ` 18,549.92 crores.

ulu

Financial Results

CMD, Mrs Alice G Vaidyan presenting the Dividend Cheque for an amount of `1002 crore for the fiscal 2016-17 to the Hon’ble Finance Minister, Mr Arun Jaitley. Standing besides CMD is Director & GM, Mr Segar Sampathkumar, Mr Rajiv Kumar, Secretary (DFS) and General Manager and Mr VC Jain (standing left to right).

ABACUS

Gross Premium ` 33,585.4 crores

Total Assets ` 94,948.6 crores

Net Worth (with fair value

change account) ` 47,982.9 crores

Profit after tax ` 3,127.7 crores

Gross Premium ` 18,435.8 crores

Total Assets ` 79,732.6 crores

Net Worth (with fair value

change account) ` 38,280.7 crores

Profit after tax ` 32,848.4 crores

31.03.2017 31.03.2016



Deciphering Nature’s Evil Designs - The Model Way

Catastrophe modeling is a risk

management tool that uses

technology to help insurers

and reinsurers as well as business and

government agencies better assess the

potential losses caused by natural and

man-made catastrophes and their frequency

of occurrence. Catastrophe models combine

available historical disaster information

with current demographic, infrastructural,

scientific and financial data to determine the

potential cost of catastrophes for a specified

geographic area. The models use these

vast databases of information to simulate

the physical characteristics of potential

catastrophes and project their effects on

both residential and commercial properties.

All major natural hazards such as hurricanes,

earthquakes, winter storms, tornadoes,

hailstorms and floods are modeled. Even

efforts are on to model and financially

quantify risks associated with manmade

events like Terrorism.

The process of developing catastrophe

models is quite complex and utilizes skills

of experts in the fields ofmeteorology,

seismology, geology, engineering,

mathematics, actuarial science, decision

scientists and statistics. The results of

these models are of critical importance for

insurance industry and can be used at various

stages right from designing, formulating and

pricing an insurance product to critically

examining the product during policy period

and finally for undertaking analysis after any

loss is encountered.

The modeling process evolved in the late

1980s as companies became increasingly

aware of their exposure to catastrophic

risks. After Hurricane Andrew in 1992 and

the Northridge earthquake in 1994, the use

of catastrophe models gained momentum

as these two earthquakes took entire

industry by bitter surprise and consequently

companies strived to analyze their exposure

more accurately so as to write and price

for natural catastrophe adequately. The

advancement of catastrophe modeling can

also be attributed to quantuml leaps made

in the field of computing since without these

advances modelling could not really have

taken off.

Modeling is all about the data and depends

on the information given to it. The quality,

accuracy and quantum of data is a big

factor that decides upon the quality of the

modelled output. For example, differences

in how buildings in a similar location are

constructed may respond to the same event

differently as for instance a masonry building

is likely to fare better in a windstorm than

one made of wood. Similarly, differences

in data pertaining to building types, age of

the structure, its size, and occupancy may

produce different loss levels. Therefore, it

becomes rather important to understand

broadly the process and procedure involved

in catastrophe modelling.

Catastrophe Modelling process may on broad

basis be divided into three phases- Event

occurrence- Damage – Loss assessment.

The first phase is meteorologically or

peril driven and is associated with factors

such as storm path, its intensity, landfall

probabilities, minimum central pressure,

land friction, seismicity of the area, distance

of the region from equator and its proximity

to tropics etc. Second phase applies Data

Engineering methodologies to predict

damage by considering the demographic

features, characteristics of property in the

area, considering vulnerability functions

such as building type, construction, usage

etc. The third phase is associated more with

insurance sector as it produces estimates of

values at risk and loss data for risk carriers by

taking into account the insured properties

in affected area, applying deductibles

and re-insurance programme layering.

With improvement in technologies and

advancement of knowledge in various

fields of science and with learnings gained

out of various cat events in recent past, the

modelling algorithms constantly finetuned

and the modelled outputs have become

more reliable. Each cat event leads to critical

evaluation of the model effectiveness.

All models produce data in the form of tables.

Models operate in two ways: probabilistically

- to estimate the range of potential

catastrophes and their corresponding losses,

and deterministically - to estimate the losses

from a single hypothetical or historical

catastrophe.

When running a probabilistic model, the

output is either a probabilistic loss distribution

or a set of events that could be used to create

a loss distribution. Probable maximum losses

(PMLs), also sometimes called Exceedance

Probability (EP), and annual average losses

(AALs) are calculated from these loss

distributions. When running a deterministic

model, losses caused by a specific event such

as Hurricane Katrina or Nepal earthquake,

are calculated and analyzed. Outputs of

typical importance in Probabilistic model

are Exceedance Probability, return period,

Average Annual Loss. EP is the probability

that a loss will exceed a certain amount

in a year. It is displayed as a curve with the

losses running along the X-axis, and the

exceedance probability running along the

Y-axis. It is further divided into two namely

Aggregate Exceedance Probability (AEP)

and Occurrence Exceedance Probability

(OEP). The AEP is the probability that the

associated loss level will be exceeded by

the aggregated losses in any given year

and is used when the insurance program is

written on an aggregate basis. The OEP is

the probability that the associated loss level

will be exceeded by any event in any given

year. It is used when the insurance program

is written on an occurrence basis or when the

loss associated with one event is important.

These two results help in designing the

program structure, as modeling can be

performed on each individual layer as well

as on overall program. These results are also

helpful in analyzing various options such as

limits of self-insuring layers or transferring

risk to various insurers where these limits

are breached. Another important output

is Annual average loss (AAL) which is the

average loss of all modeled events, weighted

by their probability of annual occurrence.

This helps insurers determine the minimum

annual charge that would need to be

collected to fund for the expected loss. This is

RISK FEATURE



often referred to as the “technical premium”.

Insurers often use a multiple of this figure

to determine the actual annual premium

charged. In an EP curve, AAL corresponds

to the area underneath the curve which

represents the average expected losses

that do not exceed the norm. If we compare

one company’s AAL for earthquake and

windstorm perils versus the actual premium

paid with that of another, it can help one to

determine how well priced is their program

overall. However, the results may not be

fully reflective of actual risk exposure due to

various known or unknown factor. Therefore,

a Coefficient of Variation - CV is always

employed. CV measures the size or degree

of variation of each set of damage outcomes

in estimation. Mathematically, the CV is the

ratio of the standard deviation of the losses

over the mean of the possible losses. This is

important because damage estimates with

high variation, and therefore a high CV, will be

more volatile than an estimate with a low CV.

The modelled output for a property against

a particular risk will behave unexpectedly if

the property’s characteristics were modeled

with high volatility data instead of a data set

with more realistic variation. These output

figures may be used in different possible

ways with different sets of permutation

and combination to arrive at the most

complete picture possible so that insurance

companies can determine how much loss

they could sustain over a period of time,

how to price products to balance their own

and the market needs and potential costs

and how much risk they should transfer to

reinsurance companies based on attendant

capital requirements.

The accuracy of modelled output depends

primarily on the set of input data. As is said in

information technology domain, garbage-in-

garbage-out. Though the methodology used

in data mining process and the assumptions

made also affect the data output, but data

entries made with respect to any of the

input data such as those pertaining to

meteorological features associated with a

natural risk or the geographical features of

the region affected or geocoding of the area

or insurance related data, all of which may

be considered as primary set of input data,

are the most critical parameter. It is precisely

these parameters the variation in which can

produce widely divergent results. Another

such key element of uncertainty is Non-

modelled losses. Non-modelled losses can

result from regions or perils not included in

the modelling assessment or the risks that are

not considered by a model or some missing

exposures. The key learning out of some of

the biggest historical cat events serves as

testimony to this. For example, Hurricane

Wilma of 2005 which was the most intense

tropical cyclone ever recorded in the Atlantic

basin, as well as the most intense recorded

in the western hemisphere until Hurricane

Patricia in 2015, showed us that the extent to

which various cat modelers had considered

the effect of tree damage on properties was

not sufficient. Similarly, Hurricane Ike of 2008

showed us that storms can maintain strength

further inland than previously thought.

Apart from the primary set of input data,

another cause of potential uncertainty

may be non-inclusion of correlation and

dependency factor between different class

of businesses in an area or between different

department in a big organization. This of

course relates to how modelling is deployed

by any entity. Few examples may be cited

here to support the point. For instance, lack

of correlation analysis between classes of

business in the World Trade Centre attacks

and business interruption implications of

clustered industries in the 2011 Thai floods.

In such cases relying solely on modelled

data and cat modelling techniques may

lead to business decisions being made on

an incomplete view of risk. These elements

of uncertainty help us in understanding

why there are huge differences between

prognosticated and post event loss

assessment value estimates projected by

various risk modeler. As for example, RMS,

a leading risk modeler worldwide, had

estimated insured loss from Hurricane

Harvey between $25 to $35 billion, with an

upper bound of $40 billion associated with

wind, storm surge, and inland flood damage,

across Texas and Louisiana only including

losses coming out of National Flood

Insurance Program of $7 to $10 billion. While

AIR, another big risk modeler, had estimated

industry insured losses from wind, flood, and

storm surge combined at around USD 10

billion excluding losses from the National

Flood Insurance Program (NFIP). These

variations indicate different underlying data

sets, assumptions and algorithms. Post event

once the actual loss results are available,

required changes in these constituents of

modelling can be evaluated and recalibrated.

Catastrophe Modelling, over the years

have come long way and have overcome

many of the glitches and shortcomings

and have redefined the approach to loss

assesments. However uncertainty and errors

will always be associated with models. It

is also important to recognize the fact that

there is no one-size fits all approach when

it comes to catastrophe modeling. There

are a number of different methodological

approaches to catastrophe modeling, each

using somewhat different assumptions, data

inputs and computational algorithms. Also

recent developments in this relatively young

field of science are quite encouraging and

innovative. One such attempt made in this

regard is Open Catastrophe Modelling by

which an effort to create and disseminate

open multi-hazard cat risk modeling tools

initiated by the Alliance for Global Open Risk

Analysis (AGORA). AGORA is conceived as a

nonprofit, international virtual organization

created to promote and coordinate

development of open-source risk software

and methodologies to perform end-to-end

risk modeling. End-to-end refers to modeling

the occurrence of hazardous events,

site effects, physical damage to the built

environment, and economic and human

impacts. In 2007, the Alliance released initial

design of the Open-source Risk software

and timeline for future developments.

Important developments are USGS National

Seismic Hazard Mapping effort, which has

produced freely available hazard software.

Another is Open Risk, a set of methodologies

and object-oriented, open-source software

for conducting multi-hazard risk analysis

developed collaboratively by Caltech, USGS,

Southern California Earthquake Centre

(SCEC) and Kyoto University.

Catastrophe modeling allows the world to

predict and accordingly manage damage

resulting from the events. As models will

improve, so will our ability to face these

catastrophes and minimize the negative

effects in an efficient and cost-effective way.

Catastrophe modeling is one of many tools

in the risk management toolbox available

to insurers and reinsurers as they look to

predict future losses and better manage and

prepare for disasters in the years to come.

- Anand Pratap Singh Yadav

ulu

RISK FEATURE



Sovereign Rating - Poser, Puzzle and the Conundrum

Debt, we've learned, is the match that

lights the fire of every crisis. Every crisis

has its own set of villains - pick your

favorite: bankers, regulators, central bankers,

politicians, overzealous consumers, credit

rating agencies - but all require one similar

ingredient to create a true crisis: too much

leverage. - Andrew Ross Sorkin, an American

journalist and financial columnist for The New

York Times and author of bestselling book

Too Big to Fail. One would normally expect a

rating agency to understand leverage better

than others and raise red flag but this hope

was belied during global financial crisis. In

fact, they were instrumental in promoting

the leverage in the financial system.

Sovereign rating actions invite a lot of press.

These are rating changes by credit rating

agencies. Last year in a sovereign rating

action Moody's (Credit Rating Agency)

downgraded China's Country/Sovereign

rating to A1 from Aa3 and changed outlook to

stable from negative. This downgrading was

attributed to the fact that China’s economy-

wide debt continued to rise as potential

growth slowed and the consequent growth

in contingent liabilities for the government

was likely to be slowed down.

While India another force to be reckoned

after ‘World Superpower’ China from Asia,

has been reaffirmed ‘BBB-’ sovereign rating

with a ‘Stable’ Outlook by Fitch Rating

Services. It has been observed that the

Indian government has been consistently

rolling out its ambitious reform agenda for

almost three years and remains committed

to continued reforms. A continued rise

in foreign direct investment (FDI) inflows

during April-September 2017 stood at US$

33.75 billion, shows that India is becoming

a more attractive destination for foreign

investors coupled with upcoming favorable

reforms to support & relaxation in FDI norms

for more FDI inflows in its latest Budget

and government's effort to improve ease of

doing business is yielding results.

Sovereign Rating or Sovereign Credit rating

of a country is simply called the credit rating

of that country. A Sovereign credit rating

gives investors an insight into the level of risk

associated with investing in that particular

country and the risk assessment is done

mainly on three broad categories of risk:

Economic, Political and Financial System Risk.

In a nutshell, Economic risk is the chance that

macroeconomic conditions like exchange

rates, government regulation, or political

stability will affect investment environment

in that concerned country. Political risk is the

risk an investment's returns could suffer as a

result of instability due to political changes

in a country. These changes may be in the

form of change in government, legislative

bodies, other foreign policy makers or

military control. Financial system risk is the

risk of collapse of an entire financial system

or entire market.

Obtaining a good sovereign credit rating is

usually essential for developing countries like

India in order to access affordable funding in

international capital markets. Currently it is

costlier for Indian corporates to access global

capital markets, due to low investment grade

sovereign rating (BBB- Fitch / Baa2Moody’s),

which in turn affects potential growth in the

competitive international market.

Despite this, as mentioned earlier, India

continues to be among the top ten

countries in terms of FDI inflows globally

and the fourth in developing Asia, as per

the World Investment Report 2017 by the

United Nations Conference for Trade and

Development (UNCTAD).

Also, to be noted that, India’s projected Real

GDP Growth Rate is 6.7% in 2017, as per IMF

(World Economic Outlook October 2017),

which is second highest among countries

across developing and developed nations

after China (6.8%), followed by Philippines

& Vietnam at 6.6% & 6.3% respectively. Even

with such a robust Real GDP Growth rate

Projection, India has been constantly rated

at a lower investment grade by prominent

International Rating agencies.

S&P Moody’s Fitch

BBB- Baa2 BBB-

Perhaps looking at the merit in India’s claim

for higher rating, Moody’s Investors Service in

November 2017 upgraded India’s sovereign

rating by a notch from the lowest investment

grade of Baa3 to Baa2, and changed the

outlook from stable to positive in a ringing

endorsement of the recent government’s

reforms policy. It’s the first upgrade of India’s

rating in 14 years.

Indian Finance Minister Mr. Arun Jaitley

said the upgrade was recognition and

endorsement that "a number of structural

reforms in the last three years have placed

India on a path of high trajectory growth,"

and also that "India continues to follow a

path of fiscal prudence which has brought

stability." Backing the reforms initiated

by the government in the last three years,

FINANCE FEATURE



and corroborating Finance Minister’s view

Moody’s said in a statement, “The decision

to upgrade the ratings is underpinned

by Moody’s expectation that continued

progress on economic and institutional

reforms will, over time, enhance India’s high

growth potential.” But it is worth watching

which other rating agencies follow suits and

when.

Prior to the rating upgradation in August

Mr. Kaushik Das chief India economist at

Deutsche Bank AG said “Apart from a change

in political leadership in 2014, the macro

landscape has also changed favourably

in the last four years, thanks to the bold

reform measures initiated by the respective

new governments” and there is a strong

argument that there is a genuine case for

rating agencies to consider giving a ratings

upgrade to India, or at least prepare the

ground by first raising the outlook to positive

(from stable), as an acknowledgement of the

positive changes that have taken place in

India since the 2013 ‘taper tantrum’ period. In

his report Mr. Das has also pointed out that

the Indian economy is far more resilient today,

with low inflation, high real interest rates,

large forex reserves, stable rupee and robust

growth outlook. Though banking sector NPA

resolution and fiscal consolidation remain a

work-in-progress, “but realistically each and

every emerging market economy will have

some areas of weakness at any given point

of time”.

The most important rating factors that may

determine the rating of a country are:

• InternationalTransactionspolicy

• MonetaryPolicy

• FiscalPolicy

• BusinessEnvironment

• Laborflexibility

• GovernmentStability

• SocialStability

• RegionalStability

• LegalSystem

• AssetQualityandaverageperformance

• Easeofdoingbusiness

In all these parameters India has a scope to

perform better than the World Average, and

the constant endeavor is reflected in the

30-spot jump in the World Bank Ease of doing

Business Ranking List in October 2017. In

‘Credit Probability of Default’ analysis by S&P

Global Market Intelligence (December 2017),

India fares moderately among the APAC

countries, which takes into consideration all

the key sectors of a country.

Fiscal deficit is considered to be among the

most important drivers of rating since it

shows government not being able to manage

its finances well. So, the question is how far is

Fiscal Deficit a deciding factor?One argument

is that the ideal fiscal deficit target of 3% of

GDP is a statistical outcome of the European

market experience which has served them

well, but not necessarily applicable to a

rapidly growing and a developing nation like

India. But then again, we are not far behind.

Fiscal deficit in fiscal 2017 was 3.5% of GDP

with approximately 40 basis point decrease

from the preceding fiscal reflecting the

government's commitment to the process of

fiscal consolidation.

In this respect, it is to note that, India’s

Government debt is well-bridled at 69.5%

of GDP (December 2016) with a consistent

reduction from a peak of 84% in 2003, and

currently eyeing ‘60% benchmark’ in 2017.

This 60% benchmarking is again debatable

as with the subsequent improvement of

Public debt to GDP ratio over the period

is not assuring any rating enhancement

and also considered inappropriate target

for a developing nation. Evidently there

are a number of countries which are rated

above India but have a significantly higher

government debt which is worsening over

time. Interestingly this fact has not affected

their respective rating.

So, what is the deciding factor? Fiscal deficit,

Debt to GDP ratio or FDI inflow? Or any other

macroeconomic factor? Definitive answers

are elusive and no clear pattern could be

zeroed down on from the past rating actions

in Asia or Europe or for that matter from the

other regions.

Inconsistency in the Rating agency results are

abundant and often allegedly competition

induced. Recent example is China’s Sovereign

rating downgrade by Moody’s, while Fitch

ratings has stuck to their decade old rating

and was spared the confusion of dialing

down its rating as per the current Chinese

economic scenario. Incidentally Moody’s

and S&P upgraded Beijing IOUs to the AA

territory in the last quarter of 2010. And this

rating action comes precariously almost one

and half years after Fitch Rating came up with

concerns on the rising corporate exposure

in the Chinese Banking Industry and its

long-term impact on the repaying ability of

corporate borrowers. This somehow exhibits

that Sovereign Rating is not always uniform

across the CRAs.

This observation begs for consideration of

auniversal parameter of Sovereign Credit

Rating, which needs to be voiced and

discussed in International forums. This issue

must be raised by Third World nations as they

are the most affected by such an ambiguous

system.

Credit rating agencies globally have attracted

strong criticism from time to time for various

reasons. Their role, or infact contribution to

the global financial crisis came under focus

and attracted scathing criticism from all

quarters. One principal criticism is the lack of

transparency in their rating methodologies.

Rating agencies have, to their credit, sought

to address concern through more disclosures

and sharing of information to be able to

be seen as transparent. However, there is

possibly need for more demystification.

Another important criticism and this goes to

the very raison detre of their existence and

utility to the market is that they have not

been able to predict impending financial

troubles. Rating actions have not been

going far enough into the future. In fact,

rating agencies have been perceived to be

acting too late to financial and economic

developments. This quite possibly applies

both to the sovereign ratings as well as

commercial entity ratings. Economic and

financial forecasting is a treacherous terrain.

Looking into the future is always uncertain

and fraught with risks of failure. But the very

utility of ratings is to provide an assurance,

however probabilistic or weak it maybe, so to

say, for the future, whatever may be the time

frame involved. Rating agencies need to

embrace this wholeheartedly – the question

is how far into the future they will look, how

will they assess what they see and most

importantly, how will they communicate

their findings to the users of ratings, who

may not be quite conversant with the lexicon

FINANCE FEATURE



and methodologies and their limitations.

One principle reason for reactive stance of

rating agencies is that they would like to base

their rating actions on “confirmed trend”. Just

offshoots of an emerging trend would not

easily propel an agency into rating action.

But then, if the action is based on confirmed

trend, how far does it have predictive value?

This is possibly the principal reason for Indian

sovereign rating not being quite upgraded

though among the financial and investing

community, India is certainly among the

bright spots globally. The disconnect

between the financial flows and rating

stance of agencies are something that needs

to be looked into with diligence.

One more parameter that rating agencies

usually look at while rating is the per capita

income. This creates certain advantages

for more prosperous countries to the

disadvantage of the emerging economies.

This also overlooks the fact that prosperous

countries are prosperous in the present and

their future may not be very bright while

emerging markets though less prosperous

have bright growth prospects.

In the paper Study of Sovereign Credit Rating

Determinants with Bayesian Approach, Melki,

Ftiti and Arab conclude that in pre-global

crisis period, exchange rate, per capita and

openness indicator are the sole significant

factors that explain sovereign ratings,

however, after the crisis period, GDP growth,

Governance indicators, debt per GDP, GDP

per capita and openness indicator appear to

exert a strong impact on rating assessment.

They are further scathing in observing that

their study implies the unstable behavior

of rating agencies and failure of rating

agencies to anticipate the crisis is result of

their methodology in selecting appropriate

weight of determinants of sovereign rating.

It seems that rating agencies have a lot

of ground to cover and it can begin with

proactive stance on the rating actions rather

than being “reactive”.

It's not a stretch to say the whole financial

industry revolves around the compass point of

the absolutely safe AAA rating. But the financial

crisis happened because AAA ratings stopped

being something that had to be earned and

turned into something that could be paid

for, said Matt Taibbi, American journalist and

author of several books including Griftopia:

Bubble Machines, Vampire Squids, and the

Long Con That Is Breaking America.

-Arka Kabasi & Hitesh Joshi

ulu

The year 2017 will be remembered for

the hurricane trio Harvey, Irma and

Maria and the havoc they wreaked

on both life and property in the affected

regions.It will go down on record as the year

of highest insured losses ever. The collective

insured losses inflicted by Hurricanes Harvey,

Irma and Maria, earthquake in Mexico and

other natural catastrophes across the world

have been estimated to be around US$ 135

billion. This is significantly higher than the

US$ 56 billion sustained in 2016 and the

2000-2016 average of US$ 51 billion.

Economic losses for the year have been

estimated to be US$ 330 billion, second

only to the US$ 354 billion recorded

in 2011. The glaring protection gap in

coverage is widely evident as only 41%

of the affected risks were insured in 2017.

This was the costliest hurricane season

on record having caused US$ 215 billion

worth of damage. The catastrophes have

largely been an earnings event for reinsurers

FINANCE FEATURE

rather than a capital event, since a large

portion of the losses was retained in the

primary market and alternative capital, in

the form of Insurance Linked Securities

(ILS) supplemented traditional reinsurer

capital in absorbing losses. It is estimated

that globalreinsurer capital was at about

US$ 600 billion on September 30, 2017. This

includes both traditional and alternative

capital, which stood at about US$ 518 billion

and US$ 82 billion respectively.

All the above was widely expected to result in

a strong increase in pricing of risks. However,

data emerging from January 2018 renewals

paints a somewhat subdued picture. In the

United States, pricing in the property class

of business has increased between 0-7.5%for

catastropheloss free risks and between

5-10% for catastrophe loss affected risks.

This is an indicator that instead of reinsurers

demanding an across-the-board increase in

prices, quotes were adapted to reflect the

loss experience of individual insurers. The fact

that pricing corrections have been generally

serene seems to strengthen previous

observations about localized and granular

outlookof the industry, rather than cyclical

forces impacting pricing at an aggregate

level. In addition, industry executives opine

that there is a lot of capital in the market

and there is a lot of competition for business

globally. So that may have been a factor

in lower than expected rate increases for

reinsurers as well.

The juggernaut that is the Indian insurance

industry continues to roll on at a brisk

pace. As of November 30, 2017, the general

insurance industry had recorded ` 96,107

crores in premium volume, a growth of 18%

over the same year-ago period. This growth

continues to be driven by the motor, health

and crop insurance segments with personal

accident segment recording strong growth

as well.The industry is all set to replicate this

strong growth in the rest of the financial year.

According to latest data released the general

INDUSTRY NEWS



insurance penetration in India increased to

1.05% as of March 2017 based on constant

prices. The life insurance industry recorded

` 1,38,524 crores as first year premium up

to December 31 2017. This was a growth of

18% over the same period of the previous

financial year.

The Pradhan Mantri Fasal Bima Yojana

(PMFBY) has witnessedstrong offtake in the

year 2017 as well. The Government of India

had allocated ` 10,701 crores (additional

` 1,701 crores by way of supplementary

grants) in its budget outlay for the financial

year 2016-17 in line with their objective of

covering 40% of gross cropped area in the

year. The scheme had generated ` 22,337

crores in crop insurance premium in the

Indian market in 2016-17. The Government

is contemplating a budget outlay of ` 13,000

crores for the scheme in its budget for fiscal

year 2018-19.

The year 2017 witnessed the entry of

new players like Acko General Insurance

Company, DHFL General Insurance,

Edelweiss General Insurance Company

Limited and Go Digit General Insurance.

2017 was a record year in terms of listing

activity for Indian insurance and reinsurance

companies which raised hugesums from the

capital markets. Out of the overall 36 main

board IPOs floated in the Indian market

in the year 2017 which altogether raised

approximately ` 67,147 crores, five were

from the (re)insurance industry - HDFC

Standard Life, The New India Assurance

Company, General Insurance Corporation

of India, SBI Life Insurance Company and

ICICI Lombard General Insurance Company.

These five companies raised approximately

` 43,424 crores from the capital markets in

aggregate. This comprises 65% of the total

capital raising through IPOs in calendar year

2017. This is a healthy sign for the Indian

insurance industry as it implies that the

industry is gaining traction in the investing

community in India and abroad. The year

2018 promises to be an exciting year as well

with more companies expected to tap the

capital markets. Reliance General Insurance

has already received approval from SEBI for

its IPO. The three public sector insurers –

National Insurance Company, United India

Insurance Company and Oriental Insurance

Company are expected to follow suit in 2018

as well.

Fifteen Indian insurers spanning life and

non-life segments have jointly started India’s

first blockchain project in the financial

services industry to help control costs for

running medical tests and evaluations, and

to ensure confidentiality and security of the

data collected from individuals. The concept

is based on distributed ledger technology

and will work on sharing of customer data

between companies based on the customer’s

consent. It will also help in fraud detection.

This initiative follows the world’s first marine

insurance blockchain platform launched

in 2017. The global blockchain platform

connects clients, brokers, insurers and third

parties to distributed common ledgers

that capture data about identities, risk and

exposures, and integrates this information

with insurance contracts. Insurers can use

this blockchain platform to gain efficiencies,

with increased transparency and reduced

manual data entry or reconciliation and

administration costs.

With India’s growing reputation as an

international insurance and reinsurance

centre, it has become a member of Global

Insurance Law Connect which is a formal

international alliance of independent

insurance law firms spanning four

continents. India is represented by Khaitan

Legal Associates. The alliance purports to

provide comprehensive legal advice to

industry participants across product lines

and geographies.

The Supreme Court of India, in 2017, has

ruled that the future prospects of the self-

employed and those with a fixed income

have to be taken into consideration in

computing the amount of compensation to

dependents in fatal motor accident cases.

This is a significant shift from the existing

compensation award practice, according to

which dependents of only those having a

permanent job with scope for increases in

salary are entitled to compensation based

on future prospects.

IRDAI has recently formed a working group

to examine the use of wearable and portable

devices in the insurance framework. The

group will evaluate how technological

INDUSTRY NEWS

advancements, particularly wearable and

portable devices, may be treated from in

terms of risk improvement, risk assessment

and utilisation of such devices as part of

policy design. It would also examine facets

that would affect pricing and formulate

a policy framework keeping in view the

interests of the policyholders. This is line with

global best practices ofoffering premium

discounts to policyholders who exercise and

share their activity data.

Indian general insurers have decided to

reduce their premiums in the ‘own damage’

segment by 5-20 per cent for customers

of private and commercial vehicles as the

new regulations of the IRDAI have led to

a reduction in the commission offered by

them to auto dealers.This would to an extent

indicate that market players believe that

motor third party premium is adequate. The

role of motor dealers has been recognised by

the regulator and they have been brought

under the regulatory purview. Motor dealers

can get registered as Motor Insurance

Service Providers (MISP), which will bring

ease in distribution and better service for the

customers. Insurers opine that this step has

the potential to usher in a differential pricing

regime, where customers with good claims

records will get reduction in the pricing and

vice versa.

IRDAI has called for Expressions of Interest

(EOIs) from consultancies and other

institutions for the implementation of the

Risk Based Capital (RBC) regime in India.

In September 2017, the regulator had

also constituted a 10-member steering

committee to implement the shift from

solvency to RBC regime. The proposed risk

based supervisory framework is for effective

and efficient monitoring and evaluation of

potential risks in the insurance sector.

The Reinsurance Expert Committee (REC)

appointed by the IRDAI submitted its

report in November 2017. Following up

on this, IRDAI has issued draft regulation

which is thrown open for comments from

stakeholders.

-Rahul Dayal

ulu



ALGEBRA OF BIG DATAD

ata is the Oil of the digital era, which is

driving the growth of “data economy”.

The prominence of data is more than

it ever was at the turn of this century. It is

the data which is driving competition and

innovation simultaneously as businesses

are becoming aware of how and when

to respond. The organisations which are

sensitive to algebra of data are able to sustain

competition and which didn’t, failed in a

heap as they failed to respond to dynamics

around them. Not only the trade which

has become globalised but all arithmetics

related to data collection, analysis, sharing is

increasingly becoming globalised through

digitalisation riding on the power of Internet,

making people more aware and conscious

for making informed choices. This has led

to increased competition and in order to

sustain in this competition – Innovation.

It is common knowledge that with advent

of smart technologies like smartphones,

automated systems employing AI, cloud

computing, Internet of Things (IoT),

information explosion is taking place

creating an issue of data relevancy. Data

relevancy to any business suggests only that

set of information is relevant which is capable

of being analysed computationally to

provide meaningful and actionable data and

information. This has brought prominence to

Big Data in today’s digital era transforming

trade economies into “data economies”.

Origins of Big DataIts origins are of keen interest. In 1944,

Wesleyan University librarian Fremont

Ryder stipulated that by 2040 Yale library

would have 200 million volumes because

of information explosion. In 1980, Oxford

English dictionary discovered that

Sociologist Charles Telly was the first person

to use the term Big Data in his article. Not far

in 1997, Michael Cox and David Ellsworth for

the first time in ACM paper used the term

Big Data. The concept of Big Data took the

flight in early part of 2000s, when Big Data

got identified with 3 V's as defined by analyst

Doug Laney :

Volume: Size is enormous.

Variety of data: Gathering of data by

applications goes beyond spreadsheets

and databases. The heterogeneity and

complexity increase as data is flying into

from heterogeneous and distributed

sources- both structured and unstructured.

Data is available in the form of emails,

photos, videos, audios etc. as a feeder stock

to analysis applications.

Velocity: The above two V's are meaningless

if data is not generated and processed in real

time to cater to demands. Here, comes the

speed.

Later Google astonished us in 2008 when

it claimed to have processed 20 Petabytes

(1 PB = 1015 bytes) of data in a single

day. In 2013, 4.4 Zettabytes (1 ZB = 1021

bytes) was produced by the Universe.

Presently, businesses have started building

and implementing Big Data technologies

such as in-memory technologies to take

advantage of Big Data. Insurance companies

especially Actuaries, Insurance marketers,

brokers require intelligent and sophisticated

softwares to model the data.

Now the question is what is Big Data? In

simple terms, it is extremely large data set that

may be analysed computationally to reveal

patterns, trends and associations. The trends,

patterns may relate to human behaviour

(Consumer behaviour), Catastrophe data

modelling, weather modelling etc.

As per OECD, Data-driven innovation forms

a key pillar in 21st century sources of

growth. The confluence of several trends,

including the increasing migration of socio-

economic activities to the Internet and

the decline in the cost of data collection,

storage and processing, are leading to the

generation and use of huge volumes of data

– commonly referred to as “big data”. These

large data sets are becoming a core asset

in the economy, fostering new industries,

processes and products and creating

significant competitive advantages.

A report published (2015) by the Lloyd’s of

London insurance and reinsurance market

concludes that by underpinning liability

catastrophe models with big data techniques,

opportunities could be found for the ILS

market to get more deeply into casualty

risks. The report further discusses the use

of innovative, technology and scientific

methodologies for analysing, understanding

and managing liability risk accumulations.

Risk Management is an intrinsic part of

functioning in financial institutions which

heavily rely on vast amount of data and data

models. Value at Risk (VaR) and Stressed Value

at Risk (SVaR) etc. are some of the methods

for risk evaluation. Simulation methods like

Monte Carlo simulation, Scenario analysis and

Sensitivity analysis, all require huge amount

of data and different types of modelling

techniques. Big Data innovations have the

potential to create robust, ‘parsimonious’

risk models. This would result into sensible

underwriting – allowing underwriting where

it makes sense.

The impact of Big Data analytics on (re)

insurance and other industries and legal

aspects related to Big Data including

concerns about data privacy, source of

market power leading to abuse etc. will be

spelt out in the second part in the next issue

of the newsletter.

Big Data Economy

“Data is a precious thing and will last longer

than the systems themselves”, said Tim

Berners-Lee (Inventor of the World Wide

Web).

Economies worldwide are becoming smarter,

leaner connecting through Digital Highways,

which has allowed for the proliferation of

unlimited amounts of data travelling and

creating an invisible world where data can

grow unconfined by laws of physics. Data are

becoming a new raw material of business, a

new factor of production. However, Data in

itself is of no use unless value can be created

from it and here Big Data analytics involving

technologies have come into picture turning

trade economies into Data Economies.

Recently, Google Earth helped in finding

‘lost’ gates in Saudi Arabian desert creating

an opportunity for Archaeologists, value

through Tourism in otherwise barren place.

POST-DATA



Foundation Daywho completed 25 years of service in the organization. The winners of Rangoli competition were also announced.

The next performance was a soulful rendition of Vande Mataram by Mr. Mehul Jaiswal, Mr. Siddharth Guha and Mr. Manish Tiwari in an Audio-Visual. This wasfrom the 1997 studio album by Indian musician A. R. Rahman.

Then began the musical journey with KK performing his Chart-topping songs to keep the audience rapt for a good hour and half. Krishnakumar Kunnath, popularly known as KK, is noted for his broad vocal range and is considered one of the most versatile singer in India. Some of the songs from the Chartbusters are Pal (Pal)/Tadap Tadap Ke Is Dil SE (Hum Dil De Chuke Sanam)/Koi Kahe Kehta Rahe (Dil Chahta Hai)/Tu Aashiqui Hai (Jhankaar Beats)/Hai Re Hai Re (Khushi)

How Google and other apps identify your

routine places you visit and try to offer

products, solutions to you at your nearby

places. Big data is being used to predict

earthquake and other natural hazards.

For instance, a company by the name One

Concern (figuring out how to apply data

science and machine learning to aid disaster

response) uses its web platform Seismic

Concern - collects data from every source on

the physical environment of a subscribing

city or county, including geography, soil

conditions, bodies of water, as well as details

about physical structures, including the

age of structures and how they have been

affected by previous earthquakes. After the

company’s algorithms are applied to the

data, the resulting map provides a reading

of which structures are likely to be damaged.

It is not difficult to imagine how this type

of functioning will help in Risk mitigation,

saving human costs in Risk inspection

surveys and speedy response to mitigate

damages. Data sharing can also be a revenue

generator.

In businesses, data access and exploitation

creates value in optimisation of value chains

in global manufacturing and services.

Adoption of ‘smart grid’ technologies is

generating volumes of data on energy and

resource consumption patterns that can

be used to improve energy and resource

efficiency (as per OECD). The public Sector

who is a data user can also be a key source of

data, which can generate benefits across the

economy. Therefore, there is no denying the

role of data in promoting innovation, growth

and well-being of economies. It is the data-

driven innovation which is key to survival of

economies in the future.

Data is the key to ‘Data’

Dr. Yemi Kale, Statistician-General of the

Federation / Chief Executive Officer National

Bureau of Statistics while delivering

speech at the 1st National Summit on Big

Data Economy said that the thing that

differentiates Big Data from the “regular data”

we were analyzing before, is that the tools

we use to collect, store and analyze it have

had to change to accommodate the increase

in size and complexity. With the latest tools

on the market, we no longer have to rely on

sampling. Instead, we can process datasets in

their entirety and gain a far more complete

picture of the world around us. With more

complex of technologies, the phenomena

of generation of data has increased with not

only human beings but also in businesses.

The fact is data is giving rise to new data and

the process of cycle is becoming rapid with

ever-growing new technologies because the

race is to capturing it faster and better in real

time and with minimal invasiveness.

With this, part 1 leaves you with the thoughts

of Gary King, Director of Harvard’s Institute

for Quantitative Social Science -

“It’s (Big Data) a revolution. We’re really

just getting under way. But the march of

quantification, made possible by enormous

new sources of data, will sweep through

academia, business and government. There

is no area that is going to be untouched.”

-Arpan Sharma

ulu

We celebrated our 46th GIC Re Foundation Day with gusto at Nehru Center, Worli with a musical extravaganza followed by Gala dinner. The evening, compered by Mr. Vikash Kumar and Ms. Deepti Atri, was declared open with CMD’s address followed by an Audio-Visual presentation recapitulating the year gone past.

CMD, Ms Vaidyan enunciated her appreciation for the overwhelming response from the employees to the IPO. She said it is the enthusiasm, and the belief in the future of the organization that is really encouraging. This is a journey to take pride in. We have accomplished a lot together during our first 46 years and empowered countless businesses and people to realize their full potential. But what matters most now is what we do next. Let us set off on a journey of change to become a truly great company and not just a big company. We need to come together to make this ambition a reality.

This gave way to felicitation, with a gold coin and memento, of those GICians

Aashaayen (Iqbal)/Tu Hi Meri Shab Hai (Gangster)/ O Meri Jaan (Life In A... Metro)/Zara Sa (Jannat), and many more. The audience had a gala time and grooved to the melodious rendition by KK.

After honouring the members of the band, the vote of thanks was then proposed by General Manager, Pauly Sukumar N.

The enthralled audience then proceeded for the sumptuous dinner to wrap up the memorable day.

- Deepti Atriulu

POST-DATA



GIC Re took public avatar through IPO

PUBLIC CONCERN

GIC Re was incorporated in 1972 as a wholly owned Government of India company. This changed when in

October 2017, it became the first Government owned (re)insurance company to list its shares on the Stock Exchange after an Initial Public Offer (IPO) which was the third largest IPO by amount of capital being raised in India.

GIC Re embarked upon its 10-month long IPO exercise in January 2017 when it received the Government of India advice about the approval of Cabinet Committee on Economic Affairs for listing of Government owned General Insurance companies. Following the advices of the Government of India, GIC Re got in touch with the Department of Investment and Public Asset Management (DIPAM) to familiarize itself and initiate the process for divestment of part of the shareholding of Government of India.

A committee comprising of officials of Ministry of Finance and DIPAM and senior executives of the Corporation, was constituted in March 2017 to consider and approve various phases and modalities for carrying out the IPO.

GIC Re has selected and appointed five Merchant Bankers as Book Running Lead Managers (BRLMs) with “Citigroup Global Markets India” as the left lead to assist the Corporation in obtaining necessary approvals and completing the IPO followed by listing of its shares on the Stock Exchanges. GIC Re also selected a domestic and an international legal counsel for the IPO. Simultaneously, BRLMs selected their domestic and international legal counsels for the IPO. The elaborate exercise also required appointing an Advertising Agency, Registrar, and the Bankers to the issue.

The IPO process formally commenced with the kick-off meeting of Senior Executives of the Corporation with BRLMs, Domestic and International Counsels and Auditors. The due diligence process was immediately started with the assistance of the Legal Counsels and was followed by sessions for drafting various chapters of DRHP. All departmental teams joined the due diligence & drafting process and assisted in collating, reviewing and contributing significantly large volume of information. Several rounds of meeting were held internally and along with intermediaries to ensure completion of tasks within the tight timelines. Regulatory approvals from IRDAI

and SEBI were required. Necessary alteration in the Memorandum and Articles of Association were made in compliance of the SEBI regulations and Stock Exchange listing requirements. This included consolidation of face value of equity shares to ` 5/-per share.

Equity shares of GIC Re were held historically in physical form by way of consolidated share certificates and complying with the extant requirements, entire share capital was converted into Dematerialized form.

The Corporation obtained government approvals for fresh issue of capital of 17,200,000 equity shares (being 2% of the pre-issue paid up capital),and for sale of 107,500,000 equity shares (being 12.5% of the pre-issue paid up capital) held by the President of India.

During September 2017, a team comprising Senior executives of the Corporation and Merchant Bankers held series of meetings with various Analysts, Mutual Funds, Institutional Investors during the domestic and international roadshow of the IPO

The Draft Red Herring Prospectus (DRHP) approved by the Board of the corporation was filed with SEBI and IRDAI on 7th August 2017. The SEBI observations were responded to and accordingly SEBI approved the Corporation’s IPO on 22nd September 2017 along with final observations. All regulatory observations were incorporated in the updated DRHP of the Corporation which thereafter was filed with SEBI.

The Red Herring Prospectus (RHP) was finalized after receipt of SEBI letter for filing of Updated DRHP and the same was approved and filed with Registrar of Companies (ROC). ROC approved the same on 3rd October 2017.

Regulatory compliance required appointment of independent directors by the Government on the Board of GIC Re which was carried out.

In consultation with DIPAM the floor and cap Price for the IPO was approved at ` 855/- and ` 912/- respectively along with a discount of

` 45/- to the offer price for Employees and Retail individual bidders. The Bid Open & Close dates were finalized as 11th and 13th October 2017 respectively.

National Stock Exchange was selected as the designated Stock Exchange and GIC Re decided to list shares on both Bombay Stock Exchange and National Stock Exchange.

The Corporation’s IPO was open for subscription as per schedule and was oversubscribed by 1.31 times.

The Corporation in consultation with DIPAM approved the offer price at ̀ 912/-. In line with regulatory requirements, the Corporation approved the basis of allotment and shares were allotted.

The equity share of the corporation was listed on NSE and BSE on 25th October 2017 and the status of GIC Re changed to a Government Company, wholly owned being now dropped.

This presents a very important milestone for the corporation in its journey from being right at the centre of the nationalization to opening up the sector to the private players and now GIC Re itself being divested. This also now makes it possible for the corporation to raise additional resources from the market instead of relying solely on the government capital subscription. Given the growth opportunities in the Indian market, this opens up important possibilities for the corporation. Simultaneously, the corporation will be under greater focus from analysts, investors and public in terms of evaluation and benchmarking of performance and governance standards. With some other insurance companies in the Indian market also floating IPOs in recent past and some more on the anvil, the insurance sector is poised for its next phase of evolution.

- Satheesh Kumarulu



Claim inflation is an important topic for

reserving and thus one of the areas of

concern in insurance industry. There

is no common definition on the subject but

in general, it is the increase in claim payment

amount on the same level of exposure

overtime-period. The claim inflation has

various components which include financial

inflation (represented by Consumer Price

Index), judicial inflation, regulatory inflation,

increase in frequency resulting from increase

in insuredawareness, higher fraud incidence

andfunctional efficiency .The list is non-

exhaustive and there can be other reasons

too. In fact, it can be taken to mean any

sustainable increase in claims outcome due

to whatever factor. Broadly speaking this can

be, for the purpose of analysis, broken down

into severity increase and/or frequency

increase attributable to some new category

of claims.

The significant impact of claim inflation can

be seen on reserving, pricing, reinsurance

protection and capital management. The

methodology used for claim reserving by

insurance companiesis mainly based on

Unpleasant Unsurprise - Claims Inflation in Non-Life Industry

methodology specified by the regulator. This

has to be followed in conjunction with any

guidelines from the professional actuarial

bodies. Any variation in methodology needs

to be justified by the appointed actuary.

This methodology would generally include

the estimation of future claim development

based on the past claim development which

is inclusive of past claim inflation.The most

commonly used method for reserving in

non-life sector is chain ladder method. Under

this method the future claim development is

based on past claims development pattern

which inherits any claim inflation over

the past year. The future claims would be

developed based on the assumption that

the weighted average past claim inflation

over the development years would follow

in the future. The major issue here is the

segregation of claim development into

various parts such as claims increase because

of program design change, underlying

exposure change and the real inflation.

Having considered future inflation based

on past inflation, the major issue may result

if the past inflation rates differs from the

expected future inflation rate. In this respect

the Indian regulator in Chapter III (14e) (iv) of

general insuranceclaim reserving regulation

says,

“The Appointed Actuary shall ensure that

the estimation process shall not discount

the estimated future development of paid/

ncurred claims to the current date nor shall

it load the claims outstanding specifically

to provide for inflation in the future cost of

claims, other than the factor already inherent

in the estimation process.”

Therefore, there is no need to consider any

variation in future inflation from what is

considered in estimation process. But at the

same time the claim reserves should not be

discounted so as to keep a buffer for such

variation.

The other major area affected by claim

inflation is pricing. Pricing is handled

by underwriters and may be referred to

actuaries for technical pricing. Pricing

exercise considers the expected claim cost,

expenses and the cost of capital to derive

the total cost for the coverage provided.

Expected claim cost is the multiple of

RESERVED MUSINGS



average claim frequency and average claim

severity. Thus pricing involves projecting

claims cost by projecting frequency and

severity. This could be aggregated for various

risk bands and classifications. The frequency

and severity would need to be adjusted

for underlying trends such that the past

figures get updated to be in line with the

expectations for the future. Having done

that the exposure in the future year would

be subject to future years claim inflation.

Therefore, one would be required to estimate

the future claim inflation and adjust the

pricing accordingly.

The price so arrived should be sufficient to

settle the expected claims. The uncertainty

here is in the future claim inflation rate; if

the estimated future inflation figures vary

consistently and significantly from the actual

figures over timethen it becomes a major

area of concern.

Claim Inflation (%) = (Expected claims cost

on this year’s policy this year / Expected

claims cost on this year’s policy year) -1

As highlighted by the above formula

the inflation is adjusted each year while

calculating policy premiums. Therefore, any

variation in inflation rate would be corrected

each year. The sensitive part here is the delay

in settlement of claims for a given exposure

year for which the premium is already

collected.

In case the inflation rate affects a claim

payment which is supposed to be made in

multiple years then the effect of inflation

would be multifold resulting in major

difference in expected in actual claim

payment. For example, if the claim is paid

over 5 years; the inflation would affect the

claim amount till it is fully settled. This may

lead to over or under availability of premium

to make the claim payments.

Now it is important to note such cases where

there can be major variation in inflation rates

and claims are paid over multiple years. One

such example is of long term care contracts

where the company provides facility

foreither home and nursing care for the

insured. In such cases if the cost of nursing

care or home inflates, it will have direct

effect on the cost for the insurer and that will

continue for multiple year.

The other area of concern could be if the line

is exposed over multiple years such that the

it is exposed to variation in future inflation

for multiple year. One such example is of

engineering insurance where the exposure

is over the long run and hence isexposed

to future inflation. In case of engineering

insurance, the premium is decided at the

time of the contract but the underlying

project gets completed in different phases

over the year. In this case if the inflation

affects the cost of construction and labor, it

would directly impact the cost of insurance

to the insurance company.

Another important aspect affected by claim

inflation is the protection cover required

by the insurance companies. If the claims

inflation is not factored in while buying

protection, it is possible that the insurance

company finds the protection bought

inadequate. It is important that there is no

significant variation between the claims

inflation estimates of the insurer and their

reinsurer. If reinsurers estimate claims

inflation higher than that by the insurer, it

would have two aspects; one the protection

purchased may be deemed to be inadequate

andanother that they would charge higher

protection cost. Sometimes there may

be a lag in underlying policy period and

protection period; say if the policies run

from 1st January to 31st December and

the protection cover say starts from 1st

April then the reinsurance companies while

providing protection would also account

for any changes that took place between

31st December of previous year and

1st April of the next year.

As discussed claims inflation considerations

affect reserving and pricing and thus, also

the level of protection bought. This is where

capital allocation comes into play. Having

considered claims inflation, the profitability

of the portfolio would be re-estimated and

would require decisions about protection

RESERVED MUSINGS

which goes in tandem with capital allocation.

With higher claims inflation, the available

capital would decrease. This would also

impact the available solvency margin of the

company.

The last point of discussion but the most

important one would be to how to estimate

inflation. As discussed earlier that the

reserving technique relying on triangulation

of losses includes the trending of inflation

in its estimation process. The same

methodology can be used to ascertain the

trend of inflation. In case the development

of claims for different underwriting years

is changing that would suggest a change

in trend of inflation over the year. One

important point here is that the development

factors includes the effect of change in policy

design and underlying exposures. It would

require that these changes are factored in

while analyzing the development factor.

For conclusion, it can be said that the change

in inflation is considered continuously in core

insurance decision making processes.It can

develop through a creep and may not quite

throw a surprise barring upheaval in the

economic climate. But it certainly corrodes

profitability. The topic of claims inflation

comes up for discussion from time to time

but any substantial literature on the topic

has not developed. It somehowgets fully

considered implicitly rather than explicitly in

the loss development estimates. The major

impact of inflation is mitigated if there is

no major variation in actual vs estimated

inflation rates. Otherwise the reason for such

variation would need to be investigated

properly to account that into future business

plans.

- Hemant Khurana

ulu



Recent media reports of aircraft coming

to a halt facing each other on a runway or

aircrafts missing each other in mid air has

raised a question whether air traffic growth

coming at the cost of safety.

The Indian Airspace is getting highly

congested with the number of aircraft that

are taking to the air. We have the Mumbai

– Delhi which is the fourth busiest route in

the world with about 7.3 million passengers

taking these flights. To cater this increasing

number of flyers we have seen that there are

almost 1000 aircraft purchase orders by the

operators in India.

As the Government intends to incentivize air

travel by the recent scheme the air traffic is

all about to grow rapidly.

As the number of aircrafts increase the

chances of an accident, even though remote,

increase.

The DGCA (Directorate General of Civil

Aviation) categorization of incidents are,

1. “Accident” shall mean an occurrence

associated with the operation of an

aircraft

2. “Serious incident” means an incident

involving circumstances indicating that

there was a high probability of an accident

Identifying an accident is easier, while

incidents are a little bit trickier. DGCA

has defined “serious incidents” with an

exhaustive list as guidance, while there are

many on it which are procedural, but the

below list is little bit interesting to note,

1. Near collisions requiring an avoidance

manoeuvre to avoid a collision or an

unsafe situation or when an avoidance

action would have been appropriate.

Aviation Safety - Near Miss or Near Hitsa. Collisions not classified as incidents

2. Controlled flight into terrain only

marginally avoided.

3. Aborted take-offs on a closed or engaged

runway, on a taxiway or unassigned

runway.

4. Landings or attempted landings on a

closed or engaged runway, on a taxiway

or unassigned runway.

5. Multiple malfunctions of one or more

aircraft systems seriously affecting the

operation of the aircraft.

Ideally unless an accident occurs all are

defined as incidents, the seriousness of it is

measured with a scale by the authorities only.

As mentioned earlier, those are the accidents

that did not happen due to corrective action

by the personnel in command, technology

(viz. instrument such as TCAS (Terrain

collision avoidance system), GPWS (ground

proximity warning system) or may be sheer

coincidence.

There have been reports of aircraft accidents

due to the same, recently there have been an

incident of a Bombardier 605CL (a big aircraft

in the business jet category) being declared

a total loss after it had been struck by wake

turbulence of an Airbus A380 over the Indian

Ocean. This incident had happened with

the aircrafts being well outside the defined

vertical separation limit for a Jumbo.

Wake turbulence is a disturbance in the

atmosphere that forms behind an aircraft as

it passes through the air. It includes various

components, the most important of which

are wingtip vortices and jetwash. As the

aircraft become bigger in size the wake size

become bigger and there by requires aircraft

to maintain larger separation both in vertical

and horizontal distances from one another.

In India, we have had an accident due to

miscommunication between the flight crew

and the ATC, wherein the pilot did not take

corrective action like in Charkhi Dadri Mid-Air

Collision, which is the third deadliest incident

in the world for aviation accident with about

350 people dead. This accident happened in

1996 with the aviation industry being on the

verge of growth in India. Any incident of this

seriousness in the future can have disastrous

results as the air-traffic increase in India.

Any accident prior to it’s happening will

be like an inverted iceberg where the

unknowns will drive the overall output. As

we learn more about non-serious incidents

being reported we are invariably nearing

an accident that may or may not happen. As

said before even though being remote it has

a probability of occurring.

We have had technological advancement

with many equipment being a mandatory

to new aircraft that are being designed

with EGPWS (Enhanced Ground Proximity

Warning System), TCAS which have been

included due to the past accidents and to

reduce the occurrence in the future.

Apart for the above we have also seen that

wildlife coming on to the runway as an

aircraft prepares to take off or on approach to

landing, being felt by the insurers purse and

luckily with no loss of life. These incidents

raise concern on the security measures

available at the airports across the country

and more so specifically to Tier I and Tier II

cities across the country as the government

intend to connect them. We as insurer are

aware that aviation is and will continue to

be low frequency and high severity accident

related line of business. Let us be more aware

that as the air traffic increase we are very

close to a scenario where a near miss can

always be a scenario of near hit that did not

happen.

-Bharathi Vijayan

ulu

SAFETY ON WINGS



New Postings

Taking over the Reins

FAMILY ADDITIONS

Ms. Sashikala MuralidharanDirector & General Manager

Mr. Uttam Kumar Sharma Deputy General Manager

Ms. Sashikala Muralidharan took charge as

Whole-Time Director of Corporation on 28th

December 2017. She holds a bachelor’s Degree

in Commerce. She is Intermediate of ICWA and

Associate Member of Insurance Institute of India. She

joined New India Assurance Co. Ltd. as Direct Recruit

officer in the year 1983 and has put in 35 years of

service in Insurance Industry.

Mr. Uttam Kumar Sharma, took charge as a Deputy

General Manager of our Corporation on 29th December

2017. He holds a bachelor’s degree in Commerce. He is

a Member of The Institute of Chartered Accountants

of India and is a Fellow Member of Insurance Institute

of India. He joined New India Assurance Co. Ltd. in the

year 1985 as Direct Recruit Officer. He has 32 years of

experience in Insurance Industryand has served in

various capacities like Divisional Manager, Regional

Manager and Chief Regional Manager.

Mr. Charles Asirvatham Deputy General Manager

GIC Re South Africa Ltd

Mr. N Ramaswamy Deputy General Manager

GIC Re, London Branch

Mr. Vishnu Salunkhe Assistant General Manager

GIC Re, Malaysia Branch

PR

ES

SM

AN

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