Innovation and Distribution
Osvaldo do NascimentoTaipei, Taiwan
July, 2008
International Insurance Society, Inc44th Annual Seminary
V6 – 30/06/08
1. Brazil: - Prepared to develop its Insurance Industry
2. Insurance Market - Need of Growing
3. Information Technology to develop insurance sales
4. Micro-insurance: Definition and Challenge
5. “Brazil Case” – CRM and Life Insurance Sales at Itaú
2
Brazil
Area (km2): 8,511,965
GDP 2007: US$ 1,3 trillion
Population 2007: 191.8 million
3
About Brazil...
Conditions to Develop the Insurance Industry in Brazil
Inflation under control
Wealth distribution
Market Growth
4
0,00%
5,00%
10,00%
15,00%
20,00%
25,00%
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Inflation in Brazil(INPC - % p.y.)
Source: IBGE5
(*) 2008 until May
(*)
Nominal and Real SELIC Rate(in 12 months, % p.y.)
12.2%
0%
4%
8%
12%
16%
20%
24%
28%
32%
Jan
-97
May-9
7S
ep
-97
Jan
-98
May-9
8S
ep
-98
Jan
-99
May-9
9S
ep
-99
Jan
-00
May-0
0S
ep
-00
Jan
-01
May-0
1S
ep
-01
Jan
-02
May-0
2S
ep
-02
Jan
-03
May-0
3S
ep
-03
Jan
-04
May-0
4S
ep
-04
Jan
-05
May-0
5S
ep
-05
Jan
-06
May-0
6S
ep
-06
Jan
-07
May-0
7S
ep
-07
Jan
-08
May-0
8S
ep
-08
Jan
-09
May-0
9S
ep
-09
Nominal Selic rate
Real interest rate (ex post)
Average real rate
Interest Rate
6Source: Brazilian Central Bank
Net Debt
Net debt of public sector (% GDP)
-9.4
41.0
-15,0
-10,0
-5,0
0,0
5,0
10,0
15,0
20,0
25,0
30,0
35,0a
br-
01
jul-
01
ou
t-0
1ja
n-0
2a
br-
02
jul-
02
ou
t-0
2ja
n-0
3a
br-
03
jul-
03
ou
t-0
3ja
n-0
4a
br-
04
jul-
04
ou
t-0
4ja
n-0
5a
br-
05
jul-
05
ou
t-0
5ja
n-0
6a
br-
06
jul-
06
ou
t-0
6ja
n-0
7a
br-
07
jul-
07
ou
t-0
7ja
n-0
8a
br-
08
Do
llar
den
om
inat
ed d
ebt
30,0
35,0
40,0
45,0
50,0
55,0
60,0
Net
deb
t
Dollar denominated debt/GDP Net debt/GDP
Apr / 2008
Source: Brazilian Central Bank7
Foreign Reserves
Source: Brazilian Central Bank
US$ Billion195,8 (*)
(*) Apr, 2008
10
30
50
70
90
110
130
150
170
190
210
01/0
0
07/0
0
01/0
1
07/0
1
01/0
2
07/0
2
01/0
3
07/0
3
01/0
4
07/0
4
01/0
5
07/0
5
01/0
6
07/0
6
01/0
7
07/0
7
01/0
8
US$ BillionInvestment grade by Standard & Poor’sUpgrades on April 30, 2008 – long-term foreign currency
Brazil: BBB -
8
Source: ACLI Fact Book, 2005
Asset Growth
$10.400
$2.800
$495
$4.500
$2.100$826
$0
$2.000
$4.000
$6.000
$8.000
$10.000
$12.000
1985 1995 2006
$ in
bil
lio
ns
Mutual Fund Companies
Life Insurance Industry
Robert A. Kerzner, President and CEO of LIMRA International presented this slide during the LIMRA 2007 Annual Meeting in Boston last October.
9
And more…
According to LIMRA , 60% of consumers in the USA say they prefer to buy “face-to-face”.(*)
But , to be physically present to sell “face-to-face” nowadays we have to consider:
(*) Trillion Dollar Baby, LIMRA International, 2005 10
So, we can be available, but not physically present, offering the most recent technology to interact with clients.
Costs of transportation Traffic jam into big cities New stile of life
Face-to-face preference Personalized approach Opportunity to establish relationship
X
11
1.4 billion Internet users worldwide!
Source: Internet World Stats
Brazil: 46.2 million
12
Wealth Distribution in Brazil
Bolsa Família – a Brazilian program to reduce the poverty
11 million families supported by Bolsa Familia
45 million people are covered
US$ 6.8 billion* is the budget to 2008
(*) US$ 1,00 = R$ 1,597 – 06/30/2008
Mr. Luiz Inácio Lula da Silva (President Lula)President of República Federativa do Brasil
13
15% 15%18%
34% 36% 46%
51% 46% 39%
2005 2006 2007
Source: Ministry of Finance - Research IPSOS (O Estado de São Paulo, pages B16, 03/30/2008).
Class A/B
Class C
Class D/E
Wealth Distribution in Brazil
More than 86 million people
Changes in the population distribution by classes
Micro-insurance
Micro-insurance is a type of insurance with low premiums developed to protect low-income people against specific risks.
As the premium price is very low, there is a need of a large scale to allow its economic viability and one important issue is to define the distribution model to be adopted by insurers.
In Brazil SUSEP (the Governmental Supervisor) and FENASEG (the insurance market institutional representative) are working hard to create the adequate environment to develop the micro-insurance.
Of course, some partnerships will be relevant to sell micro-insurance, like utilities companies (electricity and gas bills), retail market, credit cards providers and financial institutions.
China, India and Russia have significant experience in micro-insurance distribution, but Brazil certainly will be a expressive player in this business considering its technological structure provided by the financial industry and specialized insurance brokers developed inside the communities.
14
Challenge! Regulatory changes…
INSURANCE COMPANIES
BROKERS AGENTS DIRECT SALES BANKASSURANCEFINANCIALADVISORS
CLIENT
Distribution Players at Insurance Industry
Mobile Phones(SMS & 3G technology)
Internet Call Centers Financial Services
Providing the distributors…
… with high technological tools
122 million of mobile phones in Brazil (1)
46.2 million of internet users in Brazil (2) and 99% of Income Tax Declarations delivered by internet (3)
166,773 ATM’s (5)
18,308 Bank Braches (4)
1. Source: ANATEL – Brazilian's Telecommunications Agency2. Source: Internet World Stats – Dec/20073. Source: O Estado de São Paulo, 04/may/2008 – Mrs. Renata veríssimo, Jornalist4. Source: Tribuna do Brasil, 28/may/20085. Source: Research “O setor bancário em números” by FEBRABAN – Brazilian's Association of Banks – Dec/2007 15
16
Experience of Itaú in Segmentation and Distribution
Key Information (*): 2nd largest financial institution in Brazil 2,594 branches 11.2 million current account holders US$ 138.7 billion** billion in AUM
(*) March, 2008
(**) US$ 1,00 = R$ 1,597 – 06/30/2008
CRM Environment
17Material prepared by Banco Itaú, Brazil
CLIENT
InternetATMVideoPhone
E-mailSMS
Mailing
Insurance Products
Insurance Products
Insu
ran
ce P
rovi
der
s
Brokers Agents Financial Advisors Insures Banks Partners
StimulationInteraction
Insu
rance P
rod
ucts
Service Interactive Providers
Post-Sales Valuation Segmentation
Control of stand-by Contacts Policies for
Product-Channel
2
Elected Customers to offers
1
Sales Probability Models
Sales Optimization Budgets/Scenario,Capacity Planning
7b
Cartão
LIS
$11
$6
$0
$3
$4
$1
Seg. PPI
CPF 1
CPF n
Warnings optimization Algorithm
7a
Customers CRM Feedback Registers
3
Potential Offers Basket for each
Customer
Valuation João Crediário - 281
PPI – Tomadores Renda < R$500
Cartão - Tomadores Renda < R$500
Residência - Tomadores Renda < R$500
Mini PIC - Tomadores Renda < R$500
PIC – Tomadores Renda entre R$500 e R$1.000
PPI – Tomadores Renda entre R$500 e R$1.000
Cartão – Tomadores Renda entre R$500 e R$1.000
Residência – Tomadores Renda entre R$500 e R$1.000
Mini PIC – Tomadores Renda entre R$500 e R$1.000
Valuation João Crediário - 281
PPI – Tomadores Renda < R$500
Cartão - Tomadores Renda < R$500
Residência - Tomadores Renda < R$500
Mini PIC - Tomadores Renda < R$500
PIC – Tomadores Renda entre R$500 e R$1.000
PPI – Tomadores Renda entre R$500 e R$1.000
Cartão – Tomadores Renda entre R$500 e R$1.000
Residência – Tomadores Renda entre R$500 e R$1.000
Mini PIC – Tomadores Renda entre R$500 e R$1.000
Custo de Venda
Valuation
500
375
250
125
0
% (Stimulated x Controlled)
$ post-sell
% x $ = Potential stimulations
Valuation
Products Uses(renew cancel,
attrition, up-sell, etc)
Stimulation feedback(acceptation/refuses)
Operational Return(no-call, phone and address actualization
and signalization good/bad)
Performance Manage
Customers Feedback
Feedback analysisto support theCorrect Value Proposition(price, product, channel, communication/script)
Warnings and TelemarketingCommittees
Bureau
4 5
6
Control Groups Feedback(to determine Stimulus)
Objective: Total ValuationMaximization
Channels
8 Intranet accompaniment / alert triggers
9
27.5 29.6 27.3 28.7 28.1 28.4 30.9 28.8 30.6 30.4 32.8 30.4 28.8 30.5 32.3
78.283.5
74.5 75.3
57.4
78.2
71.2
98.187.6
115.0124.5
0
20
40
60
80
100
120
140
0
10
20
30
40
50
Fev/07 Mar/07 Abr/07 Mai/07 Jun/07 Jul/07 Ago/07 Set/07 Out/07 Nov/07 Dez/07 Jan/08 Fev/08 Mar/08 Abr/08
Val
uat
ion
(R$
MM
)
Qtd
e d
e A
cess
os
(MM
) ***
*
Acessos Valuation Total - (Eixo Secundário)
M
S
IT
Disponibilidade Financeira
CapacidadeFinanceira
PERFIL de
PERFIL da 7 1 .4 % 7 4 .8 % 6 6 .1 % 7 1 .6 % 6 7 .0 % 6 7 .1 % 6 7 .0 % 6 7 .0 % 7 0 .0 % 7 0 .7 % 7 1 .4 % 7 6 .2 % 7 9 .9 % 7 6 .6 %
6 6 .3 % 6 8 .0 % 6 3 .9 % 6 3 .3 % 6 4 .2 % 6 2 .8 % 5 8 .1 % 4 4 .7 % 6 3 .9 % 6 6 .7 % 7 1 .4 % 6 8 .6 % 7 5 .1 % 7 1 .0 %
5 9 .0 % 6 0 .4 % 6 1 .2 % 5 6 .9 % 5 5 .7 % 5 8 .5 % 3 9 .4 % 4 1 .2 % 5 8 .4 % 6 5 .5 % 7 0 .4 % 6 8 .4 % 6 8 .4 % 7 2 .3 %
5 3 .7 % 5 5 .9 % 5 9 .2 % 5 5 .7 % 5 3 .9 % 5 3 .2 % 3 5 .9 % 3 8 .9 % 5 5 .8 % 5 8 .7 % 6 3 .9 % 6 6 .7 % 6 9 .1 % 7 2 .8 %
4 7 .6 % 4 9 .5 % 4 8 .7 % 5 1 .1 % 4 6 .3 % 5 1 .4 % 3 2 .1 % 3 8 .7 % 5 2 .2 % 6 0 .0 % 6 2 .5 % 6 1 .0 % 7 0 .9 % 6 4 .9 %
3 5 .3 % 4 1 .5 % 4 4 .6 % 4 2 .9 % 4 1 .7 % 3 9 .3 % 3 0 .7 % 3 4 .9 % 4 7 .9 % 5 8 .3 % 5 6 .1 % 5 8 .1 % 5 9 .5 % 6 9 .1 %
2 7 .3 % 3 7 .0 % 3 8 .7 % 3 4 .9 % 3 8 .6 % 3 7 .0 % 2 8 .6 % 3 2 .9 % 4 6 .5 % 5 1 .0 % 5 4 .2 % 4 8 .4 % 5 0 .0 % 5 0 .0 %
2 4 .8 % 3 3 .7 % 4 0 .3 % 3 6 .7 % 3 7 .8 % 3 9 .2 % 3 0 .9 % 3 5 .7 % 4 0 .0 % 4 1 .0 % 3 3 .3 % 2 8 .4 % 4 1 .2 % 4 1 .0 %
3 5 .9 % 2 7 .8 % 2 4 .2 % 2 4 .5 % 2 8 .8 % 2 7 .6 % 2 0 .6 % 2 2 .1 % 2 6 .1 % 2 6 .1 % 2 6 .1 % 2 6 .1 % 2 6 .1 % 2 6 .1 %
CRM Operational PlatformCRM Operational Platform
DW
CUSTOMER
Telemarketing
Bankline
Direct Mail
Telemarketing
ATM
BanklineBankfone
CashierBranch
18Material prepared by Banco Itaú, Brazil
Filters:Customer File Quality and Contact Restrictions
100% Active Customers &
Prospects
31,5% Elect for
Telemarketing
65,2% Elect toOffers
UniqueSelection
Optimization
CRM Policies
24,7% Sent to Operation
19,6% Effective Contact
15% Conversion
(Sell)
$ - Results (Valuation 7 years)
• Relation Customer-Channel saturation• Relation Customer-Product saturation• Preferred Channel to buy• Profile: Investor, Mixed, etc.• Product propensity
CRM Feedback
for each Customer
Modeling CRM by Customer /Product
/ Channel
CRM x Valuation
50% effective Call
Operational Optimization Workflow
Filters:Elect to Offers and Standby Policies
19Material prepared by Banco Itaú, Brazil
20
0
200.000
400.000
600.000
800.000
1.000.000
2008 (Jan to May) 2007
30%
70%27%
73%
Sales by electronic stimulation (1)
Sales by “face-to-face” (2)
(1) ATM, Internet, Bank Cashier and Telemarkting(2) Sales Team and brokers
Material prepared by Banco Itaú, Brazil
277,000
646,000115,000
312,000
Experience of Itaú in Life Insurance Sales(Number of individual polices sold)