Fuelling the Indian
entrepreneur –
Opportunities in SME
Bancon 2010 Panel Discussion
Presentation by Ramnath Balasubramanian, McKinsey & Co
December 3rd, 2010
CONFIDENTIAL AND PROPRIETARY
Any use of this material without specific permission of McKinsey & Company is strictly prohibited
India has more than 8 million SMEs contributing significantly to the
country’s GDP, exports and employment
Number of
Companies
Turnover cutoff
Rs. crore
CAGR
(no. of co.’s)
%
SME sector in India
Large
corporates
>500
1,500
22
▪ Contributes to ~39% of
country’s
manufacturing output
▪ Contributes to ~34% of
Mid
corporates
125-500
4,000
19
exports and ~20% of
imports
▪ Provides employment
to ~68 mn people in
rural and urban areas
of country
200,000
18
Small SME 2-10
1,500,000
22
Micro SME <2
6,500,000
25
Medium SME 10-125
SME
SOURCE: Prowess database; market interview; India Budget 2006-07; team analysis
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SME banking revenue pool will grow at a CAGR of 16% over the
next five years with growth being uniform amongst variousESTIMATES
products
SME revenue pool
Mix of SME revenue pool
INR '000s crore
INR '000s crore, percent
75
65
16%
Investment banking
100%
CMS
FX and rates
Trade finance
Deposits
32
1
6
3
10
23
65-75
1
3
10
10
23
32
Lending
FY 2009
2015E
2015E
SOURCE: RBI data; Prowess data; market interviews; McKinsey analysis
58
55
FY 09
FY 15
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Over 70% of SME advances revenue is concentrated in
the top 15 cities and 9 industries
SME advances revenues
SME advances revenues
Percent
Percent
Remaining
cities
25 Cluster
cities
Top 15
cities
14
11
75
1
Mumbai
2
Delhi
3
Chennai
4
Kolkata
5
Bangalore
6
Hyderabad
7
Ahmedabad
8
Coimbatore
9
Pune
10 Chandigarh
11 Ludhiana
12 Jaipur
Remaining
sectors
Top 9
sectors
30
1
Whole Sale Traders
2
Textiles
3
IT and professional
services
4
Retail traders
5
Metal works
6
Food processing
7
Real estate
8
Transport and
logistics
9
Auto and Auto
ancillary
70
13 Vadodara
14 Ernakulam
15 Surat
SOURCE: RBI; McKinsey analysis
ESTIMATES
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SME is a relatively profitable segment, but returns could
vary based on operating model and ability to manage risks
ESTIMATES
Percent of average advances
Risk-adjusted ROA for high performing SME Bank
2.7
4.0
4.6
2.7
1.0
Lending Risk
NII
cost
5.0
1.7
Risk
Deposit Fee
Opex
adjusted NII
Income
NII
Riskadjusted
ROA
Three key drivers of
profitability of SME
segment
▪
Ability to manage
risk (loan losses)
▪
Cross sell deposit
and fee incomerelated products to
SMEs
▪
Manage operating
costs of serving
SME segment
Risk-adjusted ROA for under-performing SME segment
2.7
2.7
1.8
0.9
4.0
0.9
Lending Risk
NII
cost
Risk
Deposit Fee
Opex
adjusted NII
Income
NII
SOURCE: Central bank data; expert interview; 2008 Asia Pacific SME Banking Report
0.5
Riskadjusted
ROA
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SMEs’ financial needs can be broadly classified into three categories
Traditionally served
+
“Enabling
day to day
business”
1
Core
financial
needs
“Creating
flexibility and
acquiring
assets”
Rarely served
“Managing
businessrelated risks”
–
2
3
Stakeholders
related
needs
Conducting
daily transactions
Managing and investing
high cash flow
Lifespan of assets and liabilities
Managing and financing
working capital
Acquiring and
maintaining assets
Complexity of risk protection
Single
“isolated” risks
“Serving
stakeholders’
financial needs”
Life-cycle “Supporting
strategic
related
growth”
needs
SOURCE: McKinsey
Complexity of cash management needs
Multiparty and
complex risks
SME owner and shareholders
SME employees and management
SME suppliers and/or customers
Lifecycle-based long-term financing needs
Starting
the business
Changing
the business
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SMEs are extremely loyal to their primary bank with ~70% of SMEs
have banking relationships of more than 6 years
Tenure of relationship with lending bank (percent)
Top 15 cities
Cluster cities
10 or
more years
52%
6-9 years
19%
3-5 years
58%
11%
24%
23%
Upto 2 years
6%
7%
Similar trend observed for transacting bank as well
SOURCE: McKinsey SME survey
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There are 7 key elements of a successful SME business
1
Appropriate customer segmentation and value proposition to ensure
different types of SMEs are served according to their needs
2
Business model choice– in terms of traditional lending based vs. liability
led vs. technology led (e.g., supply chain financing)
3
Servicing model to ensure rapid turn-around times at low cost to serve
(e.g., internet, loan factories)
4
Relationship management and branch architecture to cover and provide
specialised services to SME
5
SME-specific risk rating tools in a relatively data-scarce environment
using qualitative credit assessment based techniques
6
Suitable operating architecture in terms of centralisations vs
decentralisation of mid and back-office functions
7
Putting in place the appropriate organisation construct and business
performance management system to ensure the right focus on the segment
SOURCE: McKinsey
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1. Segmentation and value proposition
Value proposition: Bundled offers can help drive cross-selling
Description
Deposit and
cash flow
packages
Combination of business account and/or
personal account in one single package
(or two business or personal banking
products tied-up) with a fee discount
Volume
correlated
products
Interests/loan size relationship benefits
on business/individual account, e.g.,
▪ Business offset services reduce amount
of interest on business loan based on
balance in personal deposit account
▪ Loan size determined based on deposit
balances with bank
Sector
specific
offers
Examples
Combination of business and individual
oriented products that are tailored to a
specific sector (e.g., doctors, lawyers)
¹
¹
1 Limited number of sector specific offers available including non-profit, agricultural and professional services
SOURCE: McKinsey; mystery shopping; company websites
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2. Business model
Business model choice : Supply chain based
approach
Example of channel
financing strategy deployed
by a successful bank
CLIENT EXAMPLE
Traditional
Supply chain
Impact achieved
Profitability of supply chain lending vs. traditional lending
▪ Needs-based segmentation,
focus on SME within large
corporate’s supply chain
▪ Performance management
and incentive system
driving cross-unit
collaboration
▪ Use of proprietary scoring
model and client profitability
in credit assessment and
pricing
▪ Streamlined, seamless
IT-platform across segments
and products, leveraging full
transaction information
Basis points, indexed
100
800
Risk adjusted revenues
Cross-sell opportunities on supply chain finance
Basis points, indexed
Risk adjusted lending revenue
Trade services cross-sales
Cash management cross-sales
100
~65
~75
FX cross-sales
~55
Total revenues
~300
SOURCE: “Serving Asian SMEs” KIP team, 2008; expert interviews
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2. Business model
Business model choice : Integrating business
and personal wealth needs of SMEs
Example of integrated
business and personal
relationship approach
▪ Identified overlap and
cross-sales potential for
both wealth mana-gement
and SME banking
▪ Developed of SME owner
specific wealth
management offering based
on insights from SME
interaction behavior
▪ Refined organization model
with aligned performance
management and incentives
to further cross-unit
collaboration
▪ Installed referral system and
eventual collaboration model
to facilitate cross-unit sales
ASIAN CLIENT EXAMPLE
Impact achieved
Additional profits from cross sale of SME banking products
to wealth management SME customers
Indexed
~100
Current profit from SME owner’s WM
Net interest income
~245
~75
Net fee income
Operation cost
~145
Risk cost
~65
Profit
~110 ~210
Additional profits from increased WM penetration of SME
and wallet share of SME owner’s WM
Indexed
~100
Current profit from SME owner’s WM
Increased wallet share of SME owner’s WM
~195
~180
Increased WM penetration of SME
Operation cost
Profit
SOURCE: “Serving Asian SMEs” KIP team, 2008; expert interviews
~110
~265
~365
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6. Risk management
Effective mitigation of risk in SMEs will need a combined
quantitative and qualitative credit assessment approach
Quantitative rating
(statistical score)
Combined rating
Qualitative credit
assessment
▪
▪
One overall rating and
Probability of Default
▪
▪
Method of combination
chosen based on the
relative performance
of the two underlying
ratings
Appraisal of the
business
– Operating
environment
– Cash flow
forecasting
– Asset valuation
– Management, etc.
▪
Presented as a series
of questions with predefined answer options
(check boxes)
▪
Statistical techniques
– Logistic regression
– CHAID
– Neural networks
Focus on quantitative
or quantifiable data
– Financials
– Credit bureau
information
– Demographics
(e.g., age)
– Account information
(e.g., balance,
monthly turnover)
SOURCE: McKinsey Risk Management Practice
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6. Risk management
A combination of quantitative and qualitative models
has consistently yielded better results across markets
Quantitative model only
Quantitative model +
separate QCA
Predictive power (GINI) in points, sample cases
72
80
75
75
65
▪ Quantification of
54
52
inherently qualitative
factors such as
management quality
▪ Validation of financials
82
81
The QCA (Qualitative
Credit Assessment) adds
unique insights to credit
assessment
35
and other fraud indicators
▪ Flexible approach to
limited data availability
(e.g., by quantifying also
degree of uncertainty
around a data point)
India
SOURCE: McKinsey Risk Management Practice
Taiwan
Hong Kong
China
North
America
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In summary
1
SME is a large, fast growing and attractive opportunity
for banks and financial institutions and a significant
contributor to the economy
2
Needs of SMEs are evolving rapidly - financial
institutions will need to look beyond core financial needs
for this segment
3
The segment is very local and can be very profitable for
banks – but managing profitability will require a very
sound business model
4
Financial institutions will need to create a differentiated
model to serve this segment and build excellence in one
or more of seven dimensions
SOURCE: McKinsey
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Backup
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Proximity to branch and competitive prices appear as the top two
buying factors
Key Buying Factors (KBFs)
Percentage of respondents stating in top 5 factors
KBFs – lending bank
Factors
KBFs – transacting bank
Factor importance
Factors
62
Proximity to branch
Factor importance
59
Proximity to branch
Competitive prices
57
Competitive prices
Brand name/reputation
56
Brand name/reputation
55
52
Trustworthiness of
the bank
38
Trustworthiness of
the bank
Turnaround time
37
Turnaround time
34
Level of documentation
34
Level of documentation
SOURCE: McKinsey SME survey
33
37
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