Transcript SME Programme Lending Overview Group Best Practices & Key Challenges SME Conference Lahore, Pakistan - May 2005 David Yong GRM Consumer & Programme Lending.

SME Programme Lending
Overview Group Best Practices &
Key Challenges
SME Conference
Lahore, Pakistan - May 2005
David Yong
GRM Consumer & Programme Lending
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Agenda
 Introduction
 Scope
 Overview major ABN AMRO SME businesses
 Business Models
 Credit Process & Product Programmes
 Portfolio MIS
 Use of scoring
 Key Challenges
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ABN AMRO Pakistan
 1948: First foreign bank in Pakistan
 1993: Expansion of branch network (7 branches in 3 cities)
 1998: Introduction LCY deposits & penetration into Affluent segment
 1999: Introduction Personal Loans & Mortgages
 2002: Launch Commercial Banking focusing on Mid-sized Corporates
 2005: Launch Credit Cards
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History of ABN AMRO (1)
 On 29 March 1824, King Willem I
issued a royal decree creating the
Nederlandsche Handel-Maatschappij
(NHM) with the aim of reviving trade
between the Netherlands and the
Dutch East Indies.
 In 1964, NHM merged with De Twentsche Bank to form
Algemene Bank Nederland (ABN) while Amsterdamsche
Bank and Rotterdamsche Bank joined to become
Amsterdam-Rotterdam (Amro) Bank.
 In 1991, these two banks merged as ABN AMRO.
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ABN AMRO today...
Strong Balance Sheet *
Total assets
Group capital
Risk weighted assets
EUR (bln)
742.9
35.6
245.6
Global Resources *
Employees worldwide
Branches and offices
Countries/territories
97,000
3,000+
60+
Solid Credit Rating
Moody’s
Standard & Poor
Fitch IBCA
Long-Term
Aa3
AAAA-
Well- Positioned Bank **
Ranking
Total assets
- Worldwide
- European
* as at 31 March 2005
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 conducts banking, fund management &
insurance.
 ranks 11th in Europe and 18th in the
world based on total assets.
 has over 3,000 branches in more than
60 countries, a staff of about 97,000
FTEs and total assets of EUR 742.9
billion (as at 31 March 2005).
 is listed on the Euronext and the New
York Stock Exchange.
** The Banker, July 2004
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Scope –
SME characteristics & segmentation
 Backbone of economy
 Family owned/dependent (informal)
 Various types of legal entity
 Importance of personal relationship with client
 Quality of financials
 Understated revenues for taxation purposes
 Level of Owner’s commitment and equity
 Part of (small) community network
 Influential community
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Target market definitions across our sample varied
widely across markets and within markets
Main SB segment definition
by geography
Specialist segmentations observed
Specific segments served according to website (e.g. 70% of the 23 banks had a defined
‘Agriculture’ offer)
Average
North
America
2.3
5.3
7.9
(10
banks)
32%
Franchises
Benelux
2.5
4.2
6.0
(3 banks)
41%
Minorities
UK
0.7
1.6
2.9
(4 banks)
Europe
1.0
2.9
57%
Non-profit
7.5
(12 banks)
Other
1.2
2.8
4.3
0
2
4
70%
Agriculture
(3 banks)
6
8
0%
20%
40%
60%
80%
100%
Cut-off turnover (MM)
Mercer Oliver Wyman
Note: n = 32 banks
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Players have positioned themselves as having a few
products in each family – ‘simple and standard’
Simplicity of external offering
(Products per family – according to web-site)
Observations
 Often standardised ‘core’ offer with segment variation injected via
the communications mix
# prods
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 However, most players interviewed said they had many more
products internally
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–
Poor record of product management and rationalisation
 Most players applied a variety of standard customer insight tools
into SB product design
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8
6
4
–
Market sizing and projected profit pools research
–
Competitive research
–
‘Mystery shopping’
–
Networking with local influencers or trade associations
Avg
Factoring
Leasing
Credit cards
Max
Line of credit
Key:
Loans
 Only a few offered external value-added products
Savings
0
Accounts
2
 Best practices would be banks that conducted SB-specific
quantitative research around needs More specialist products such
as leasing, factoring normally outsourced to sister companies
–
e.g. advisory services
Families
Min
Mercer Oliver Wyman
n = 18 banks
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Overview
 Home Market BU’s (NL, US and Brazil) adopted Product
Programmes for SME’s
 Identify potential for further migration (NL & Brazil)
 Products across markets are similar and ‘traditional’
 Emerging markets: cautious start by other BU’s (India,
Indonesia, Pakistan & Taiwan)
 Knowledge-sharing across the Group
 Cut-off point program lending & non- program lending to be
determined per market
 Overseeing 17 Product Programmes with ENR of EUR 2,8
Billion, with transition portfolios
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Overview Total Portfolio (December 2004)
 Total portfolio: EUR 2,8
Billion (Dec 2004)
 Largest portfolio: BU US
with USD 1,3 Billion
 Portfolio consist of
traditional and simple
products (4Q2004: 84%)
 Rapid growth in NL
(organic) and Brazil
(organic + acquisition)
 Transition portfolio BU
NL earmarked >EUR 2,2
Billion
 Cautious start in India &
Indonesia
 Development of plans
for VGPB Business
Owners in NGM Asia
SME Programme Lending Portfolio
(December 2004)
NL
India
Indonesia
1%
1%
US
NL
25%
Brazil
37%
Brazil
India
Indonesia
US
36%
SME Program m e Lending Portfolio
(Dec 01 - Dec 04)
NL
3500
US
3000
2500
Brazil
2000
India
1500
1000
Indonesia
500
0
Dec 2001
Dec 2002
Dec 2003
Dec 2004
Total
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Business models
 Domestic positioning: Home Market BUs
– large client base
– traditional domestic standardised products
– relatively larger distribution network
 Greenfields: International Network
– start from (‘almost’) zero
– competitive edge
– limited distribution network
– limited reliable data for credit assessment
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There are many ways to create growth in
Small Business banking
Return to Local Intimacy
Information-based Strategy

Aus/NZ Bank had lost Small Business (SB) share after
attempting to build low-cost remote channel model

Capital One entered SB market in ’99-’00 applying IBS
techniques

Re-launched a named local point of contact (RM or
branch manager, direct dial number) with letter
campaign and outbound follow-up

Combined marketing and risk analytics, with
predictive modelling to target asset-based products
with a direct marketing model

Saw +50% increase in customer satisfaction, 4-5
points of share gain and now back in top 2 share
position, in less than 18 months

39% 3-yr CAGR in asset growth, now #2 in SB cards
and #3 in SBA loan origination
Exploit Retail Branch Coverage

HBOS’s merger had given it a strong SB business
with the BoS franchise but locked into small branch
footprint

Rapidly hired network of RMs to tackle the £1-10MM
turnover segment – ‘hunter’ force to source
acquisitions – and doubled UK share from 3% to 6%

Now re-branding 400 branches (out of 800) in England
in 2005 and creating in-branch SB specialists to
exploit full retail presence and go after £0-1MM
businesses
Multiple Business Model Focus

US bank had reduced branch network and lapsed in
service quality – suffering SB attrition rates of 30%

Segmented business into 3 distinct propositions:
national direct, ‘affluent’/upper-end SB and branchbased micro-SB, combining personal/business
accounts

Expanded SB franchise beyond branch footprint, now
in Top 3 in US SB lenders. Grew profits at 30% CAGR
over 5 years, vs. bank growth of 20% CAGR
Mercer Oliver Wyman
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Credit Process:
Commercial versus Consumer/SME
Commercial Loans
Consumer & SME Loans
Transaction
characteristics
Low volume
Large heterogeneous
High volume
Small heterogeneous
Approval process
Deal-based
Volume-based
Credit data
Audited financial
statements
Limited consumer financial
data
Handling and
checking
Account management
Review loan-by-loan
Portfolio management by
statistics
Hierarchy of
approval
Senior managers approve Senior managers approve
credit product programmes
large/complex loans
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Traditional deal-based underwriting don’t work in high volume lending
The Boss
Planning
Underwriting
Operations
Collections
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Portfolio Management is in the core of Risk Management function
Credit Cycle
Product Planning
Dynamic
Write-Off
Management Information Systems
Collections
Portfolio Management
Risk Management
Credit Acquisition
Interactive
Account Maintenance
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Risk Management Programme Lending features
 Standardised and ‘simple’ products
 Critical mass/scale
 Risk – reward balance
 Predictability
 Factory - style
 Management by exceptions
Portfolio Management done through approved Product Programmes
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What is a Product Programme?
 A standardized set of rules of credit extension for a group
of customer with similar characteristics or product needs
 A sign-off on a Product Program is considered an approval
of the complete risk/reward characteristics of the product
and the credit cycle process
 Demonstrates that portfolio performance will be
predictable in terms of revenues, delinquencies, and
losses
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The Product Program contains ...










Product Description
Target Market
Economic and Competitive Environment
Eligibility Criteria (Terms and Conditions)
Account Initiation
Account Maintenance
Collection and Write-Off Policy
Treasury, Funding, and Pricing Considerations
Support Systems and MIS reports
Product Profitability and Stress Testing
The Product Programme process is strongly supported through MIS
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Importance of MIS
 Continuously process and transforms data into
information, which will be used in the decision
making process directed towards optimizing
results:
Risk-Return Trade-Off
 Serves as a base for effective credit cycle and
portfolio management: controlling risks and
assessing opportunities
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Example I Portfolio Performance
Products
Brazil - Total
Brazil - Overdrafts
Brazil - Loans
Brazil - Leasing
Brazil - Mortgages
Brazil - Rewrites
ENR (eM) Infection NCL/ANR Rev/ANR
754.322
5,60%
3,78% 22,49%
74.593
9,10%
9,33% 81,52%
591.027
2,90%
2,07% 16,72%
45.751
0,80%
0,28%
5,08%
8.707 12,40%
1,38%
7,81%
33.975 49,90% 23,38% 13,91%
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Programme Lending benefits:
Basel 2 Retail
• An incentive to place as much of the SME portfolio into a
standardised Program-Lending format, as is practical &
prudent. (GRM limit EUR 5MM)
• Whilst the advanced approach has distinct advantages, the
standardised approach is also beneficial with risk weights
at 75%.
• Both Capital relief and cost efficiencies can be expected
from standardisation.
• As more SME portfolios become standardised to take
advantage of Basel II, the product will in turn become
easier to securitize, so the product will become more
attractive to banks, who may choose to keep it on or off
balance sheet based on capital need.
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Implementing Program Lending faces
challenges
 Sponsorship of Senior Management and Line support
 Available credit data to assess clients and prospects
 Human resource and Organization issues
–
Provide adequate and on-going training in credit cycle management
and program lending
–
Ensure an organization capable of meeting the need for greater
coordination and teamwork
 Redesign of business process
–
Identify a project team of individuals who represent functional areas
of the credit cycle
–
Be ready to supplement internal resources with external consultants
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Implementing Programme Lending faces
challenges (continued)
 Sufficient IT systems and data base resource
–
–

Resolve gaps on data source, data quality, data integration and data
usage
Ensure an automated front-end Loan Origination System (LOS) and
Collection System in place
Effective and consistent MIS reporting
–
Establish one single standard or common language reporting system
–
Provide end-to-end MIS consistent with Product Program definition
–
Ensure that the MIS has the ability to “peel the onion” or
disaggregate performance data at various level of detail
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Implementing Program Lending faces
challenges (continued)
 Implementation of scoring methods
–
Scoring systems make sense only for high volume business
–
Application Scoring
• increase underwriting process efficiency
• improve portfolio quality thru statistical control
– Behaviour Scoring
• increase profitable customer relationship
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Scoring tries to evaluate who is the best risk?
Super
Bad
Scorecard Maximum Benefit
Super
Good
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Different score cards for different purposes
 Internal Application Risk Scorecard
– Based on applicants past performance
– New accounts
 Internal Behaviour Risk Scorecard (Behaviour and
Collections Scoring)
– Existing Business
– Based on account holders past performance
 External Credit Bureau Scorecard
– Based on account holders external credit activity
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How It Works – Policy


Rank All Applications By Default Risk
Set Cutoff To Achieve Approval Objectives
40%
Default Rate
Reject High Risk Apps
To Lower Bad Debt
35%
30%
Default Rate
30%
Simplified Underwriting
On Low Risk Applications
25%
Manual Review
Marginal Cases
20%
15%
15%
10%
5%
8%
6%
5%
4%
3%
1% 0,5%
0,2%
0%
Low Score
High Score
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Recap - Key challenges
 Senior Management commitment
 Skill-set & human resources
 Overhaul of existing credit process
 Investments in IT
 Commence Data collection
 Rationalization of Product Management
 Alignment of service concept to cost/benefit
 Availability of credit data
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Thank you
[email protected]
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