Confident Credit Decisions using SAS Credit Scoring...247.8 bln TL Assets 153.7 bln TL Loans 140.1...
Transcript of Confident Credit Decisions using SAS Credit Scoring...247.8 bln TL Assets 153.7 bln TL Loans 140.1...
Confident Credit Decisions using SAS Credit Scoring: SME Underwriting
İnci Aksoy, Risk Validation Manager SAS Azerbaijan Analytics Summit 2016 Baku, February 2016
Turkish Banking Sector Overview
Source: Turkstat, Eurostat (for population, median age, population growth, GDP, per capita GDP, unemployment), IMF (for world ranking), CBRT (inflation), Bloomberg (benchmark), Turkstat and CBRT (for CAD/GDP), Treasury and
Turkstat (public debt/GDP), CBRT, BRSA, Treasury and Turkstat (private debt/GDP) Notes: EU indicates EU27 countries (source: population and macro data based on Turkish Statistical Institute)
(1) Based on Turkish Statistical Institute and IMF World Economic Outlook
(2) Upgraded by one notch to Baa3 (investment grade) by Moody’s in May’13. Upgraded by one notch to BB+ (one notch below investment grade) by S&P in Mar’13
(3) Turkish Banking Sector Basic Indicators, BRSA, September 2015
Total Bank #3 52
Total Branch # 12,330
Total Employee # 218,006
Total Banking Size 2,396
billion TL
Europe’s 8th largest economy1 and a member of
G20
Young, dynamic, large and growing population
Sovereign ratings of Baa32/BB+2/BBB- by Moody’s/
S&P/Fitch. First investment grade achieved in Nov’12
(Fitch). Second investment grade achieved in May’13
(Moody’s)
Turk
ey
TR 2014 EU 2014
Population (mln) 78 507
Median Age 30 43
Population Growth (CAGR 2000-2014)
1.4% 0.4%
GDP (€ bln) 602 13,516
World Ranking 18 -
Per Capita GDP (€) 7,784 26,638
World Ranking 631 -
Size of Assets / GNP
Ratio Billion TL
GNP Total Asset Total Asset / GNP (Right axis)
3
SME definition (BRSA):
• Less than 250 employees and
• Annual turnover less than 40 mio TL(*)
There are approximately 3.2 million SMEs in Turkey
Nearly 50% of them are unbanked
As of Q3-2013, SME loans share in total bank loans
is 26%
Key Facts SME Share and
Development of SME loans in Economy
Notes: (*) Changed in November 2012, from 25 TL million TL in line with EU benchmarks
Source : KOSGEB 2011-2013 KOBİ Stratejisi ve Eylem Planı; TÜİK, BRSA Q3 2013 report
99%
79%
55% 50% 59%
26%
Enterprises inaccordance
with EUdefinition
Employment Added value Totalinvestments
Total export Total loans
Background of SMEs in Turkey
SME Loan Development SME definition enlarged
Billion TL
Middle Size Enterprises Small Size Enterprises
Micro Enterprises
247.8 bln TL
Assets 153.7 bln TL
Loans
140.1 bln TL
Deposits+
TL Bonds2
1,274 mln TL
Net Income
22.0 bln TL
12.9%
Bank
CAR
11.0 mln
Active
Customers
1,015 Branches
85%
Share of
ADCs5
19,517 Employees
Ratings Moody’s: Baa3 / Fitch: BBB / S&P: BB+
4th largest private bank and deep rooted
franchise (established in 1944)
Among top 10 most valuable brands6 in
Turkey
Integrated network with widespread branch
coverage and strong presence in digital
Young and qualified workforce serving a
wide customer base
Core-banking focused balance sheet
(highest loans/assets; lowest securities/assets
among peers)
Conservative risk profile and prudent
provisioning policy
Resilient capital base and funding
capability
Shareholders’
Equity
Note: Loans indicate performing loans. ROAE indicates Return on Average Equity
(1) On 24 Jun’14, Fitch affirmed YKB’s Long-Term Foreign Currency and Long-Term Local Currency ratings at “BBB” while downgrading private peers ratings to “BBB-” from “BBB”.
(2) Deposits: TL 136.3 bln, TL Bonds: TL 3.8 bln
(3) Indicates customers with at least one product usage in the last 1.5 years
(4) Group data. Bank-only: 18,430
(5) Share of alternative delivery channels (ADCs) in total comparable transactions
(6) Brand Finance Turkey 100 report 2015 (Yapı Kredi ranked number 10 as of Feb’15)
3 4
Yapı Kredi: A leading financial services group
5%
23% 32%
15%
3%
12%
20%
27%
1%
3%
25%
41%
32%17%
9%
25%31%
24%
57%
Revenues Loans Deposits AssetsUnder
Management
5
Revenues and Volumes
by Business Unit
(9M15)
SME
Private
Corporate
Commercial
Treasury
and Other
Individual
(incl. Card
Payment
Systems)
Retail1 60% 49%
Private Banking and
Wealth Management
Subsidiaries:
International Operations
Corporate and Commercial Banking
Commercial Corporate
Retail Banking
Individual & SME
Card Payment Systems
US$ 356 mln US$ 173 mln US$ 2.0 bln
10.4 mln
cards2
~556K POS
411K
merchants
924 branches
4.2k RMs
4,190 ATMs
3 branches
70 RMs
59 branches
570 RMs
Further
segmented as
mid/large
companies
22 branches
183 RMs
Total
Assets
International / Multinationals
Source: Approximate numbers based on MIS reporting for company information. Asset size data of international operations based on 9M15 BRSA financials
Branch numbers exclude 3 mobile, 1 free-zone, 1 abroad, 1 custody branches (1) Includes individual, SME and private (2) Including 2.1 mln virtual cards
1 branch
22 headcount
~1,500
customers
58% 97%
Subsidiaries:
Malta
US$ 67 mln
L
L = Listed
0.5%
Well-diversified business mix on the back of a customer-oriented and divisionalised service model
Audit Committee
Retail Credit
Department
Corporate & Commercial
Credit Department
CEO
BoD
Risk Reporting Control and
Operational Risk Management
Organizational Structure for Effective Credit Risk Measurement
Internal Audit
Compliance and
Internal Control
Risk Management
Market Risk Management
Credit Risk Management
Two ultimate goals:
To measure the credit risk and take
decisions accordingly and to allow the Bank
to take decisions by maximizing the
Economic Value Added (EVA) of the credit
risk bearing portfolio;
To maximize customer satisfaction,
allowing for short response time and clear
communication.
Credit Risk Management Goals and Requirements to Achieve These Goals...
Requirements to achieve the goals:
EVA-based decisions require the capabilities to
measure the credit risk of the portfolio accurately.
Not only has risk to be measured by using reliable
measurement tools, but also the risk quantification
has to be distributed to all decision-makers;
Customer satisfaction is enhanced with fast,
objective and standardized processes and
decisions. These need to be tailored according to the
customers and their needs.
Credit risk has to be measured, the quantification of the risk has to be distributed and finally
used. Reaching excellence in credit risk management means to reach excellence in these stages.
Measure credit risk via effective analysis;
From all of its dimensions:
client, facility, collateral;
With the maximum break-down: from the facility up to the portfolio;
With clean and up-to-date information;
With efficient and robust measurement tools.
Reaching Excellence in Credit Risk via;
Distribute credit risk measures to make the information available:
At all levels of the organization
where decisions are taken, from the branch employees up to the executive management;
In all systems where decisions are taken automatically;
With different frequency (from real time to monthly);
With a different level of granularity (from facility level to portfolio level).
Use credit risk measures to steer decisions and credit processes as well as influence the behavior of people by;
Creating awareness across the whole
organization;
Using credit risk measures as a key driver during the underwriting, monitoring / collection and work-out processes
Setting credit risk targets to people and monitoring their performance;
Producing analyses and regular reports allowing senior management to take decisions.
MEASUREMENT DISTRIBUTION USAGE
SAS Rating Engine Models run on-line or batch
Decision Engines Management of rules and strategies
SAS Laboratory Environment Model development and monitoring
Other systems (internal and external) Tracking limit - risk, collateral, recovery and
delinquency information
Portfolio Analysis Environment RWA (SAS CRMS) and Credit VaR models calculation
(1)
(2)
(3)
(4)
(5)
(batch)
(batch) (score code)
SME Application PD Rating System Overview
(1)
Internally developed front end and workflow management system for SME
segment Credit workflow management
Credit Risk Data Mart Information gathering, aggregated information
calculations for modeling and reporting
Integrated infrastructure
Facilitates the underwriting process and ensures data quality of credit
proposal
Rating Models
Maintenance and continuous enhancement of rating models is
ensured
Decision Engine
On the basis of the PD and of other key risk information partial decisions
are taken
Front-End System
Presents rating and decision engine results to end users, assigns authority levels based on delivered information
Credit Risk Data Mart
All information are transfered to data mart for monitoring, analysis
and reporting
Yapı Kredi achieved a robust and successful SME Rating System to support daily processes
Accurate Credit Decisions
Credit Risk Data Mart
Other Systems
Underwriting system
700K Applications in 2015
Benefits and effects: Increased Revenue, Decreased CoR and NPL
Effective
management of
Credit Risk
Portfolio
Time efficiency
Reduced operational workload of SME RMs
Rating accuracy
NPL management Proactive Campaigns
Yapı Kredi is confident in IRB application and places great effort to enhance its Rating Systems to achieve
excellence more than the approval of the authority.
All pieces of the infrastructure are in place and all main integrations have accomplished. Minimum data
quality is ensured;
PD, EAD and LGD data are completely integrated and calculations take place in real time (application PD
models) or batch (behavioural PD models and EAD and LGD models);
Model monitoring systems are in place and models are being deployed to monitoring system following the
redevelopments, revisions and other changes.
For model management, SAS Model Manager is planned to be implemented in 2016.
Model inputs’ data quality is an essential part of the process and to support this process SAS Data Flux is
being implemented.
In the meantime RWA calculations will switch from Standardized Approach to IRB thus allowing for a
more precise capital calculation;
In parallel revision on Credit VaR calculations are ongoing together with UniCredit Group and will be
finalised within 2016 as well.
Achievements and Next Steps
Setting-up an effective credit risk management process is a complex process that requires a detailed
initial analysis and plan. To design the target solution with the utmost detail at the very beginning will
eventually speed-up the process and avoid loosing time;
When risk measures start to be used in the decision making process, some of the several
stakeholders might be reluctant to accept the change;
Investing in credit risk management is a long term investment, that requires time both to be put in
place and to achieve the first benefits. However, in the long term it provides the Company with a very
high competitive advantage.
Lessons Learnt
Thank you