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