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Riskmanagement-Landschaftder ZukunftDr. Michael WolfPrincipal Business Advisor - Banking

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OVERVIEW

Challenges in the Banking Industry

Solution Approaches and Smooth Transition Paths

Scalability

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CHALLENGESBASEL COMMITTEE IS AWARE OF THE CHALLENGES AND HAS STATED PRINCIPLES TO BE FULFILLED … ANDCALLS FOR ADDITIONAL RISK MEASURES

• Principles for effective risk aggregation and risk reporting• Principle 3: Accuracy and integrity• Principle 4: Completeness (aggregate cross the whole bank)• Principle 5: Timeliness • Principle 6: Adaptability (readiness for a broad range for

on demand ad-hoc requests)• Liquidity Risk

• 30-day liquidity coverage ratio (LCR, 2015) • Net Stable Funding Ratio (NSFR, 2018).

• Credit Valuation Adjustments (CVA) • Consideration of counterparty risk for OTC derivatives

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SUMMARY CURRENT AND NEW REQUIREMENTS ASK FOR NEW SOLUTIONS

“ the IT organization needs to dramatically modernize its IT systems, transforming out-dated data management infrastructure and replacing it with a more up-to-date and superior information environment able to support an entirely new set of requirements.” Gartner, The Information Capabilities Framework, Sep 2011

No firm-wideconsistency in DWH

Regulators

Many end-user IT applications

Classical ITapproach

to cover it all?

Volume Velocity Variety

MarketsCompetitorsClients

Mastering issues fromlegacy systems Mastering issues fromlegacy systems

Fulfill demanding regulatory requirementsFulfill demanding regulatory requirements

Readiness to react to unpredictable environmentReadiness to react to unpredictable environment

Goal: Enterprise Success

Risk aggregation and reportingLiquidity

Credit Valuation Adjustment

Finance

Risk

C I

IT

EU-IT

Consistency

Time to Market

Flexibility

Reliability

SecurityStandards

Cost Reduction

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Challenges in the Banking Industry

Solution Approaches and Smooth Transition Paths

Scalability

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SOLUTION DESIGN PRINCIPLES AND INNOVATIVE TECHNOLOGY

External Data

Internal Unstructured

Data

Other!!!!

Operational System

Operational System

Operational System

Reference Data

Information Management Master Plan

Modern Analytical Framework

Design principles

Technology

consistencies

Target Situation

Banking Analytics Factory

Risk

Finance

CI

Regions

local semi-global globale.g. risk aggregation

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SOLUTION WAY OUT: DESIGN AND INNOVATIVE TECHNOLOGY

External Data

Internal Unstructured

Data

Other!!!!

Operational System

Operational System

Operational System

Reference Data

Information Management Master Plan

Target Situation

Modern Analytical Framework

Design principles

Technology

Banking Analytics Factory

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SOLUTION STEP 1: MOVING END-USER APPLICATIONS TO AN INDUSTRIALIZED ENVIRONMENT

Code

External Data

Internal (Unstructured)

Data

Other!!!!

Operational System

Operational System

Operational System

Reference Data

DWH

DWH

Data Marts

REGULAR IT+ Reliable, controlled, secure- Expensive inflexible, slow- Specification required from

beginning

BUSINESS EXPERT IT+ Fast flexible, easy to start- often: non- compliant with

security standards, not readyfor technological upgrade

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SOLUTION STEP 1: MOVING END-USER APPLICATIONS TO AN INDUSTRIALIZED ENVIRONMENT (SAS ENTERPRISE GUIDE)

External Data

Internal (Unstructured)

Data

Other!!!!

Operational System

Operational System

Operational System

Reference Data

DWH

DWH

Data Marts

T1 DWH

Regular IT development

Self Service IT:

T nT4T3T2

Possibile benefits

• Efficient and easy to use for business experts• Transparent• Audit Trail• Compliant with IT security standards• Deployment: Development, test, production• Person independent developments• Ready for high performance computing• Full flexibility (open for writing code)• Basis for modularization and re-use

(passing to IT)

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SOLUTION STEP 2: SELECTIVELY MOVE ELEMENTS TO CONTROLLED, CONSISTENT AND RE-USABLE IT-ENVIRONMENT

External Data

Internal (Unstructured)

Data

Other!!!!

Operational System

Operational System

Operational System

Reference Data

DWH

DWH

Data Marts

T1 DWH

Regular IT development

T nT4T3T2

Data Model

Analytical Data Stores

End User Applications

Modern SAS Environment(IT and Business Experts)

SAS Data Management(Driven by IT)Data Quality

Data Governance

Master Data Mgmt.

Data Integration

Data Sources, Transformations, Definitions, Methods, Reports

Individual migration

- Successive streamlining

Consistency and re-usability- Repositories, metadata

- With full flexibility- ‘Mirror’ DWH definitions

for reconciliation andcross DWH analytics

IT

Power-User

e.g. Risk Aggregation

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SOLUTION STEP 3: … AND ENABLE FOR EXPLORATION, ANALYTICS AND GENERATION OF DYNAMIC REPORTS

External Data

Internal (Unstructured)

Data

Other!!!!

Operational System

Operational System

Operational System

Reference Data

DWH

DWH

Data Marts

T1 DWH

Regular IT development

Data Model

Analytical Data Stores Modern SAS Analytical Environment

SAS Data ManagementData Quality

Data Governance

Master Data Mgmt.

Data Integration

Data Sources, Transformations, Definitions, Methods, Reports

Individual migration

- Successive streamliningConsistency and re-usability

- Repositories, metadata- With full flexibility- ‘Mirror’ DWH definitions

for reconciliation andcross DWH analytics

IT

Power-User

Generation of dynamic reports Consumer

SAS Visual AnalyticsData Exploration

Data Mining Risk Engines Risk Aggregation

… AND PROVIDE ADVANCED RISK FUNCTIONS

e.g. Risk Aggregation

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THE SAS ANALYTICAL FRAMEWORK PROVIDES BUILDINGBLOCKS TO DESIGN A MODERNRISK IT LANDSCAPE

External Data

Internal (Unstructured)

Data

Other!!!!

Operational System

Operational System

Operational System

Reference Data

DWH

DWH

Data Marts

data sources, content, business rules (stored processes), access authorizations

Meta DataServer

SQL Query builder, free programmable logic, alerts statistics, reporting, stored processes, MS-Office

EnterpriseGuide

Easy-to-use tool: initial data exploration, report generation, deployment, applies stored processes

VisualAnalytics

Pattern recognition, scoring, text mining, optimization, prediction, network analyses

EnterpriseMiner

Credit & market risk, MtM, VaR, Expected ShortfallP&L, simulation (covar., Monte Carlo …), stress test

RiskEngine

Correlated and copula aggregation of VaREconomic capital and RAROC using joint simulation

Firm-wideRisk

Customer Int.: Marketing automation, social media Fraud, AML, ALM, Liquidity, OpRisk, Compliance

Industrysolutions

Pre-

defin

edco

nfig

urab

leex

tend

able

Full

Flex

ibili

typo

wer

ful i

nstr

umen

tssu

cces

sive

str

uctu

ring

Data Management- Integration- Governance- Master Data - Quality IT

tool

s fo

rte

chni

cal a

ndpr

oces

s su

pp.

SOLUTION

The basic toolset

Additional components

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OVERVIEW

Challenges in the Banking Industry

Solution Approaches and Smooth Transition Paths

Scalability

Copyr igh t © 2012, SAS Ins t i tu te Inc . A l l r igh ts reserved.

SCALABLE TECHNICAL OPTIONS: READY FOR MIGRATION TO ENVIRONMENTS FOR HIGH PERFORMANCE AND BIG DATA

ETL, ELT, Message Buses etc.

Hadoop

In-Memory Analytics Engine(s)

Server / Grid

and / or

and / or

Enterprise Data

Warehouse

External Data

Internal Unstructured

Data

Other!!!!

Operational System

Operational System

Operational System

Master Data Reference

Data

Data Marts

TECHNICALSCALABILITY

Dat

a in

tegr

atio

n: R

eal-t

ime,

Nea

r Rea

l-tim

e , B

atch

ReportingMarts

Data Quality, Master Data Management. SAS Metadata

AnalyticalMarts

Data Management

EnterpriseGuide

VisualAnalytics

EnterpriseMiner

Risk engine

Firm-widerisk aggregation

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CONTACT

Dr. Michael WolfPrincipal Business Advisormichael.wolf@sas.com+41 79 322 42 47