Building a Bridge between Risk and Finance to Address IFRS 9 and Stresstesting

Transcription

1 SAS FORUM PORTUGAL 2017 Building a Bridge between Risk and Finance to Address IFRS 9 and Stresstesting Martim Rocha SAS Experience your new possible #SASFPT17 C opyr i g ht 2016, SAS Ins titut e Inc. All rights res er ve d.

2 The Financial Services Landscape Intermittent growth: changing interest rate environment, continued pressure on margins Sustained regulatory pressure: enhanced rules lead to higher operating and compliance costs Increasing credit risk and market volitility: further impact expected credit loss, reserves and capital 2

3 Business Regulator y Market Key Drivers Key Challenges Geopolitical changes Emerging technologies (e.g, ML, AI, Block Chain) Digitization and industrialization Accounting standards (IFRS 9, CECL) Stress testing (CCAR, DFAST, EBA) Capital requirements for the trading book (FRTB) Cost reduction, efficiency, repeatability Risk adjusted view integrated with finance Leveraging risk investments for business #SASFPT17 3 Disparate, fragmented systems Insufficient data quality and coverage Siloed, patchwork of data and processes Inefficient infrastructure and execution Resource intensive lack of automation High maintenance costs Redundant investments Lack of appropriate controls Limited or incomplete analyses

4 Risk & Finance To properly account for potential loses and ensure that the appropriate reserves are held, risk and finance must coordinate their activities: risk to estimate credit losses and finance to determine the right level of provisions on the balance sheet, the IFRS9 standard guidelines state the allowances for credit losses in the Balance Sheet should be based on the estimation of Credit Losses, creating a direct link and dependency between the two functions Risk Management Risk enjoys the freedom needed to properly estimate various types of financial risk Financial Management To protect the assets of the institution and ensure its ongoing solvency what Can happen Finance operates within the well-defined and structured rules of accounting needed for standardized reporting what Has happen 4

5 SAS RISK FOCUS AREAS Enterprise Stress Testing CCAR/DFAST/EBA Expected Credit Loss IFRS9/CECL Regulatory Risk Management RWA/FRTB/IRRBB Model Risk Management TRIM/SR 11-7 Credit Scoring PD/LGD/EAD 6

6 IFRS9 AS EXAMPLE OF RISK AND FINANCE INTEGRATION Context: Changes to the IAS 39 approach: a call to action for banks Requirements Calculation of Expected Credit Loss (ECL) for all financial instruments at position level Updated ECL in each reporting period to reflect changes Consideration of future events including macroeconomic data Required: period-based probabilities of default as well as expected loss calculation over the entire duration and thus time-dependent models Challenges Increased volumes of data through detailed and periodic assessment Increased number of models by extending additional (macroeconomic) parameters Calculation of different scenarios due to the interpretation margin Governance, auditability, traceability The IFRS 9 requirements and challenges require the implementation of a modern risk infrastructure C opyr i g ht 2016, SAS Ins titut e Inc. All rights res er ve d.

7 KEY CHALLENGES Significant methodological challenges New models for expected loss components Forecasting Integration of large amount of risk and finance data More automation and better performance of risk and finance systems More granular disclosure More Analytics, more data to feed them, better systems to execute and report C opyr i g ht 2016, SAS Ins titut e Inc. All rights res er ve d.

8 End-to-End Business Process flow Model Library Risk & Finance Data Data Check & Augment Risk Measures Calculator Stage Allocation Review and Challenge Sign-off Management Reporting GL Posting Economic Scenario Regulatory Disclosures The risk function must provide models and methodology to estimate values such as probability of default (PD), cash flows, and loss given default (LGD) over time and subject to multiple economic scenarios. Finance, on the other hand, must process those modelbased results into useful financial information, populating a variety of managerial and regulatory reports, while maintaining the required level of governance and control demanded by both the internal and external audit functions 8

9 SAS F&R Portfolio Common, Integrated Platform Governance & Workflow Enterprise Stress Testing Expected Credit Loss Regulatory Risk Model Risk Management Credit Scoring Reporting & Analytics Business Content Model Implementation Computation Engine Open In-memory Distributed SAS Platform Deployment On-premise Hosted Cloud RaaS

10 KEY CHALLENGES Significant methodological challenges New models for expected loss components Forecasting Integration of large amount of risk and finance data More automation and better performance of risk and finance systems More granular disclosure More Analytics, more data to feed them, better systems to execute and report C opyr i g ht 2016, SAS Ins titut e Inc. All rights res er ve d.

11 ECL MODELLING ECL Calculation task def = Model Execution Environment Input Portfolio, Scenarios, Model Groups, Calculation Methods, Output Vars Quickly Create & Test New Scenarios Review & Analyze Results Input Output #SASFPT17 Portfolio Engine C opyr i g ht 2016, SAS Ins titut e Inc. All rights res er ve d.

12 SAS Risk Management Common, Integrated Platform Governance & Workflow Enterprise Stress Testing Expected Credit Loss Regulatory Risk Model Risk Management Credit Scoring Reporting & Analytics Business Content Model Implementation Computation Engine SAS Platform Open In-memory Distributed Deployment On-premise Hosted Cloud RaaS 7

13 Scenario Management Define/Load scenario Scenario library Change scenarios Scenario Enrichment, model Risk Factors from Base Scenarios Export scenarios EXPLORER DESIGNER

14 Model builders workbench

15 Import models from library

16 Define model assemblage logic Group Models Specify model group templates or user defined logic (UDL) Select models for the templates or UDL Define output variables and transformations

17 Run analysis with the models choosen Associate model with data and products Define running parameters

18 KEY CHALLENGES Significant methodological challenges New models for expected loss components Forecasting Integration of large amount of risk and finance data More automation and better performance of risk and finance systems More granular disclosure More Analytics, more data to feed them, better systems to execute and report C opyr i g ht 2016, SAS Ins titut e Inc. All rights res er ve d.

19 SAS Risk Management Common, Integrated Platform Governance & Workflow Enterprise Stress Testing Expected Credit Loss Regulatory Risk Model Risk Management Credit Scoring Reporting & Analytics Business Content Model Implementation Computation Engine SAS Platform Open In-memory Distributed Deployment On-premise Hosted Cloud RaaS 7

20 Consolidate Results Agregate Results Slice and Dice Loan Level Calculations Reconcile

21 CONSOLIDATE RESULTS - BUSINESS RULES MANAGER Stage Allocation rules #SASFPT17 C opyr i g ht 2016, SAS Ins titut e Inc. All rights res er ve d.

22 ORCHESTRATION AND COORDINATION FOR MODEL USAGE Organize workflow Select Model from model library Group models #SASFPT17 C opyr i g ht 2016, SAS Ins titut e Inc. All rights res er ve d.

23 Agregate, review, adjust, comment Review and Challenge Risk & Finance Workbench: Manual Updates Sign-off Audit tracking

24 Review and sign-off Risk and Finance Workbench: Sign-off Updates log Audit tracking

25 Management Reporting and Workflow Sample artifacts and scripts included

26 Regulatory Reporting Some Reports available in SAS for ECL content Credit Analysis A.1.a - Credit Quality Analysis A.2.a - Collateral Analysis Summary A.3.a - LTV Ratio Analysis by Product Category A.4.a - Credit Concentrations by Product A.5.a - Past Due Analysis A.6.a - Vintage Analysis C.1.a - ECL Scenario Attribution Report Movement and Reconciliation B.1.a - Movement in Expected Credit Loss Allowance (Banks) B.1.b - Movement in Expected Credit Loss Allowance (Banks) B.1.c - Movement in Expected Credit Loss Allowance (FVOCI) B.1.d - Movement in Expected Credit Loss Allowance (Banks) B.1.e - Movement in Expected Credit Loss Allowance (Held to Maturity) B.1.f - Movement in Expected Credit Loss Allowance (Financial Guarantees) B.1.g - Movement in Expected Credit Loss Allowance (Financial Guarantees) B.1.h - Movement in Expected Credit Loss Allowance (Leases) B.2.a - Classification of Financial Assets and Liabilities B.3.a - Financial Assets and Liabilities - Carrying Amount Reconciliation

27 SAS Risk Management Common, Integrated Platform Governance & Workflow Enterprise Stress Testing Expected Credit Loss Regulatory Risk Model Risk Management Credit Scoring Reporting & Analytics Business Content Model Implementation Computation Engine SAS Platform Open In-memory Distributed Deployment On-premise Hosted Cloud RaaS 7

28 SAS IRM Infrastructure for Risk Management Job Flows and Calculation traceability Contextual Documentation

29 SAS IRM Infrastructure for Risk Management The platform meets all the requirements of a modern risk infrastructure. Objectives of the platform Platform must provide a set of services IRM is the materialization of these requirements Anyone can develop apps / content for the platform (SAS, partner, customer) Regulatory changes: New Release in days / weeks (SLA) Update by capability Update as in Appstore Use modern hardware to be super fast (runs in seconds / minutes range) Open standards Content as Open Source Framework for "Regulator Ready" documentation Agile development process Total Test Automation In-Memory und Paralell Processing Self Service Versioning Regulatory processes as BPMN flows Apps as Opensource (SAS Code, Java, R,...) Code = Documentation, Integration withdoxygen Continuos Integration, Up to daily Releases Integrated test framework In-Memory Layer / Scheduler for SAS Code Any code, data, changes are automatically versioned. Each version is executable.

30 Traditionally risk and finance groups within a bank operate separately. Challenge of the new IFRS 9 and CECL regulation, however, requires the two groups to collaborate much more closely. Risk and finance traditionally use separate and dedicated IT applications In order to efficiently manage the IFRS9 and CECL process both functions should share the same IT application. Banks need a solution that provides an integrated, scalable, and controlled risk and finance platform to enable those collaborations. Even more, these two groups can work together easily to see how different business assumptions might affect a bank s financials and create the best strategy for the bank. 30

31 OBRIGADO #SASFPT17