Stress testing for competitive advantage beyond regulatory - PowerPoint PPT Presentation

Stress testing for competitive advantage beyond regulatory compliance Led by: The Center for Financial Professionals & Dennis Bennett, MRMIA Presenters: Tally Ferguson, BOK Financial Venkat Iyer, Santander Chris Smigielski, TIAA Bank

MEET THE PRESENTERS Venkat Iyer Tally Ferguson Director of PPNR Director of Enterprise- Forecasting Wide Risk Santander BOK Financial Chris Smigielski Vice President, Dennis Bennett Director of Model Risk CEO & Founder MRMIA Management TIAA Bank

Components of Performance • Interest Income • Banks are Financial Intermediaries • Loans • Money is the product • Investment Securities • Interest Rate is the Price • Trading Securities • Interest Expense • Asset/Liability Management • Deposits • Interest Rate Risk (Rates/Yield Curve) • Wholesale Funding • Balance Sheet Assumptions • Brokered Deposits • Earnings at Risk (NII simulation) • Provision for Loan Loss • Earnings Trajectory and Likelihood • Net Interest Income (NII) 1

Components of Performance • Non Interest Income • Competitive Landscape • Fees • Product Offerings • Transactions • FinTech Companies • Asset Management • Volume and Price Impact • Brokerage and Trading • Other Services • Stress Testing • Non Interest Expense • Scenario Planning • People • Comprehensive Assessments • Infrastructure • Measure ‘Realistic’ Responses • Fraud 2

Insight into Strategy Decisions Good Bad • Navigate • embarking on a businesses to venture/business financial success line that we in the face of cannot deliver or uncertainty that leads to ruin 1

Insight into Strategy Decisions • Sources of Ruin Uncertainty Unexpectedly Poor Panic Exit Performance o Range of economic o Survived the tail and environmental o impact of event without factors considered too environmental factors knowing it narrow not well modeled o “Anchoring” error o product/service o Controls not put in from behavioral knowledge base too place, or not effective finance limited Images from historicalwallpapers.blogspot.com 2

Insight into Strategy Decision • Uncertainty • CCAR/DFAST imposed discipline on forecasting PPNR from Stress Testing as economic factors • Idiosyncratic stress testing can give us insight into environmental factors a counter to • Litmus tests sources of ruin • What economic factors will lead to deviations from expectations? • What environmental factors will influence our results • For which of these factors can we measure impact on product/service results • How confident are we assessing risk from factors whose impact we cannot measure

Insight into Strategy Decision • Unexpectedly Poor Performance • Apply backtesting discipline we developed for CCAR/DFAST to Stress Testing as idiosyncratic stress tests • Use Expected Shortfall or Conditional VaR approach for products/services where worst case is not known a counter to • Define controls to keep results in the fairway and test them sources of ruin

Insight into Strategy Decision • Panic Exit • If expected shortfall analysis leads to untenable results, don’t Stress Testing as enter the business, or change controls. • Emphasize that low probability events are NOT zero probability events and should not be dismissed. a counter to • Challenge board and executive level risk tolerance decisions – are sources of ruin they really as big as they say they are? • Re-assess risk/return trade-off before exiting.

1 Aligning stress testing with business processes Ø Planning and budgeting • Use stress testing tools to support planning projections for strategic (medium to longer term) and budget (typically one year) decisions • Use of macro-sensitive and driver based models in addition to traditional bottoms-up FP&A methods will increase transparency and flexibility of the budget process Ø Capital allocation • Cascade top of the house stress absorption capital to individual LOB/products • Use of granular PPNR and loss models will assist downward allocation of risk based capital. Variance between base and stress scenarios provide good insights into LOB capital requirements and future scenario design • Granular models enable product level risk and return trade-offs Ø Portfolio optimization • New products and initiatives can be assessed for relative risk-return attractiveness • Constrained optimization frameworks can be built with risk, return and capital targets and/of constraints • Mix of segments within or across products can be assessed within the optimization objectives

2 Planning: Revenue components and stress drivers PPNR = Pre-Provision Net Revenue § PPNR components: Interest income, Interest Expense, Non-interest income, Non-interest Expense § Interest income is driven by loan balances and yields § Generally declines under stress due to balance contraction and lower yields on new and variable rate loans. § Other interest income moves due to changes in securities run-off to optimize the balance sheet § Interest expense driven by deposits for most commercial banks § Generally decreases under stress due to decline in balances and lower yields § Can be off-set by other borrowing costs based on funding requirements § Idiosyncratic events can be used to stress funding constraints § Non-Interest income driven mostly by fee based revenue § Loan, deposit and investment fees decline under stress due to asset and balance declines § Operating lease assets flow through non-interest income – impact similar to loan balances § Assets such as mortgage servicing rights can see significant volatility based on interest rates § Non-Interest expense driven by personnel and operating expenses § Personnel expenses generally decline under stress but trade-offs exist between categories § Operating lease depreciation, operational loss and FDIC insurance expenses can drive NIE higher

3 Planning: Methodologies for revenue components Total Balance approach Methodology summary § Total Balance and component approaches practiced § Total balance used when assets/liabilities are less structured or high volatility in component level drivers Balance/Line growth Utilization Book Yield § Non maturing deposits models § Revolving lines of credit § Component approaches preferred for structured assets such as amortizing term loans Component approach § Combinations of statistical and expert judgement models § NII approaches have been enhanced through: Existing § Rigorous model risk management through SR11-7 New Book book § Quantitative teams collaborating closely with business experts: Developers and validators § Judicious use of properly governed expert Originations judgement/qualitative approaches Contractual § Better understanding of business drivers : amortizations/ Yields Relationship between pricing, originations and risk yields Prepayment drivers § Use of component level build-up where feasible Prepayment Amortization – § Improvements in aggregation process: integrating models Loan PPNR and loss models implementation in a characteristics seamless manner

4 Planning – Benchmarking with models Model with Internal data Model with industry data 14,000 12,000 10,000 8,000 6,000 4,000 2,000 • Internal data is typically more granular but can have limited history – may not capture multiple economic cycles • External data may not have desired granularity but can provide multiple economic cycles • Benchmark models with external data provides useful comparisons with internal trends • Can be used to assess: • Consistency of scenario projections • Difference in sensitivity between internal and market trends • Similarity/difference in macro economic drivers • Influence of multiple economic cycles on macro sensitivity

5 Portfolio optimization illustration Return-to-Risk Ratio: Base Risk Adjusted Yield/(Base - Stress) 5.35 4.65 Impact of new 5 product 3.13 2.93 Risk Adjusted Yield by Scenario 2.44 2.26 2.18 3 2.03 1.97 1.89 1.80 1.50 10.0% 1.20 1.19 0.93 0.93 1 8.0% 6.0% 4.0% 2.0% 0.0% Legend: Products/Business Lines -2.0% (Risk Adj. Yield) Base Adverse Severely Adv • Risk can be defined as variance from base to stress … combine PPNR and provisions • Portfolios/products can be ranked on the basis of risk or return-risk • Provides insights into • What portfolios provide excess return for the amount of risk taken? • Are scenarios adequately stressing the material portfolios? • Is a new product/initiative accretive to the portfolio in terms of risk-return? • How to optimize the mix of products in a portfolio

SWOT Analysis – Risks and Opportunities • Stress Testing • Strengths • Scenario Planning / Systems and People • Comprehensive Assessments • Measure ‘Realistic’ Responses • Risk Appetite/Governance • Weaknesses • Data / Modelling • Competitive Landscape • Product Delivery Preferences • Branch Complements Electronic Delivery 1

SWOT Analysis – Risks and Opportunities • Threats • Non-Bank Competition (Amazon) • Rising Rates & Flatter Yield Curve • Strategies for a Dynamic Marketplace • Opportunities • Artificial Intelligence and Machine Learning • Enhanced Analytical Capabilities • Enhanced Service Capabilities • Automation to Reduce Operating Costs • C-suite more Risk-attuned than 10 years ago 2