Liquidity Forecasting Christian Pichlmeier, MUFG 1
Disclaimer The views expressed in this presentation are mine and not necessarily the views of MUFG Union Bank. 2
Traditional Forecasting process 3
Forecasting Inputs/Outputs Credit Rating assumption Base Scenario: Target Adverse Scenario: § Assumes Business as Funding Gap % Targeted § Access to unsecured (Assets, usual. Continue to issue Allocation (as Deposits) funding sources may be determined unsecured funding. by funding curtailed especially § Hold a certain % of FHLB strategy) assuming rating capacity open. downgrade impact. Cost of Funds § BRCD issuance increasing. Funding portfolio: Fed Funds, CP/CD, FHLB, BRCD, Repo 4
Balance Funding Gap and Funding Strategy Funding Strategy: available funding sources and associated costs, concentration risk, TLAC Funding Gap: projected loan growth, required buffer assets, RWA 5
Limitations Reliance on management Reliance on Financial Reliance on line of developed funding Reporting to calculate business forecasts strategies the funding gap Changes in business strategy, financial User errors through markets and business manual entries environment, regulatory standards or tax laws 6
Build-out of Cash Flow Forecasting 7
Components of a CF Forecast Legal Entity / Business Line / Currency Intercompany Contractual Maturities New Business Transactions 1 Contractual Cash Flow 2 New Business Other potential events Funding Renewals Customer Options that may impact liquidity 3 Behavioral Assumptions Reasonable assumptions about future behavior of assets, liabilities and off- balance sheet exposures Include sufficient detail to reflect the capital structure, risk profile, complexity, currency exposure, activities of the company 8
Considerations to develop CF Forecasting • How reliable is the business forecasting process? • How granular is the forecast? Does the business provide a breakdown by the required EPS categories (new business, behavioral assumptions, contractual)? • How do we bridge between O/N and the first business line input (commonly 1 month)? • How timely is the business forecast provided and how often is it updated? 9
CF Forecast Framework Development Reliability of Forecast Granularity of the Frequency Forecast of Updates Tenor Buckets 10
CF Forecast Starting Point Business tends Reliability of to overestimate Forecast Loan and Deposit Growth Short Term projections to Frequency be updated Business Granularity daily, LT of Updates Breakout and projections of the Treasury view monthly Forecast don’t align EPS requires Tenor short term and long term CF Buckets projections up to 1 year 11
Case Study: Deposit Forecast - Granularity Line of Business Segmentation (Industry Product Type Type) Wholesale Banking Commercial Banking Checking Accounts Saving Accounts Trust Checking Accounts Saving Accounts Financial Institutions Checking Accounts Saving Accounts Government Deposits Checking Accounts Consumer Banking Retail Deposits Checking Accounts Saving Accounts Promotional Deposits Saving Accounts CDs 12
Case Study: Deposit Forecast – Historical Analysis (Trend) Trend Analysis Monthly ending balances over a 3 year horizon Monthly Ending Daily Ending Balance Balance Threshold Threshold Regression line Regression line 2015 2016 2017 Total 2015 2016 2017 Total 0.02 0.01 0.29 0.68 >.6 0.24 0.00 0.71 0.78 >.6 The trend analysis visually demonstrates if there is evidence that ending balances follow along a trend line. R 2 is calculated and compared with a threshold (in this case, 0.6). If a trend is identified by surpassing the threshold, the results are used as part of the forecasting process for long-term cash flow predictions. 13
Case Study: Deposit Forecast – Historical Analysis (Seasonality) Seasonality Analysis The seasonality analysis attempts to find out whether a 1 Day of the Week (Represented best in seasonality) Threshold pattern exists either in terms of Mean, Frequency(%) of total, Amount(%) of total days of the week (1) or week of Monday Tuesday Wednesday Thursday Friday Total the month (2) by analyzing Mean f% a% Mean f% a% Mean f% a% Mean f% a% Mean f% a% Mean f% a% frequency and amounts of cash $ (0.05) $ 1.18 $ (0.13) $ (0.41) $ (0.04) $ 0.12 %>60 57% 50% 43% 54% 60% 51% 60% 52% 58% 50% 41% 50% flows over a 3 year horizon. Week of the month (Represented best in date of the month) Threshold Mean, Frequency(%) of total, Amount(%) of total f% = frequency of daily cash Week 1 Week 2 Week 3 Week 4 Week 5 Week 6* Total 2 flows in the same direction as Mean f% a% Mean f% a% Mean f% a% Mean f% a% Mean f% a% Mean f% a% Mean f% a% the mean $ 14.38 $ 15.53 $ (5.58) $ (12.69) $ (5.69) $ (6.73) $ 0.12 %>60 98% 100.0% 91% 97% 79% 77% 100% 100% 83% 90% 100% 100% 41% 50% e.g. for Week 2 data (contains for a total of 3 years every 2 nd We are looking for bell curves which are either to the left or to the right of zero which would indicate seasonality. If observations are spread around the 0 we might not week of the month based on 5 be able to identify seasonality. business days totaling approx. 1 2 180 data points), 91% of these Week of the month Day of the Week cash flows move in the same direction a% = amount of daily cash flows in the same direction as the mean e.g. following example of Week 2 above, of the 91% of those cash flows moving in the same direction equal to 97% of all amounts, meaning those cash flows moving in the opposite * direction equal only 3% of the * absolute cash flow movement. *The frequency of observations is shown for each bin which is determined by the standard deviation of the cash flow movements. 14
Case Study: Deposit Forecast – Final Concept The results of the trend/seasonality analysis is translated into cash flows leveraging the equation of the trend analysis and overlaying it with § potential seasonal patterns. § The forecasted balances based on the quantitative model (dark blue line) are compared to the business forecast (purple line) and provide a check in regards to the validity of the more subjective business forecast. In the shown example below, the trend analysis contributes only a very small portion to the forecasted cash flow while the seasonality overlay § impacts the overall cash flow the most. 15
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