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How to Forecast Interbank Payment Flow in Large Value Payment System on a Designated Time

How to Forecast Interbank Payment Flow in Large Value Payment System on a Designated Time. Song PAN Academy of Mathematics and Systems Science Chinese Academy of Sciences Payment and Settlement Department The People ’ s Bank of China. Major Payment Systems In China.

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How to Forecast Interbank Payment Flow in Large Value Payment System on a Designated Time

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  1. How to Forecast Interbank Payment Flow in Large Value Payment System on a Designated Time Song PAN Academy of Mathematics and Systems Science Chinese Academy of Sciences Payment and Settlement Department The People’s Bank of China

  2. Major Payment Systems In China • Payment service providers • PBC, Banks, PCOs • Payment Infrastructure • CNAPS, LCHs/CIS, CUPS/EFTSRBI • Oversight of Payment Systems • Risk-based approaches

  3. Payment Service Providers • PBC: dual roles • Overseer and service provider • Clearing and settlement: CNAPS, LCHs • Banking inst.: major service providers • Over 100K banking inst. • Various methods of payment • Payment and clearing organizations: supplement • Non-financial institutions authorized by PBC • Innovation of methods and channel

  4. Payment Infrastructure • HVPS in 2007 • Direct participants: 1569 • Indirect participants: about 72,000 • Vol. of trans.: 172m, 700 k/BD • Val. of trans.: CNY 532.9t, 2.1t/BD • Bus. Days: 250 • CNAPS: HVPS+BEPS • BEPS in 2007 • Direct participants: 1545 • Indirect participants: over 70,000 • Vol. of trans.: 8.77m, 255 k/BD • Val. of trans.: CNY 22t, 63b/BD • Bus. Days: 344

  5. Payment Infrastructure • LCHs/CIS • LCHs in 2007 • About 340 in cities and 1800 in co. towns • Direct participants: banking inst. • Vol. of trans.: 440m, 1.76m/BD • Val. of trans.: CNY 72.4t, 29.6b/BD • Bus. Days: 250 • CIS in 2007 • Participants: over 57,000 banking inst. • Limit on trans.: less than CNY 500 k • Settled by BEPS • Vol. of trans.: 1.8m, 5.2 k/BD • Val. of trans.: CNY 76b (220m/BD) • Bus. Days: 344 • CIS: benefits check to be used nationwide

  6. Payment Infrastructure • CUPS in 2007 • Vol. of trans.: about 2.47b, 6.76m/BD • Val. of trans.: about CNY 3.1t, 8.49b/BD • Oversea services: about 30 economies • EFTSRBI in 2007 • EFTS for Rural Banking inst. • Participants: over 3900 • Vol. of trans.: 3m, 12 k/BD • Val. of trans.: CNY 72b, 288m/BD

  7. What is Important? • LVPS in value • Weight of LVPS: over 90% • LVPS in Volume • Weight of LVPS: less than 10% • LVPS: no credit, systemic risk • Operational risk: technology • Liquidity risk: banks and CB

  8. Net Liquidity of Participants • Balance in Settlement Institution • LVPS: deposit in PBC • Effected by required reserve policy • Net Payment = Out-payment – In-Payment • In-payment: received from other participants • Out-payment: sent by a participant • Lending Behavior in money market • Time difference between closing time of money market and cut-off time of LVPS • Borrowing before or late: if late, other participants shall wait • Briefly speaking, the total amount in money market per BD is about 5% of LVPS total Value

  9. Background of Problem--viewpoint of participants • Liquidity risk refers to the uncertainty that counterparty can not settle debt as scheduled time but may settle it at a later time. • For each participant, liquidity risk mainly comes from time lag between origination and settlement. • If a participant overestimate incoming funds from other participants , it may face a shortage of liquidity which would make the participant can’t satisfy its reserve requirement or take on high cost of borrowing. • Forecasting interbank funds is important for participants.

  10. Background of Problem--viewpoint of system overseer • Forecasting interbank payment flows is also important for system overseer, central bank. • RTGS system has a network topology, a participant’s settlement delay might trigger system congestion (gridlock). • The optimal settlement method for a participant is not optimal for the system. • Forecasting interbank payment flows can help system overseer to monitor participant, and might achieve an optimal status of the system.

  11. Time Series of LVPS Transaction Volume

  12. Basic Statistics of LVPS Transaction Volume (in billion) total period period I period II Mean 576.83 419.79 763.64 Median 516.83 403.75 710.84 Min 151.16 151.16 271.12 Max 2216.55 968.59 2216.55 Std. 249.79 106.45 242.79 ** Period I refers to sample period before the reserve requirement ratio adjustment(July,2006) ** Period II refers to sample period after the reserve requirement ratio adjustment

  13. Time Series of Transaction Volume of Typical Participants

  14. Time Series of Net Payment of Typical Participants

  15. Basic Characters of Interbank Payment Flows • Not subject to normal distribution • Nonstationary • Fat-tail • Stochastic Volatility • Autocorrelation • Structural change betweens different periods

  16. What We Can Provide • Number of Banks four representative participants • Data Length daily data from June 2005 to April 2007 • Details the amount received the amount sent number of transactions

  17. What We Expect • Get proper forecasting models on the amount received, the amount sent and the number of transactions, and forecast effect of payment flow on liquidity on a designated time. • Analyze the statistical property of each commercial bank’s payment flow. • Build models based on bank’s own payment flow. • Forecast results should have higher accuracy.

  18. Thanks

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