Spatial financeWhere capital meets hazard, exposure and transition
Network science and contagion for payments and market infrastructure
Network science represents payment and market infrastructure as nodes and links: participants,سیستەمەکان, settlement banks and providers. On this platform it maps dependencies, identifies critical nodes and simulates how a failure spreads.
Network science and contagion study how the structure of connections among entities shapes the spread of failures, information and disease. It provides tools to analyse interdependent infrastructure, supply chains and financialسیستەمەکان. In financial stability, cyber and digital resilience and digital public infrastructure, network science identifies critical nodes and pathways through which shocks propagate across sectors. It informs targeted protection and diversification to limit cascades. The canonical description is onthe STEM Commons.
Payment flow networks
Interbank payment flows are analysed as networks to find participants whose delays would most affect others’ liquidity.
Shared provider mapping
Dependencies of institutions on cloud, messaging and software providers are mapped to show concentration that individual views miss.
CCP membership networks
Common membership across CCPs is mapped to show how one member default could affect several clearing houses at once.
03چاودێری
Network analysis.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Network analysis
Payments and market infrastructure · Network science and contagion · Run R-7933
Single point of failureGRA · Payments and Market Infrastructure
هێڵکاری پشتبەستن
nodes: assets · edges: dependencies
Most central nodes
N3
0.16
11
Critical
N4
0.31
14
ئاسایی
N5
0.32
9
ئاسایی
N6
0.41
14
ئاسایی
Cascade size under removal
Network analysis: the screen’s structure, terms and states for Payments and market infrastructure.ناو و بەهای نموونەیی؛ دیزاینێکە، نەک تۆمار یان سیستەمی ڕاستەوخۆ.
04داتا
What the method consumes.
Datasets and records used by network science and contagion on this platform, with the role each plays and the label its values carry. Sources are listed inthe source register.
داتا
ڕۆڵ
ناونیشان
Payment system transaction data
Flow networks
چاودێریکراو
Third-party registers
Provider dependencies
REPORTED
CCP membership lists
Clearing networks
ئامارە بڵاوکراوەکان
05Stress test
How a shock to assets becomes a system loss.
The equity the system loses after interbank contagion, against the initial hit, as leverage, interconnection and recovery rates change, the core of a macroprudentialتاقیکردنەوەی فشاری. Teaching model with stated illustrative values, not a prediction.
کۆنترۆڵەکان
Fall in external assets
2.0%
Leverage (assets over equity)
10 times
Interbank share of assets
10%
Recovery on interbank claims
40%
Banks in the system
20
Core banks
20% of banks
خوێندنەوەکان
Equity lost to the initial shock
18.0%
Equity lost after contagion
45.0%
Added by contagion (DebtRank)
27.0 points
Banks in default
0
ژمارە، ڕێگا و سەرچاوەکان
Round
System equity lost (%)
Banks in default
0
18.00
0
1
28.80
0
2
35.28
0
3
39.17
0
4
41.50
0
5
42.90
0
6
43.74
0
7
44.24
0
8
44.55
0
9
44.73
0
10
44.84
0
11
44.90
0
12
44.94
0
13
44.96
0
14
44.98
0
15
44.99
0
16
44.99
0
17
45.00
0
18
45.00
0
19
45.00
0
20
45.00
0
21
45.00
0
22
45.00
0
23
45.00
0
24
45.00
0
25
45.00
0
26
45.00
0
27
45.00
0
28
45.00
0
29
45.00
0
30
45.00
0
ڕێگاکان
DebtRankBattiston and others (2012), Scientific Reports 2:541
Differential DebtRankBardoscia and others (2015), PLOS ONE 10
Contagion in financial networksGai and Kapadia (2010), Proc. R. Soc. A 466
Clearing in financial networksEisenberg and Noe (2001), Management Science 47
پەنجەی نادڵنیایی (مۆنتی کارلۆی پارامیتەر) Spiegelhalter, Pearson و Short (2011)، Visualising uncertainty about the future، Science 333
هەستیاریی یەک-یەک (تۆرناد) Saltelli و ئەوانی دیکە (2008)، Global Sensitivity Analysis: The Primer، Wiley
داتا
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.
How a shock to assets becomes a system loss. Illustrative teaching model: it runs on the values set by the controls, not on measured data. Methods: DebtRank (Battiston and others (2012), Scientific Reports 2:541); Differential DebtRank (Bardoscia and others (2015), PLOS ONE 10); Contagion in financial networks (Gai and Kapadia (2010), Proc. R. Soc. A 466).
Network data are often incomplete or confidential. Static network models may miss adaptive behaviour during cascades.
07Exposure, loss and capital
What it means for exposure, loss and capital.
The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.
Transmission channels
How a shock in network science and contagion for payments and market infrastructure reaches credit, market, underwriting, liquidity and operational risk, and feeds back.
Channel structure after the Basel Committee’s work on climate-related risk drivers and transmission channels; links shown are typical paths, not estimated exposures.
NGFS climate scenarios · Network for Greening the Financial SystemIFRS S2 Climate-related Disclosures · ISSBTCFD recommendations · Financial Stability Board TCFDPrinciples for the effective management of climate-related financial risks · Basel Committee on Banking Supervision
What are the limits of network science and contagion in this field?
Network data are often incomplete or confidential. Static network models may miss adaptive behaviour during cascades.
How are results checked?
Models are checked by reproducing observed cascades and outbreaks. Robustness of results to missing or uncertain links is tested.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Reportsis the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
Global Risks Allianceپارەدان و ژێرخانی بازاڕسیستەمە ستراتیژییەکانسیناریۆ و تاقیکردنەوەی گوشار
Editors and the expert reviewers named on each article decide what we publish. Funders and partners do not review or approve articles before publication.
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