1. Delta Capita Project Contagion Risk 22nd August 2018 – Project update
Edward Adcock
Sritik Sinha
Toby Alfred-Jones
© COPYRIGHT | Delta Capita | CONFIDENTIAL

2. 01. Project Overview

3. Project Overview Project Outline: Project Objectives:
To develop software that represents the UK banking system as a system of connected agents and model the risk of contagion by applying stress events in some part of the financial system, e.g. deposit withdrawals.
Project Objectives:
Model the complexity of the financial system when a significant shock event happens to one or more institutions and the subsequent spreading of contagion using the agent-based modelling paradigm.
The model should take into account the interconnected relationship between liquidity and solvency via interactions of agents that are subject to regulatory constraints (Basel III & IV).
To be able to simulate the future contagion risk in a large number of scenarios.

4. Project Overview Project Use Cases: Project Delivery:
Root cause of the contagion risk – The model helps to identify key contagion channels (e.g. credit channels) or vulnerable nodes (i.e. agents that can trigger wide-spread contagion losses).
Finding measures of policy effectiveness – The model helps to understand effectiveness of policy measures targeting liquidity of solvency conditions (i.e. Basel III regulation – Liquidity Coverage Ratio and Net Stable Funding Ratio).
Simulation - The future contagion risk based on the behaviours of agents and external factors / contagion channels in many scenarios.
Project Delivery:
Target Audience – Major UK banking institutions looking to reduce their contagion exposure by assessing their exposure to asset devaluations, deposit shocks and default exposures and regulators looking at financial stability and liquidity to determine the robustness of the financial system and its resilience to shocks and contagion.
Competitive Advantage – By assessing their exposure to shocks and contagion the client bank can take actions to defend themselves prior to any shock taking place, such as securing credit or reducing exposure to key contagion channels.

5. 02. Software

6. Software Six Step Process:
Funding Shock (initial step) / Asset manager redemptions (subsequent steps)
Sufficient liquidity buffer
Replacing interbank funding
Fire sales
Direct effects on funding costs
Indirect effects on funding costs
Default cascade
Process is repeated until no further defaults occur (system is in equilibrium)

7. Software Demo Software
Agent-Based Model – Simudyne software (2000 lines of code) potential to build own software (faster, no server interaction and not using most of the features).
Global User Interface – Java JFrames framework (2500 lines of code) more advanced GUI building tools are available but significant development time required.
Simulations – Single simulations can be run changing the global parameters, balance sheet and shock event each time.
Visualization – Java package ‘GraphStream’ used as Power Bi and Tableau do not allow interactive simulations.
Initialization – All agents were initialized with their balance sheet data as reported at 31st Dec 2017.
Demo

8. 03. Future Development

9. Future Development
Multiple simulations and collective results – running multiple simulations across a range of values for either shock event or balance sheet.
Random network generation – creating algorithm to create random networks between the agents based on total amount borrowed and lent on their balance sheets.
User interface voice integration – allow users to control the parameters and simulation results via voice control (snips?)
Global user interface – continue to develop and expand the global user interface