Business Continuity and Crisis/Incident Management During incidents that could disrupt the Bank’s business and operations, Business Continuity and Crisis Management supports the ability of senior management to continue to manage and operate their businesses, and provide customers access to products and services. The Bank’s robust enterprise-wide business continuity and crisis management program leverages a multi-tiered, global crisis/incident management governance structure to ensure effective oversight, ownership, and management of crises and incidents affecting the Bank. All areas of the Bank are required to maintain and regularly test business continuity plans designed to respond to a broad range of potential scenarios.
Supplier Management
A third party supplier/vendor is an entity that supplies a particular product or service to or on behalf of the Bank. While these relationships bring benefits to the Bank’s businesses and customers, the Bank also needs to manage and minimize any risks related to the activity. The Bank does this through an enterprise-level third-party risk management program that guides third-party activities throughout the life cycles of the arrangements and ensures the level of risk management and senior management oversight is appropriate to the size, risk, and importance of the third-party arrangement.
Project Management
The Bank has established a disciplined approach to project management across the enterprise coordinated by the Bank’s Enterprise Project Management Office. This approach involves senior management governance and oversight of the Bank’s project portfolio and leverages leading industry practices to guide TD’s use of standardized project management methodology, defined project management accountabilities and capabilities, and project portfolio reporting and management tools to support successful project delivery.
Financial Crime and Fraud Management The Financial Crime and Fraud Management Group leads the development and implementation of enterprise-wide financial crime and fraud management strategies, policies, and practices. TD employs advanced fraud analytics capabilities to strengthen the Bank’s defences and enhance governance, oversight, and collaboration across the enterprise to protect customers, shareholders, and employees from increasingly sophisticated financial crimes and fraud.
Operational Risk Capital Measurement
The Bank’s operational risk capital is determined using the AMA, a risk-sensitive capital model, along with TSA. Effective the third quarter of 2016, OSFI approved the Bank to use AMA. Entities not reported under AMA, use the TSA methodology.
The Bank’s AMA Capital Model uses a Loss Distribution Approach (LDA) and incorporates Internal Loss Data and Scenario Analysis results. External Loss Data is indirectly considered through the identification and assessment of Scenario Analysis estimations. Business, Environment and Internal Control Factors (BEICF) are used as a post-model adjustment to capital estimates to reflect forward-looking indicators of risk exposure.
The Bank’s AMA model includes the incorporation of a diversification benefit, which considers correlations across risk types and business lines as extreme loss events may not occur simultaneously across all categories. The capital is estimated at the 99.9% confidence level.
Although the Bank manages a comprehensive portfolio of insurance and other risk mitigating arrangements to provide additional protection from loss, the Bank’s AMA model does not consider risk mitigation through insurance.
Excluding those events involving litigation, the Bank did not experience any material single operational risk loss event in 2016. Refer to Note 28 of the 2016 Consolidated Financial Statements for further information on material legal or regulatory actions.
Model Risk
Model risk is the potential for adverse consequences arising from decisions based on incorrect or misused models and their outputs. It can lead to financial loss, reputational risk, or incorrect business and strategic decisions.
WHO MANAGES MODEL RISK
Primary accountability for the management of model risk resides with the senior management of individual businesses with respect to the models they use. The Model Risk Governance Committee provides oversight of governance, risk, and control matters by providing a platform to guide, challenge, and advise decision makers and model owners in model risk related matters. Model Risk Management monitors and reports on existing and emerging model risks, and provides periodic assessments to senior management, Risk Management, the Risk Committee of the Board, and regulators on the state of model risk at TD and alignment with the Bank’s Model Risk Appetite. The Risk Committee of the Board annually approves the Bank’s Model Risk Framework and Model Risk Policy.
HOW TD MANAGES MODEL RISK
The Bank manages model risk in accordance with management approved model risk policies and supervisory guidance which encompass the life cycle of a model, including proof of concept, development, validation, implementation, usage, and ongoing model performance monitoring. The Bank’s Model Risk Management Framework captures key processes that may be partially or wholly qualitative, or based on expert judgment.
Business segments identify the need for a new model or process and are responsible for model development and documentation according to the Bank’s policies and standards. During model development, controls with respect to code generation, acceptance testing, and usage are established and documented to a level of detail and comprehensiveness matching the materiality and complexity of the model. Once models are implemented, business owners are responsible for ongoing performance monitoring and usage in accordance with the Bank’s Model Risk Policy. In cases where a model is deemed obsolete or unsuitable for its originally intended purposes, it is decommissioned in accordance with the Bank’s policies.
Model Risk Management and Model Validation provide oversight, maintain a centralized inventory of all models as defined in the Bank’s Model Risk Policy, validate and approve new and existing models on a pre-determined schedule depending on regulatory requirements and materiality, monitor model performance, and provide training to all stakeholders. The validation process varies in rigour, depending on the model type and use, but at a minimum contains a detailed determination of: • the conceptual soundness of model methodologies and underlying quantitative and qualitative assumptions;
• the risk associated with a model based on complexity and materiality; • the sensitivity of a model to model assumptions and changes in data inputs including stress testing; and
• the limitations of a model and the compensating risk mitigation mechanisms in place to address the limitations.
TD BANK GROUP ANNUAL REPORT 2016 MANAGEMENT’S DISCUSSION AND ANALYSIS
89
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112 |
Page 113 |
Page 114 |
Page 115 |
Page 116 |
Page 117 |
Page 118 |
Page 119 |
Page 120 |
Page 121 |
Page 122 |
Page 123 |
Page 124 |
Page 125 |
Page 126 |
Page 127 |
Page 128 |
Page 129 |
Page 130 |
Page 131 |
Page 132 |
Page 133 |
Page 134 |
Page 135 |
Page 136 |
Page 137 |
Page 138 |
Page 139 |
Page 140 |
Page 141 |
Page 142 |
Page 143 |
Page 144 |
Page 145 |
Page 146 |
Page 147 |
Page 148 |
Page 149 |
Page 150 |
Page 151 |
Page 152 |
Page 153 |
Page 154 |
Page 155 |
Page 156 |
Page 157 |
Page 158 |
Page 159 |
Page 160 |
Page 161 |
Page 162 |
Page 163 |
Page 164 |
Page 165 |
Page 166 |
Page 167 |
Page 168 |
Page 169 |
Page 170 |
Page 171 |
Page 172 |
Page 173 |
Page 174 |
Page 175 |
Page 176 |
Page 177 |
Page 178 |
Page 179 |
Page 180 |
Page 181 |
Page 182 |
Page 183 |
Page 184 |
Page 185 |
Page 186 |
Page 187 |
Page 188 |
Page 189 |
Page 190 |
Page 191 |
Page 192 |
Page 193 |
Page 194 |
Page 195 |
Page 196 |
Page 197 |
Page 198 |
Page 199 |
Page 200 |
Page 201 |
Page 202 |
Page 203 |
Page 204 |
Page 205 |
Page 206 |
Page 207 |
Page 208 |
Page 209 |
Page 210 |
Page 211 |
Page 212
