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<p>Introduction ix</p> <p>Acknowledgments xv</p> <p><b>Chapter 1 Financial Institutions as Information Processors 1</b><br /> <br /> Financial Institutions’ Raison d’Être 1</p> <p>Cultural Issues 6</p> <p>IT Literacy and the Spreadsheet Deluge 13</p> <p>Other Challenges to Establishing an IT-Savvy Culture 19</p> <p>Notes 25</p> <p><b>Chapter 2 Strategic Hardware and Software Management 27</b></p> <p>Overview 27</p> <p>An Integrated Data Architecture 41</p> <p>Information Processing Efficiency as an Institutional Objective 52</p> <p>A Digression on Unstructured Data 58</p> <p>Notes 60</p> <p><b>Chapter 3 Data, Models, and Information 61</b></p> <p>Model Risk Mania 61</p> <p>Definitions and Epistemology 69</p> <p>Data Quality 73</p> <p>Models and Their Role 79</p> <p>Regulatory Regimes and Guidance 88</p> <p>Notes 99</p> <p><b>Chapter 4 Model Risk Measurement 101</b></p> <p>Three Phases of Model Management 102</p> <p>Model Governance 103</p> <p>Defining Model Risk 105</p> <p>Objectifying the Downside 108</p> <p>Model Risk Attribution: An Information Entropy Approach 121</p> <p>Notes 126</p> <p><b>Chapter 5 The Return on Analytic Assets 127</b></p> <p>Measuring the Productivity of Models 128</p> <p>Complementarity of Data Inflow with Information Processing 132</p> <p>A Digression on Price Taking 134</p> <p>Notes 135</p> <p><b>Chapter 6 Data Risk Measurement 137</b></p> <p>Strategic Data Acquisition 139</p> <p>The Information Conversion Rate 140</p> <p>Other Approaches for Data Risk Assessment 142</p> <p>Notes 143</p> <p><b>Chapter 7 A Higher Level of Integration 145</b></p> <p>Alternate Views of Integration 146</p> <p>Identifying Key Information Cycles 146</p> <p>An Integrated Physical View 149</p> <p>Multidimensional Information Asset Management 151</p> <p><b>Chapter 8 A Strategy for Optimizing the Information Processing Complex 155</b></p> <p>Evaluation 156</p> <p>A Path toward Improvement 160</p> <p>Notes 167</p> <p><b>Chapter 9 Case Studies 169</b></p> <p>The Pricing of Automobile Insurance 170</p> <p>Moody’s KMV 174</p> <p>The London Whale 177</p> <p>The Mortgage-Backed Securities Disaster 178</p> <p>The Value of Annuities 180</p> <p>Notes 182</p> <p><b>Chapter 10 Conclusions 183</b></p> <p>References 189</p> <p>About the Author 193</p> <p>Index 195</p>

<p><b>SEAN C. KEENAN, P<small>H</small>D,</b> is Senior Managing Director-Model Risk Management at a leading international insurance organization. Prior to joining this organization, he was the Quantitative Risk Analytics Leader at GE Capital, Vice President in the Risk Architecture Group at Citigroup, Vice President at Moody's, and Senior Econometrician at Loan Pricing Corporation.</p>

<p><b>A PROVEN APPROACH FOR CREATING <i>and</i> IMPLEMENTING EFFECTIVE GOVERNANCE <i>for</i> DATA <i>and</i> ANALYTICS</b></p> <p><i>"Nearly every month, the media report cases of major blunders by financial institutions in trading, reporting of financial information, and mishandling of customer information, or censure from a regulator caused by a failure in data management or information processing."</i><br /> <b>—From the Introduction</b></p> <p><i>Financial Institution Advantage and the Optimization of Information Processing</i> offers a key resource for understanding and implementing effective data governance practices and data modeling within financial organizations. Sean Keenan—a noted expert on the topic—outlines the strategic core competencies, includes best practices, and suggests a set of mechanisms for self-evaluation. He shows what it takes for an institution to evaluate its information processing capability and how to take the practical steps toward improving it.</p> <p>Keenan outlines the strategies and tools needed for financial institutions to take charge and make the much-needed decisions to ensure that their firm's information processing assets are effectively designed, deployed, and utilized to meet the strict regulatory guidelines.</p> <p>This important resource is filled with practical observations about how information assets can be actively and effectively managed to create competitive advantage and improved financial results. <i>Financial Institution Advantage and the Optimization of Information Processing</i> also includes a survey of case studies that highlight both the positive and less positive results that have stemmed from institutions either recognizing or failing to recognize the strategic importance of information processing capabilities.</p>

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