Technology Solutions for Credit Risk 2.0

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<h2>A new credit risk universe</h2>

<p class="MsoBodyText">The centuries-old mechanisms of credit, and in particular the ways in which they are assessed and analyzed, are in the throes of a revolution. Built on the emergence of new credit instruments, devised by the world’s Financial Institutions (FIs), and propelled by innovative new technologies that are increasing the speed, flexibility and risk profile of the lending market, this revolution is reshaping the credit landscape.</p>

<p class="MsoBodyText">Yet this is only the latest credit revolution to occur. With the introduction of internal ratings-based models, the Basel II regime heralded a step-change in the way that banks systematized their credit assessment and analysis in the mid-2000s. And, in the decade since the operationalization of the Basel II Accord, the market has continued to develop, driven by another revolution – <em>a digital revolution </em>– that has ushered in new capabilities, rising expectations, and a range of new risks.</p>

<p class="MsoBodyText">Riding this wave of innovation, credit and its associated processes are, once again, poised at the brink of a totally new credit risk environment. We call this new normal ‘Credit Risk 2.0’, and we believe it is defined by three key factors:</p>

<ul>
<li>The emergence of new ‘risk-aware’ accounting standards, prompted by new measures like IFRS 9¹ and the CECL² regime. Both are altering the core of credit risk, down to the fundamental nature of how default risk is calculated.</li>
<li>A new focus from regulators on market-linked contingent credit in the trading book (such as Credit Valuation Adjustment (CVA), Standardized Approach for measuring Counterparty Credit Risk (SA-CCR) and Fundamental Review of the Trading Book CVA (FRTB CVA))³. In the wake of the financial crisis, FIs are moving to adopt clearer, more stringent and sustainable practices for measuring and managing counterparty risk.</li>
<li><!--[if !supportLists]-->•New computational approaches to assessing credit and credit risk – changes to the underlying mathematical models, such as new graph-based approaches and other similar innovative computational techniques.</li>
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<h2>Trading on existing strengths</h2>

<p class="MsoBodyText">The Credit Risk 2.0 revolution can be seen most dramatically in the banking book, although it is not confined to it. In the trading book a ‘credit transformation revolution’ is also taking place, as FIs</p>

<p class="MsoBodyText">increasingly take on highly collateralized exposures, converting credit risk into contingent market risk and operational risk. In the wake of this transformation, a range of new analytics is emerging, such as Value at Risk (VaR)-style margin analytics and Margin Valuation Adjustments (MVA). We are also seeing the rise of new operational issues and challenges impacting the management of liquidity.</p>
Despite challenges, credit risk analytics and methodologies in the trading book (such as CVA, CCR and margin models) all draw on a well-established theoretical framework going back many years. While CVA and MVA models may be breaking new ground, we would argue that overall they are simply signposts along the long evolutionary path of market-linked credit models, which dates back to Merton’s framework⁴ for calculating implied default rates from equity prices. Equally, while some of the Profit &amp; Loss (P&amp;L) practices, performance analytics and risk attributions associated with them may be relatively recent phenomena, broadly they draw on work that is relatively well established. In short, although Credit Risk 2.0 is driving significant changes in the trading book, systems and processes will continue to evolve and cope – as they have been doing for years.</div>

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<h2>Real revolution in the banking book</h2>

<p class="MsoBodyText">In contrast, we believe that the methodologies and technology underpinning models in the banking book are undergoing a profound structural revolution. In this report we will argue that it will require considerable mathematical and structural development to bring them into line with the demands of Credit Risk 2.0.</p>

<p class="MsoBodyText">To cope, we believe FIs need a new methodological and technical structure for their credit risk processes, one that is able to account systematically for the many idiosyncratic properties of banking book products. To do this it should encompass the frameworks needed to:</p>

<ul>
<li>Analyze the performance of loans.</li>
<li>Integrate behavioral factors.</li>
<li>Properly analyze the risk embedded in the contingent components of banking book products (so-called <em>optionality</em>).</li>
</ul>

<p class="MsoBodyText">As credit structures change, the character of the analytics used to analyze them will depend on the legal and operational context in which credit resides – what it is used for and how it is delivered. So, for example, while bonds and loans are similar products, they operate in different legal and market environments, with different consequences for how they are assessed and analyzed.</p>

<p class="MsoBodyText">This report examines the shifts in the overall credit ecosystem that are driving these changes, and the technical systems that FIs will require to handle them.</p>

<h2>Getting the technology right</h2>

<p class="MsoBodyText">Credit risk is a huge subject, so we will take a broad view of the evolving landscape, signposting the critical issues and aspects of the credit risk market structure and analytical environment that we think are often overlooked.</p>

<p class="MsoBodyText">Our report doesn’t set out to provide a directory of new credit products or credit analytics. Instead, it argues that there has been a structural shift in the way that credit is provided, consumed and analyzed. Then it examines the consequences of this from a technology perspective, and how FIs can optimize their systems to cope.</p>

<p>Credit risk exists within an operational and analytical ‘value chain’, and credit analytics does not exist independently, but as part of a process. We will therefore begin by defining the background to Credit Risk 2.0, and then examining the value chain itself⁵. We will then consider the supply-side landscape, assessing how vendors are meeting their clients’ demands now, and examining the challenges they will face in providing the most effective solution for FIs in the new credit universe.</p>

<p class="MsoBodyText">The report uses Chartis’ RiskTech Quadrant^® to explain the structure of the market. The RiskTech Quadrant^® uses a comprehensive methodology of in-depth independent research and a clear scoring system to explain which technology solutions meet an organization’s needs. The RiskTech Quadrant^® does not simply describe one technology solution as the best solution; it has a sophisticated ranking methodology to explain which solutions would be best for buyers, depending on their implementation strategies.</p>

<p class="MsoNormal"><em>To reflect the relative maturity and focus of credit risk solutions across the landscape, we have developed two quadrants: one each for the trading and banking books.</em></p>

<p class="MsoBodyText">We have assessed the following vendors of credit risk systems and technology: AxiomSL, Bloomberg, Broadridge, Calypso, CME, CompatibL, Finastra, FIS, IBM, ICE, IHS Markit, Infosys, InfrasoftTech, Intellect Design, ION Trading, Kamakura, Loxon, Moody’s Analytics, MSCI, Murex, Numerix, Oracle, Prometeia, Quantifi, Quaternion, Sageworks, SAS, StatPro, TCS, TriOptima, Vertiv, Wipro, Wolters Kluwer and zeb.</p>

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<p class="MsoNormal">^{<em>1 The acronym IFRS is short for ‘International Financial Reporting Standard’. For more on IFRS 9, see our report IFRS 9 Technology Solutions Market Update, 2017.</em>}</p>

<p class="MsoNormal">^{<em>2 Note that when we refer to CECL in this report, we mean the US Generally Accepted Accounting Principles (GAAP) Current Expected Credit Loss (CECL) accounting standard.</em>}</p>

<p class="MsoNormal">^{<em>3 Credit generated from derivatives and other instruments, where changes in market value can impact the amount of related credit exposure.</em>}</p>
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<p class="MsoNormal">^{<em>4 Named after economist Robert Merton.</em>}</p>

<p class="MsoNormal">^{<em>5 In terms of front-office activities, enterprise risk analytics and so on.</em>}</p>
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