indistinct from credit risk. of course, at root, effective risk management lies in evaluating the risk models upon which capital allocations and economic decisions are made. regardless of the resources and effort a bank puts into forecasting its risk profile, it ought not make crucial capital allocation decisions based on those forecasts until their accuracy has been appraised. yet forecast evaluation, or “ backtesting ”, procedures to date have received surprisingly little attention in both academic circles and private industry. quite apart from complacency over risk - modeling systems, we must be careful not to foster an expectation that policymakers will ultimately solve all serious potential problems and disruptions. such a conviction could lull financial institutions into believing that all severe episodes will be handled by their central bank and hence that their own risk - management systems need not be relied upon. thus, overreliance on public policy could lead to destabilizing behavior by market participants that would not otherwise be observed - what economists call moral hazard. there are many that hold the misperception that some american financial institutions are too big to fail. i can certainly envision that in times of crisis the financial implosion of a large intermediary could exacerbate the situation. accordingly, the monetary and supervisory authorities would doubtless endeavor to manage an orderly liquidation of the failed entity, including the unwinding of its positions. but shareholders would not be protected, and i would anticipate appropriate discounts or “ haircuts ” for other than federally guaranteed liabilities. as we consider potential shortcomings in risk management against the backdrop of an absence of significant credit losses in derivatives, one is compelled to ask : has the financial system become more stable, or has it simply not been tested? probability distributions estimated largely, or exclusively, over cycles that do not include periods of financial stress will underestimate the likelihood of extreme price movements because they fail to capture a secondary peak at the extreme negative tail that reflects the probability of the occurrence of extreme losses. further, because the experience during crises indicates heightened correlations of price movements, joint distributions estimated over periods that do not include severe turbulence would inaccurately estimate correlations between asset returns during such episodes. the benefits of diversification will accordingly be overestimated. another aspect of the system that may not have been appropriately tested is the set of credit risk modeling systems that have evolved alongside the growth in derivatives. such models embody procedures for gauging potential future

the life of the bond. although the idea of automating certain aspects of contracts is not new, and banks do some of this today, the potential introduction of smart contracts does raise several issues for consideration. for example, what is the legal status of a smart contract, which is written in code? would consumers and businesses rely on smart contracts to perform certain services traditionally done by their banks or other intermediaries? could the widespread automated interaction of multiple counterparties lead to any unwanted dynamics for financial markets? these and other considerations will be important factors in determining the extent of the application of smart contracts. regardless of the application, much of the industry is at a “ proof of concept ” stage of development. these proofs of concept are often simple, experimental uses of the technology on a small scale that help stakeholders understand the potential and limitations of the technology for a specific purpose, which in turn typically lead to refinements and more developed proofs of concept. as such, many potential applications are in their infancy, and the industry may still be several years away from an application that is ready to be fully implemented. even so, the industry seems to be making announcements daily on new proofs of concept and progress that may lead to pilots, so that timeline could accelerate. in some cases, there have been announcements the technology will be used within the next year or two in actual production environments. the initial relatively simple proofs of concept must be followed by much more complex demonstrations in real - world situations before these technologies can be safely deployed in today ’ s highly interconnected, synchronized, and far - reaching financial markets. although many private and inward - facing projects are being explored, the industry has also recognized the need to collaborate at early stages of development. an important positive development is that industry participants are actively engaging with each other to look for common approaches. some groups are creating standards that facilitate common platforms to enable greater interoperability of often proprietary applications that are built on them and interoperate through application program interfaces, or apis. in coming months and years, innovators, investors, and financial practitioners will no doubt make important strides in addressing key challenges such as adopting common standards, achieving interoperability between and among legacy systems and evolving distributed ledgers, improving scalability and computational throughput, and improving cryptographic security. these are 2 / 4 bis central bankers'speeches positive developments that we will monitor closely. managing risks all of this activity demonstrates that we are in a very innovative