It knows their methods
它知道他们的招数
New banking rules baffle humans; can machines do better?
银行新规让人类备感困惑。机器的表现会更好吗？
JOINING “Hamilton”, a Broadway show, and concerts by Adele, a British soul diva, on the list of tickets-to-kill-for in New York is a screening in an ugly new office building that recently popped-up in the East Village, a place best known for offbeat culture. There is a ten-week-long queue to see simulations by Watson, IBM’s cognitive artificial-intelligence platform.
Watson最初为人所知是因其击败了世界顶级的国际象棋大师和其他一些惊世之举，之后它一直在努力吸引更多的观众，并已在金融监管界找到了一个庞大的潜在观众群。尽管规定已变得庞杂而难懂，即使是监管者自身也已开始寻求指引。面对这一需求，一个全新的市场涌现出来：金融科技达人的新产物——“Regtech”（监管科技）。
Initially known for stunts such as beating the world’s best chess player, Watson has been seeking a wider audience. It has found a vast potential one in the world of financial regulation. Rules have become so sprawling and mysterious that even regulators have begun asking for a map. In response, a market is springing up: for “regtech”, fintech’s nerdy new offspring.
最近一座丑陋的新办公楼在纽约东村（因另类文化的发展而知名）拔地而起，这里举办的一个活动和百老汇音乐剧汉密尔顿（Hamilton）、英国灵魂乐女歌手阿黛尔的演唱会一样一票难求。这就是IBM的认知人工智能平台Watson进行的模拟演示，观看这个演示需要等候10周。
On September 29th, IBM announced the purchase of Promontory, a 600-strong consultancy whose senior staff include former officials from the Federal Reserve, the World Bank, the Securities and Exchange Commission and other regulators. The hope is that person and machine will combine into a vast business. Promontory was founded in 2001 by Eugene Ludwig, who had headed one of America’s primary bank-supervisory agencies. It grew first because of the slathering of new rules during the previous, Bush administration and then prospered, says Mr Ludwig, as this process expanded under Barack Obama.
9月29日，IBM宣布收购拥有600名员工的金融咨询公司Promontory，其高层员工包括美联储、世界银行、美国证券交易管理委员会和其他监管机构的前任官员。此次收购目的是把人和机器相结合，创造出一项庞大的业务。Promontory于2001年由尤金·路德维格（Eugene Ludwig，曾任美国主要银行监管机构之一的负责人）创建。路德维格说，公司最初的发展是由于前任小布什政府时期实施了大量新规，后来公司不断壮大，则是因为奥巴马执政期间新规还在继续增加。
Promontory has recently dabbled in software, but is best known for its employees’ background and their capacity to provide expertise (its contention), contacts (its critics’) or both. Either way, it is a profoundly human business. Watson, for all its charms, is not. Automation of financial institutions has long been a core business for IBM. It played a central role in the development of the ATM; its systems keep many banks and insurance companies around the world humming along. Aware that annual expenditure on regulation and compliance is vast—it reckons in excess of $270 billion, of which $20 billion is spent simply on understanding the requirements—it began work on adding this business to Watson in early 2015. Chief compliance officers and lawyers were interviewed to break down their tasks and needs.
Promontory最近开始涉足软件，但最为人知的仍是其员工的背景和他们提供专长（观点）、介绍人脉（评论员）或两者兼顾的能力。不管如何，根本来说公司的业务主要靠人。Watson尽管魅力多多，但并不依靠人。金融机构的自动化很久以来一直是IBM的核心业务。IBM在ATM的发展过程中扮演了核心作用，它的自动化系统让全球的许多银行和保险公司都提高了效率。IBM意识到每年在监管和合规方面的巨大支出（它预计达2700多亿美元，仅是理解监管要求就要花掉200亿），2015年初开始在Watson上添加此项业务功能。IBM访问了多位首席合规官和律师以更好地了解他们的任务和需求。
The first area of focus was trading, which has the virtue of being both discrete and wildly complex. A pilot programme with half a dozen banks and three exchanges began in July, providing surveillance. A library of possible illicit schemes is fed into Watson, which can then evaluate trading patterns and communications ranging from overt messages to social media (voice analysis will be added in November). Scrutiny can extend to the network of people on the other end of trades in order to untangle complex relationships.
IBM首个关注的领域是交易，这一领域的监管规定缺乏连贯性且极为复杂。一项与六家银行和三家交易所共同展开的试点项目于7月启动，提供合规监督服务。大量可能的违规手法被输入Watson，它可以对交易模式和各种交流内容（从公开信息到社交媒体）进行分析（11月会增加语音分析功能）。这种监察还能延伸至交易对手方的人际网络，以厘清复杂的关系。
The next area is to provide clarity about rules. They are sorted by jurisdictions, institutional divisions, products and so forth, and then further broken down between rules and guidance. Watson is getting better at categorising the various regulations and matching them with the appropriate enforcement mechanisms. Its conclusions are vetted, giving it an education that should improve its effectiveness in the future. Promontory’s experts are expected to help Watson learn. A dozen rules are now being assimilated weekly. Thousands are still to go but it is hoped the process will speed up as the system evolves. Ultimately, IBM hopes speeches by influential figures, court verdicts and other such sources will be automatically uploaded into Watson’s cloud-based brain. They can play a role in determining what regulations matter, and how they will be enforced.
IBM关注的另一个领域是明确监管规则。所有规则按管辖权、部门划分、产品等进行分类，然后进一步分离出规则和指引。Watson在分类各种监管规则，并在将其与对应的执行机制相匹配方面表现得越来越好。它的最终结论会受到审核，审核意见也会对它有指导作用，应该会让它在未来更有效力。IBM希望Promontory的专家能帮助Watson学习。现在每周都会有十几条规则被吸纳，待吸纳的规则还有几千条。随着系统的发展，这一进程有望加快。最终，IBM希望有影响力的人物发表的讲话、法庭判决和其他此类来源的信息将能自动上传到Watson基于云的大脑。这些信息在决定规则的重要性以及执行方式方面能发挥作用。
Global financial institutions provide an obvious market for these services, but so too do small, local ones that lack the scale to justify the cost of a team of legal experts. A third group is the regulators themselves, who often privately grouse about being bewildered by their own remit and distrust other regulators with overlapping briefs.
全球性金融机构很显然为这些服务提供了市场。但对于很多小型的地方性金融机构来说，这种服务同样有市场，因为它们业务规模有限，没必要专门聘请法律专家团队。第三类需要这种服务的群体便是监管者自身，他们经常私下抱怨被自己的工作搞晕了，也不信任工作内容近似的其他监管者。
To some extent Watson’s success depends on whether the rules are consistent, make sense and are fairly applied. At the very least, it will be able to highlight anomalies. If successful, Watson could shift legal authority from individuals to laws. That, of course, may be its greatest virtue.
在某种程度上来说，Watson的成功取决于监管规则是否连贯、合理以及公平地应用。但至少它能够凸显异常情况。一旦成功的话，Watson可能将法律权威从个人转到法律。当然，这也可能是它最大的优点。
