金融業(yè)科技革命是否存在失控風(fēng)險(xiǎn)？

The mysteries of bitcoin are turning heads yet again this week. At the start of the year, the digital token was worth $1,000; on Thursday, it breached $16,000. This is eye-popping, particularly given that so few investors actually understand how cryptocurrencies really work.

上周，比特幣再次使人們目眩神迷。今年初的時(shí)候，這種數(shù)字代幣單枚價(jià)格還只是1000美元左右;上周四卻突破了1.6萬(wàn)美元。如此大的漲幅令人瞠目結(jié)舌，尤其是考慮到?jīng)]多少投資者真正了解這種加密貨幣究竟如何運(yùn)作。

But amid this frenzy, here is a more startling idea to ponder: what is happening with bitcoin is not actually the most head-spinning technological development in finance today. Far from it. Away from the public gaze, there are a host of other digital innovations emerging that have attracted little public attention, yet have more far-reaching implications.

但在這種狂熱氛圍中，有一點(diǎn)細(xì)思起來(lái)更加令人惶恐：發(fā)生在比特幣身上的景象實(shí)際上并非當(dāng)今金融領(lǐng)域最令人頭暈?zāi)垦５募夹g(shù)發(fā)展。絕非如此。在公眾視線之外，還涌現(xiàn)出了很多其他數(shù)字創(chuàng)新，這些創(chuàng)新雖沒(méi)怎么引起公眾的注意，卻有著更深遠(yuǎn)的意義。

Consider the structure of markets. A few decades ago, most investors assumed that markets were a place where human brokers traded securities, on behalf of flesh-and-blood investors, driven by strategies devised in their brains (or investment committees).

想想金融市場(chǎng)的結(jié)構(gòu)。幾十年前，大多數(shù)投資者都認(rèn)為，金融市場(chǎng)是一個(gè)人類(lèi)經(jīng)紀(jì)人代表真人投資者買(mǎi)賣(mài)證券的地方，所依據(jù)的是他們的頭腦中(或投資委員會(huì))設(shè)想出的策略。

But today that idea is as quaint as assuming that currencies are controlled by a central bank. Marko Kolanovic, a JPMorgan analyst, estimates that a mere 10 per cent of US equity market trading is actually now conducted by discretionary human traders; the rest is driven by various rules-based automatic investment systems, ranging from exchange traded funds to computerised high-speed trading programs.

但如今，這種想法就如同認(rèn)為所有貨幣由一家央行控制一樣古怪。摩根大通(JPMorgan)分析師馬爾科•科蘭諾維奇(Marko Kolanovic)估計(jì)，如今美國(guó)只有10%的股市交易由擁有自由決定權(quán)的人類(lèi)交易員操作;其余的則由各種基于規(guī)則的自動(dòng)投資系統(tǒng)——從交易所交易基金(ETF)到計(jì)算機(jī)化的高速交易程序——操作。

Of course humans write this code, and sometimes oversee trades. But at a recent financial technology conference at Michigan Law School, regulators and academics estimated that computers are now generating around 50-70 per cent of trading in equity markets, 60 per cent of futures and more than 50 per cent of treasuries. Increasingly, machine learning and artificial intelligence are being added to the mix, to analyse data, trade securities and offer investment advice.

當(dāng)然，人類(lèi)編寫(xiě)了這些代碼，有時(shí)也監(jiān)督交易。但在密歇根法學(xué)院(Michigan Law School)最近舉行的一場(chǎng)金融技術(shù)會(huì)議上，監(jiān)管者和學(xué)者們估計(jì)，計(jì)算機(jī)目前產(chǎn)生了證券市場(chǎng)約50%至70%、期貨市場(chǎng)60%、國(guó)債市場(chǎng)逾50%的交易量。機(jī)器學(xué)習(xí)和人工智能正日益被采納，用于分析數(shù)據(jù)、交易證券并提供投資建議。

What we are seeing, in other words, is the rise of self-driving investment vehicles, matching the auto world. But while the sight of driverless cars on the roads has sparked public debate and scrutiny, that has not occurred with self-driving finance.

換句話說(shuō)，我們當(dāng)前正看到“自主驅(qū)動(dòng)”(self-driving)投資工具的興起，如同自動(dòng)駕駛汽車(chē)的到來(lái)。但是，雖然無(wú)人駕駛汽車(chē)上路的前景引發(fā)了公眾辯論和審視，“自主驅(qū)動(dòng)”金融領(lǐng)域還沒(méi)有出現(xiàn)這種情況。

This needs to change. Theoretically, digital finance could deliver huge benefits. As the Basel-based Financial Stability Board noted in a report last month, computers trade faster and more accurately than humans, and analyse bigger volumes of data to exploit price differentials. In good times, that should make markets more liquid and efficient.

這種情況需要改變。理論上講，數(shù)字金融可以帶來(lái)巨大收益。正如總部位于巴塞爾的金融穩(wěn)定委員會(huì)(Financial Stability Board)上月在一份報(bào)告中指出的，計(jì)算機(jī)交易的速度比人類(lèi)更快、準(zhǔn)確性更高，可以分析更龐大數(shù)據(jù)，以利用價(jià)差獲益。在經(jīng)濟(jì)繁榮時(shí)期，這應(yīng)該會(huì)令金融市場(chǎng)更具流動(dòng)性、更高效。

But, as with self-driving cars, there is a catch: technology is moving faster than politicians (or voters) understand, and outstripping the legal and regulatory frameworks. Nobody yet knows how to assign liability if a self-learning financial program goes haywire. “How are we supposed to think about intent?” asks Yesha Yadav, a law professor at Vanderbilt University.

但正如自動(dòng)駕駛汽車(chē)一樣，這里面存在一個(gè)隱患：技術(shù)進(jìn)步的速度超過(guò)了政客(或選民)理解的速度，而且超越了法律和監(jiān)管框架。如果一個(gè)自主學(xué)習(xí)的金融程序失控，沒(méi)有人知道該如何確定責(zé)任。“我們?cè)撊绾嗡伎计浔澈蟮哪康?”范德比爾特大學(xué)(Vanderbilt University)法學(xué)教授耶莎•亞達(dá)夫(Yesha Yadav)問(wèn)道。

There are gaps in software laws. In the US, it is generally presumed that manufacturers have legal liability for product flaws. But as Washington’s Office of Financial Research has noted, “software developers are not generally subject to US product liability requirements”.

軟件方面的法律也存在漏洞。在美國(guó)，一般認(rèn)為，制造商應(yīng)對(duì)產(chǎn)品缺陷負(fù)法律責(zé)任。但正如美國(guó)政府下屬的金融研究辦公室(Office of Financial Research)指出的，“軟件開(kāi)發(fā)者通常不受美國(guó)產(chǎn)品責(zé)任要求的約束”。

Another problem is regulatory fragmentation: although digital finance straddles geographical borders and asset classes, regulators do not. That creates a high risk that issues fall between the cracks. In turn, this fuels another issue: the technology is so fast-moving and opaque, that regulators find it hard to assess the cumulative impact or risks of contagion.

另一個(gè)問(wèn)題是監(jiān)管碎片化：數(shù)字金融可以跨越地理邊界和資產(chǎn)類(lèi)別，但監(jiān)管機(jī)構(gòu)卻做不到。這就產(chǎn)生了一個(gè)很大的風(fēng)險(xiǎn)，即問(wèn)題可能被忽略。這反過(guò)來(lái)又引發(fā)了另一個(gè)問(wèn)題：技術(shù)進(jìn)步如此之快且不透明，監(jiān)管機(jī)構(gòu)將發(fā)現(xiàn)很難評(píng)估問(wèn)題蔓延的累積影響或風(fēng)險(xiǎn)。

This is worrying. In recent years we have already seen some mysterious flash crashes, or sudden wild price swings, erupt in equity, bond, commodity and currency markets, apparently sparked by automated trading. This has not caused lasting damage, since these events were temporary and exchanges introduced measures to offset them in future. But nobody quite knows why these flash crashes keep occurring; and regulators admit that the arrival of AI will make it even harder to determine what is happening.

這令人擔(dān)憂。近年來(lái)，在股票、債券、大宗商品和外匯市場(chǎng)，我們已經(jīng)目睹了一些顯然是由自動(dòng)交易引發(fā)的離奇閃電崩盤(pán)或者突然的大幅價(jià)格波動(dòng)。這些并未造成持久破壞，因?yàn)檫@些波動(dòng)很短暫，而交易所也出臺(tái)了未來(lái)防范措施。但沒(méi)人確切知道為什么此類(lèi)閃電崩盤(pán)不斷出現(xiàn);監(jiān)管機(jī)構(gòu)承認(rèn)，人工智能的到來(lái)將使得確定究竟發(fā)生了什么更加困難。

“Applications of AI and machine learning could result in new and unexpected forms of interconnectedness,” the FSB notes, adding that the “lack of interpretability or ‘auditability’ of AI and machine learning methods could become a macro-level risk”.

“人工智能和機(jī)器學(xué)習(xí)的應(yīng)用可能帶來(lái)新的、讓人意想不到的聯(lián)通形式，”金融穩(wěn)定委員會(huì)指出，并表示“人工智能和機(jī)器學(xué)方法缺乏可解釋性或‘可審核性’可能會(huì)變成一種宏觀層面的風(fēng)險(xiǎn)”。

Digital evangelists will retort that since the arrival of the telegram, new technology has posed challenges for regulators; they also insist that the benefits of innovation more than offset the risks. Hopefully so. But the key point is this: just as we are scrutinising self-driving cars, we need to have a public debate about the computing revolution in finance. If the crazy antics of cryptocurrencies spur this, then bitcoin will have performed a public service.

數(shù)字技術(shù)倡導(dǎo)者會(huì)反駁稱，自從電報(bào)問(wèn)世以來(lái)，新技術(shù)就給監(jiān)管者帶來(lái)了挑戰(zhàn);他們還堅(jiān)信，創(chuàng)新的好處要大于風(fēng)險(xiǎn)。希望如此。但關(guān)鍵在于：正如我們仔細(xì)審視自主駕駛汽車(chē)一樣，我們需要對(duì)金融領(lǐng)域的計(jì)算革命展開(kāi)一場(chǎng)公開(kāi)辯論。如果加密貨幣帶來(lái)的狂熱能夠引發(fā)這場(chǎng)辯論，那么，比特幣也算提供了一項(xiàng)公共服務(wù)。

[email protected] 譯者/申凱