金融業(yè)科技革命是否存在失控風險？

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。今年初的時候，這種數(shù)字代幣單枚價格還只是1000美元左右;上周四卻突破了1.6萬美元。如此大的漲幅令人瞠目結舌，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，有一點細思起來更加令人惶恐：發(fā)生在比特幣身上的景象實際上并非當今金融領域最令人頭暈目眩的技術發(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)新雖沒怎么引起公眾的注意，卻有著更深遠的意義。

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).

想想金融市場的結構。幾十年前，大多數(shù)投資者都認為，金融市場是一個人類經(jīng)紀人代表真人投資者買賣證券的地方，所依據(jù)的是他們的頭腦中(或投資委員會)設想出的策略。

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，如今美國只有10%的股市交易由擁有自由決定權的人類交易員操作;其余的則由各種基于規(guī)則的自動投資系統(tǒng)——從交易所交易基金(ETF)到計算機化的高速交易程序——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.

當然，人類編寫了這些代碼，有時也監(jiān)督交易。但在密歇根法學院(Michigan Law School)最近舉行的一場金融技術會議上，監(jiān)管者和學者們估計，計算機目前產(chǎn)生了證券市場約50%至70%、期貨市場60%、國債市場逾50%的交易量。機器學習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，我們當前正看到“自主驅(qū)動”(self-driving)投資工具的興起，如同自動駕駛汽車的到來。但是，雖然無人駕駛汽車上路的前景引發(fā)了公眾辯論和審視，“自主驅(qū)動”金融領域還沒有出現(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)字金融可以帶來巨大收益。正如總部位于巴塞爾的金融穩(wěn)定委員會(Financial Stability Board)上月在一份報告中指出的，計算機交易的速度比人類更快、準確性更高，可以分析更龐大數(shù)據(jù)，以利用價差獲益。在經(jīng)濟繁榮時期，這應該會令金融市場更具流動性、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.

但正如自動駕駛汽車一樣，這里面存在一個隱患：技術進步的速度超過了政客(或選民)理解的速度，而且超越了法律和監(jiān)管框架。如果一個自主學習的金融程序失控，沒有人知道該如何確定責任。“我們該如何思考其背后的目的?”范德比爾特大學(Vanderbilt University)法學教授耶莎•亞達夫(Yesha Yadav)問道。

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，一般認為，制造商應對產(chǎn)品缺陷負法律責任。但正如美國政府下屬的金融研究辦公室(Office of Financial Research)指出的，“軟件開發(fā)者通常不受美國產(chǎn)品責任要求的約束”。

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.

另一個問題是監(jiān)管碎片化：數(shù)字金融可以跨越地理邊界和資產(chǎn)類別，但監(jiān)管機構卻做不到。這就產(chǎn)生了一個很大的風險，即問題可能被忽略。這反過來又引發(fā)了另一個問題：技術進步如此之快且不透明，監(jiān)管機構將發(fā)現(xiàn)很難評估問題蔓延的累積影響或風險。

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.

這令人擔憂。近年來，在股票、債券、大宗商品和外匯市場，我們已經(jīng)目睹了一些顯然是由自動交易引發(fā)的離奇閃電崩盤或者突然的大幅價格波動。這些并未造成持久破壞，因為這些波動很短暫，而交易所也出臺了未來防范措施。但沒人確切知道為什么此類閃電崩盤不斷出現(xiàn);監(jiān)管機構承認，人工智能的到來將使得確定究竟發(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”.

“人工智能和機器學習的應用可能帶來新的、讓人意想不到的聯(lián)通形式，”金融穩(wěn)定委員會指出，并表示“人工智能和機器學方法缺乏可解釋性或‘可審核性’可能會變成一種宏觀層面的風險”。

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)字技術倡導者會反駁稱，自從電報問世以來，新技術就給監(jiān)管者帶來了挑戰(zhàn);他們還堅信，創(chuàng)新的好處要大于風險。希望如此。但關鍵在于：正如我們仔細審視自主駕駛汽車一樣，我們需要對金融領域的計算革命展開一場公開辯論。如果加密貨幣帶來的狂熱能夠引發(fā)這場辯論，那么，比特幣也算提供了一項公共服務。

[email protected] 譯者/申凱