The Machine Translation Bubble

Gordon Gekko: That’s smart. That’s the next bubble.

Wall Street: Money Never Sleeps

Fry: What are we going to do?

Professor Hubert Farnsworth: Duh, I know, let's play the lottery.

Amy Wong: No, let's buy internet stock.

Futurama, “The Day the Earth Stood Stupid”

Anyone who has lived through the last few years has the dubious distinction of having experienced two of the most massive investment bubbles the world has ever seen: the late nineties Internet bubble and the worldwide housing bubble that erupted so majestically in 2008.

These periods are strange. They remind me of the Will Ferrell character who screams in exasperation that “it’s like everybody swallowed stupid pills!” You ask a person if they think their house is really going to increase 20% a year forever and you get a blank look in response. You ask them if it’s reasonable to expect that to happen without massive inflation in all other items. Blank stare. You ask them if they aren’t afraid that interest rates will go up. Zip. You remind them that interest rates went up to 10%, 12%, 15% as recently as the early 1990s and people even older than you look at you as if you’re talking about the Pre-Cambrian. “Well, interest rates would never go up that high!” And they were right. Interest rates barely poked their nose above the four percent plateau and it produced a global hurricane that destroyed trillions of dollars of economic value. We’re still in the middle of picking up the pieces of the wreckage left by the hurricane that swept by three years ago.

To have a bubble, you need a rationalization of an irrational market movement. In the case of housing, spurious justifications of the relentless rise in housing prices were readily available. House prices would rise indefinitely in the United States because of projections that the population in the U.S is set to rise indefinitely until well into the middle of the century. But in Britain, where I experienced the housing bubble first hand, this rationalization was unavailable prior to the avalanche of Eastern European immigration, so there the pseudo-explanations focused on 1) affordability of mortgages thanks to record-low interest rates and 2) the dearth of new housing units to keep up with demand (high population density in the British Isles, etc.; constraints on new development, etc.). In Spain, it was immigration and the influx of Northern European retirees. And so on.

Now, flawed argumentation is beginning to ring in my ears again, and this time the tintinnabulations emanate from closer to home.

The translation industry is a sleepy backwater. It is relatively small. The biggest companies are far from being even puny mid-caps. The largest translation agency is (wait for it) one thousand times smaller than Google. In fact, the only way the “localization” industry can show up on headlines is when translation done by computers (otherwise known as machine translation, or MT) comes up. The advent of statistical machine translation (SMT) and, above all, Google’s offering of its own translation application for free has kept the issue at the forefront of the public’s imagination.

I have been reading blogs and white papers by and about the translation industry for the past few months and, slowly, I am beginning to identify the outlines of bubble rationalization. The key thing is that all of the individual statements lack any supporting proof, which is kind of basic for any sort of rational argumentation. Individually, some statements are debatable. Loosely-strung-together observations can be press-ganged to build a weak case for something that isn’t happening.

Condition 1: “Translation budgets are being slashed.”

Condition 2: “Heads of translation departments are being pressured to produce more with less.”

I don’t know if either of these things is actually happening. I’m simply saying that there is no actual evidence that this is happening. It might be happening, but the alacrity with which people cite these two nostrums at the drop of a hat raises at least an eyebrow for the survivor of Worldwide Bubble 1.0 and Worldwide Bubble 2.0. Rational discourse should be based on data. Data is what is usually absent from any discussion in the brave, new world of L10N Land.

The other phenomenon that is frequently cited is what I call the Content Big Bang:

Condition 3: “There has been a cosmic explosion in the amount of content.”

To which I say “hmmmm…” Really? The same economic contraction that produced the Great Slashing of Translation Budgets in Condition 1 also generated a cosmic multiplication of content? That is doubtful. There is probably some sort of correlation between GDP and the text produced for commercial translation. Just as translation budgets are under pressure, copywriting budgets must be subject to some of the same constraints (unless Google Copywrite came out and I haven’t been informed…).

Hmmmm….

So where (oh, where) is that tsunami of content? One blogger points the idle reader in this direction: an article from The Economist entitled “Data, Data Everywhere.” The subtitle reads: “Information has gone from scarce to superabundant.” The piece goes on to describe the mountains of data spewed out by everything from telescopes to supermarket scanners:

Wal-Mart, a retail giant, handles more than 1m customer transactions every hour, feeding databases estimated at more than 2.5 petabytes—the equivalent of 167 times the books in America’s Library of Congress (see article for an explanation of how data are quantified). Facebook, a social-networking website, is home to 40 billion photos. And decoding the human genome involves analysing 3 billion base pairs—which took ten years the first time it was done, in 2003, but can now be achieved in one week.

Any half-awake reader of this (if such exists) should immediately stir from his or her light slumber and protest. “Wait! The data described by The Economist is really numbers. Numbers don’t require localization, do they?”

That’s right. Data isn’t “content.” In fact, even “content” isn’t “content.” “Content” is just jargon for commercially produced text by companies and governmental organizations. The reduction of linguistic bits of text to data is simply misleading.

Thus, the search continues for the content deluge.

If you probe and prod and niggle and dig hard enough to uncover the alleged mountain of content, you finally wring a grudging response from bubble promoters. To the question: “Where, dear sir, is this cornucopia of content stretching translation budgets thin?” One finally gets the following whimpering reply:

“Well, uh, there’s Facebook… and Twitter… and all those blogs.”

To which my reaction is: “Really? Facebook…? Twitter?”

Give me a break.

I’m sorry. But that is pretty lame. I find it hard to believe that senior marketing execs at multinationals are strategizing about how to translate the mountain of tweets by their clients and employees into every other language. Or that I really need the “He’s adorable!” messages at the bottom of my nephew’s Facebook baby pictures translated into Cantonese.

So, yeah, that is some seriously fuzzy thinking going on there.

Some rational choice theorists argue that bubbles, despite their tendency to pop disastrously, are actually good in the long run. To which one must reply that “in the long run we are all dead.”

Remember: friends don’t let friends ride bubbles, because bubbles burst and when they burst, people get hurt.

And if you hear anyone claim that there isn’t a machine translation bubble, ask yourself: does this person’s livelihood depend upon there being a machine translation bubble? Then go ahead and ask: what were these people doing during the 1990s?

Of course, machine translation is here to stay, in one way or another. Which doesn’t mean that a lot of fools won’t be parted from their money in the mean time, like the hapless idiots who sank their pensions in Pieceofcrap.com circa 1999. I just wish there were some way to short this…

Miguel Llorens is a freelance financial translator based in Madrid who works from Spanish into English. He is specialized in equity research, economics, accounting, and investment strategy. He has worked as a translator for Goldman Sachs, the US Government's Open Source Center and H.B.O. International, as well as many small-and-medium-sized brokerages and asset management companies operating in Spain. To contact him, visit his website and write to the address listed there. Feel free to join his LinkedIn network or to follow him on Twitter.

Lower Translation Rates: *ϗԇḨἭᾎ‡₩ion and the Idiocy of Averages

"...averages and extreme values (as abstractions and unrepresentative instances respectively) often provide only partial, if not downright misleading, views of a totality's behavior."

Stephen Jay Gould, Full House: The Spread of Excellence from Plato to Darwin

There seems to be a meme whereby any discussion of lower rates in the translation industry is immediately, or at least eventually, appended by the coda that, “of course, this is partly due to the increased usage of machine translation (MT).” The curious thing is that this is also accompanied by the meme that “the volume of material that needs to be translated has mushroomed exponentially.” Allegedly, we are facing a case in which demand for a service has expanded fantastically but the price per unit of that service has dropped. Surely, there can’t be any parallel for such a trend anywhere else in the history of the world economy since the first caveman traded a pelt for a sharp-edged stone with another caveman.

It is truly stupefying to note how even intelligent discussions of machine translation sooner or later crash into the lower rate/greater demand conundrum and come limping out of it with the “machine translation” crutch.

At first blush, this appears absurd. Supply and demand dictates that greater demand and stable supply breeds higher prices. If demand for translation services is rising but the price of translation a single word is going down, something odd must be happening. Our fuzzy thinker jumps to the conclusion that somehow an advance in productivity is making it cheaper to translate the average word despite the demand rise. Baboom! Machine translation comes to mind. And thus is born the questionable thesis that “greater adoption of machine translation is driving down the price per unit of a translated word.”

This way of (wrongheaded) thinking is so seductive that it is hard to disentangle the sleight of hand that our 21^st century way of thinking plays upon our own poor reptilian cortex.

Step back for a moment and think about this situation critically. Imagine for a moment a world in which all translation was done by post-editors. They charge a fraction of a penny for every word they edit or they charge by the hour. The crucial point is that the entirety of all the translation work carried out in this hypothetical world is first done by a computer and then processed by a human being who does post-editing.

In this hypothetical word, any improvement in the technology naturally feeds higher productivity. Any profit increase from this productivity improvement is swallowed by the creator or owner of the technology, albeit with perhaps a slight lag. A period of adjustment ensues, after which the post-editor drops her rate slightly to accommodate the greater productivity. Crucially, she still makes the same amount of money every day. But society benefits because a greater amount of work is done for the same amount of money. The same amount of money buys a greater amount of output. In this scenario, the average rate per word has dropped.

Return for a minute to the basic components of this model:

A.    Demand for translation/machine translation technology/population of post-editors/stable output of translation/x cost per unit

Let us tweak it slightly, by improving the quality of the technology:

B.    Demand for translation/BETTER MT technology/post-editors/GREATER output of translation/x cost per translated word DROPS

Let us tweak that slightly again by hypothesizing a concurrent increase in overall demand for translation in this world:

C.    HIGHER demand for translation/BETTER MT technology/post-editors/GREATER output/unit cost per word of translation STILL DROPS (if, and only if, the productivity boost outstrips demand growth, which is not necessarily the case)


In cases B and C, it is perfectly reasonable for the average price per word to drop. And also for the post-editor to charge less per word. Otherwise, there would be no incentive for the investor in the technology to fund the research necessary for improvement. If the post-editors brake a trend toward lower per word rates under conditions of higher productivity (say, through a worldwide union of some sort), society in general is harmed. While higher productivity is ensured, the incentive for better technology is hijacked by a hypothetically all-powerful Brotherhood of Teamsters and Post-Editors and no further improvements are likely to occur.

This is unconsciously the model we are thinking of when we say price per unit is going down because of machine translation.

The problem is we still live in a hybrid world of both post-editors and translators, or, to put it another way, translators who process MT output and translators who don’t. As we proceed, let us take as a given the premise that the price per unit of non-post-editing (i.e., human translation) is going down.

I hope that by now it should be clear to the careful reader that a massive cognitive conflation is occurring here. Leaving aside borderline cases and grey areas, post-editing and translation still remain two distinct activities. To say that lower cost of post-editing (since that is the proper name for the activity, not machine translation) is driving down the cost of translation is tantamount to claiming that the invention and massive adoption of frozen dinners in the United States of the 1960s drove down the average salaries of chefs in Paris during the same decade.

We’re not talking apples and oranges here. We’re talking apples and moon pebbles.

What machine translation might be doing is driving down the average cost of a word that is translated (or, perhaps more accurately, machine translated).

But “translated” here has to be rendered here with an asterisk. Perhaps also a skull and crossbones, but my word processor doesn’t have that emoticon… yet! (as machine translation enthusiasts like to exclaim so mischievously).

So let me restate the thesis thusly:

Machine translation might be driving down the average cost of a word that is *ϗԇḨἭᾎ‡₩ed.

Wherein “*ϗԇḨἭᾎ‡₩ion” refers to the activity of creating sequences of words in one language that are conceptually and stylistically equivalent to other sequences of words in another language. This is done either through the processing by so-called post-editors of linguistic output produced by a computer or via the more traditional process of “translation” (now often referred to as "human translation"). While the two methods of *ϗԇḨἭᾎ‡₩ion bear some distant family resemblance, they in fact belong to two widely divergent genera.

Without this neologism (the “‡” is silent, by the way), the idea that machine translation can have any sort of impact on "human" translation is quite frankly questionable. Although the cost of servicing a mortgage in many countries has gone down drastically and some commodities such as oil have plummeted from their dizzying heights of 2008, the cost of translating texts (essentially equal to feeding and clothing one human translator and his or her family plus a little extra cash on the side for incidentals) is essentially the same as in 2008. Ditto for 2005 and 2000. Perhaps even 1885 after adjusting for inflation.

So are translation costs really plummeting? Is this really what is happening?

Completely unnecessary picture of Sofía Vergara

As Sofia Vergara would say: “I don’t think so, papi.”

Or is it perhaps something else? Something perhaps more complicated… or perhaps simpler?

Miguel Llorens is a freelance financial translator based in Madrid who works from Spanish into English. He is specialized in equity research, economics, accounting, and investment strategy. He has worked as a translator for Goldman Sachs, the US Government's Open Source Center and H.B.O. International, as well as many small-and-medium-sized brokerages and asset management companies operating in Spain. To contact him, visit his website and write to the address listed there. Feel free to join his LinkedIn network or to follow him on Twitter.

Sorpresa: economista galardonado con Nobel es un geek

Ayer terminé una entrada con un clip del clásico de Mel Brooks Young Frankenstein y hoy el blog de Paul Krugman contiene varias referencias a la película que ilustran su carácter como metalenguaje. Debe ser completamente incomprensible para cualquiera que tenga menos de 30 años. Lo transcribo y traduzco en su totalidad:

Blucher! Neighhhh! 

Oh, dear. Brad DeLong is right: the CBPP transcript (pdf) of Jan Hatzius, Marty Feldstein, and yours truly being gloomy does keep calling Marty “Feldman” instead.  

Someone has a rotten brain! Destiny! Destiny!

http://krugman.blogs.nytimes.com/2010/10/08/blucher-neighhhh/

Traducible del siguiente modo:

¡Blucher! (Relincho)
Qué error. Brad DeLong tiene razón: la transcripción del CBPP (pdf) de Jan Hatzius, Marty Feldstein y yo diciendo cosas lúgubres contiene numerosas referencias a Marty "Feldman".
Alguien tiene un cerebro podrido. ¡Es el destino! ¡Es el destino!

Marty Feldman como Igor.

La película de Brooks contiene muchos chistes que giran alrededor de los nombres. El joven Frankenstein pronuncia su apellido "FrankensTÍN" para distanciarse del infame antepasado que creó el monstruo. Del mismo modo, el descendiente de Igor se hace llamar "AI-gor". Mientras tanto, Frau Blucher --la tenebrosa ama de llaves del castillo ancestral-- es tan espeluznante que sólo mencionar su nombre hace que los caballos relinchen de terror (neigh). Al referirse erróneamente a su colega Feldstein como "Feldman", resalta la referencia inconsciente de la transcripción a la película. El lapsus se debe a que el nombre del ilustre economista de Harvard es muy similar al de Marty Feldman, el comediante que interpreta a Igor, el asistente de laboratorio de Wilder. Y la referencia al "cerebro podrido" es al intercambio en la película en que le explican al monstruo el error de haberle implantado un cerebro anormal.

El lenguaje de las referencias culturales puede ser increíblemente compacto. En apenas 20 palabras, Krugman remite a toda una constelación de significados. Lo curioso es que probablemente dentro de 100 años un mensaje como éste será completamente imposible de decodificar. Excepto quizás para la familia Feldstein.

La postergación del trabajo, Freedom, la lentitud de las herramientas CAT y Young Frankenstein

La edición de este mes del New Yorker, además de la pieza de Malcolm Gladwell que comenté hace dos días, contiene una reseña de James Surowiecki de una recopilación de artículos académicos sobre la postergación de tareas desagradables (procrastination). El artículo enumera diversos métodos que utiliza la gente para vencer ese obstáculo. Se trata de técnicas denominadas self-binding, que se podría traducir como "obligarse a uno mismo" o "autocompromiso". Consisten en hacer arreglos para negarte forzosamente a ti mismo la capacidad para cometer un error o transgresión en el futuro. Un ejemplo son los ludópatas que firman contratos con casinos para que éstos les nieguen la entrada en el futuro.

Surowiecki menciona también el ejemplo de un software llamado Freedom, que cierra el acceso a Internet y, teóricamente, obliga al usuario del ordenador a centrarse en la tarea que tiene ante sí. Confieso que los paseos intermitentes por Internet (y sin ninguna relación con el proyecto de turno) son uno de los principales motivos por los que sufre mi productividad. Probablemente podría trabajar con mucha mayor rapidez si la tentación de usar imdb.com para averiguar en cuántas películas han figurado canciones de Creedence Clearwater Revival o consultar Wikipedia para verificar en qué LP apareció "Jokerman" por primera vez no estuviese a la corta distancia de la ventana de búsqueda de Google.

Confieso que no he probado la herramienta en cuestión, aunque la idea me parezca ingeniosa. El problema es que me parece demasiado radical, como una lobotomía para curar un dolor de cabeza. Una vez visité a un primo en su oficina y cuando quise hacer una consulta en su máquina, descubrí que el acceso a cualquier cosa que no estuviese relacionada con la empresa estaba bloqueado. Me pareció digno de un régimen autoritario fundamentalista.

Sin embargo, creo que mi facilidad para distraerme no es sólo una flaqueza propia de mi carácter. Estoy convencido de que parte de la culpa radica en las herramientas de traducción. Para decirlo brevemente, son demasiado lentas. Wordfast Pro se demora una eternidad mientras pasa al siguiente segmento y decide si hay alguna coincidencia en la memoria. Mal que bien (aunque en menor grado), Trados y SDLX adolecen del mismo problema. Dos o tres segundos suena como poco, pero mutiplicado por 1.000 segmentos, es una eternidad en la que siento cómo se mueren mis células grises. Ese dolor lo mitigo a veces yendo al New York Times o revisando mi cuenta de Twitter por enésima vez.

En todo caso, al menos soy consciente de mi problema. Antes que soluciones radicales como Freedom, prefiero esperar a que alguien invente una CAT que se ejecute con más rapidez y reduzca mis devaneos. La idea de Freedom me recuerda a la escena de Young Frankenstein en la que Gene Wilder decide entrar a la celda a domesticar al monstruo. Les dice a sus asistentes con gran solemnidad que no abran la puerta por ningún motivo, incluso aunque les ruegue o amenace. Es un buen ejemplo de una técnica de obligación de uno mismo para hacer una tarea desagradable.

La revolución no será transmitida por Twitter, según Malcolm Gladwell

El viernes pasado estaba viendo el Colbert Report y el invitado era Aaron Sorkin, guionista/creador de mi programa de televisión preferido (quizás de todos los tiempos), The West Wing. Estaba promocionando su más reciente peli, The Social Network, sobre la creación de Facebook. Huelga decir que es tan brillante que se le deslizan perlas similares a las de sus personajes (y con el mismo desparpajo). La siguiente fue tan lapidaria que se escucharon exclamaciones de asombro (audibles) en el público: "Los medios sociales como Facebook y Twitter son a la socialización lo que los reality shows son a la realidad". (Ver clip aquí.) Cuando alguien así expresa escepticismo sobre el evangelio de esta década, hay que sentarse a pensar. Y ahora se ha sumado otra voz digna de escuchar que nos invita a dudar, aunque sea un poco.

Malcolm Gladwell es una de las estrellas del non-fiction en inglés (categoría de escritura para la que no existe ningún equivalente en castellano, al menos que yo sepa). Para mí, es el mejor escritor de misterios de la actualidad --con la diferencia que sus misterios son sacados del mundo real. Suele abordar un problema cognitivo, analizar con elegancia por qué las respuestas tradicionales fracasan y rematar sus piezas con descubrimientos científicos recientes que sugieren nuevos horizontes.

En la edición de este mes del New Yorker, Gladwell enfoca sus poderosas baterías analíticas sobre el mundo de las redes sociales online. El título, "Small Change", es un doble sentido: en el primer nivel, significa "menudo, sencillo, las monedas que uno lleva en el bolsillo" y, en otro, significa "cambio pequeño", referido a lo impotentes que son las redes sociales para efectuar cambios políticos genuinos. Su primer paso consiste en analizar la sabiduría convencional. Todos conocemos el Zeitgeist: Twitter permitió que la disidencia iraní se organizara para protestar las elecciones presidenciales fraudulentas en las que Ahmadineyad salió reelegido. Tanto así que el Departamento de Estado solicitó a Twitter que suspendiese el mantenimiento programado durante la crisis para impedir que el movimiento verde quedase incomunicado. Contacto con la realidad: la mayoría de los microblogueros que tuiteaban sobre los eventos en Irán y escribían en inglés estaban transmitiendo desde el exterior. La sensación de inmediatez pasaba por alto un dato evidente: ¿no es extraño que los organizadores de las protestas en Irán escribiesen en inglés y no farsi? Efectivamente, la mayoría eran exiliados que transmitían el mensaje de sus compatriotas a un público internacional. Es posible que las esperanzas milenaristas de los "maoístas digitales" (derecho de autor: Jaron Lanier) sean, por lo menos, exageradas. Para reforzar este punto,  Gladwell procede a citar a mi historiador preferido, Robert Darnton:

Las maravillas de la tecnología comunicacional en el presente han generado una falsa conciencia sobre el pasado, incluso la sensación de que las comunicaciones no tienen ninguna historia.

De allí, Gladwell pasa a aplicar su bisturí a un contraejemplo del pasado: el movimiento de los derechos civiles de la población negra en el sur de Estados Unidos. La característica clave de este activismo "tradicional" (es decir, previo a Internet) que resalta Gladwell es la siguiente: fuerte compromiso interpersonal (los participantes en las protestas se conocían entre sí), lo que el sociólogo Doug McAdam denomina un fenómeno strong tie ("vínculo fuerte"). Este tipo de relación es la que permite a los individuos correr los riesgos (prisión, violencia física, incluso asesinato) implícitos en el desafío del sistema de segregación institucional conocido como "Jim Crow".   

Las redes sociales modernas, en contraste, carecen de este tipo de vinculación: "El tipo de activismo asociado con los medios sociales no se parece en nada a esto. Las plataformas de medios sociales se construyeron alrededor de lazos débiles". Lo que no significa que estas redes carezcan de valor. Los vínculos débiles logran fomentar acciones pequeñas que, agregadas, se pueden volver gigantescas. Gladwell cita el ejemplo de un empresario que logró que 25.000 personas se inscribiesen en el registro nacional de EE.UU. de posibles donantes de médula ósea. El esfuerzo requerido para darse de alta es mínimo y el beneficio para la sociedad es inmenso.

Pero esto resulta muy distinto a imaginar que este tipo de activismo puede tumbar gobiernos autoritarios. Los organizadores de movimientos como los derechos civiles en los años 60 y los jóvenes iraníes de la Revolución Verde exigen mucho más a sus seguidores que simplemente tomar una muestra de su ADN y enviarla por correo. Golpizas, tortura, prisión y pérdida de empleos son apenas algunos de los costes de este tipo de activismo. Acota Gladwell:

Los evangelistas de los medios sociales no comprenden esta distinción; al parecer, creen que un amigo de Facebook es lo mismo que un amigo real y que inscribirse en un registro de donantes en Silicon Valley es activismo en el mismo sentido que sentarse en un comedor segregado en el Greensboro [Carolina del Norte, cuna de las protestas contra restaurantes segregados] de 1960.

No contento con esta herejía, Gladwell pasa a explorar un territorio aun más delicado: la posibilidad de que las redes sociales desestructuradas son menos efectivas que organizaciones más jerárquicas. Del lado positivo, las redes carentes de autoridad central son "enormememente resistentes y adaptables en situaciones de bajo riesgo". Pero del lado negativo:

Debido a que las redes no tienen una estructura de liderazgo central y líneas claras de autoridad, experimentan problemas serios a la hora de llegar a consensos y fijar metas. No saben pensar estratégicamente y son susceptibles de forma crónica al conflicto y el error. ¿Cómo puedes tomar decisiones difíciles sobre asuntos tácticos, estratégicos o filosóficos cuando la opinión de todos pesa por igual?

Y, con esto, Gladwell cruza el Rubicón y se instala del otro lado de la ribera, ocupado por apenas dos o tres intelectuales públicos como el chillón Andrew Keen (El culto del aficionado; en la página de Amazon hay una reseña mía, enterrada en algún lado) y el estrafalario pero profundísimo Jaron Lanier, uno de los pioneros de la "realidad virtual" que después de cumplir los 40 comenzó a replantearse algunas de las esperanzas evangélicas de la cultura digital. Su brillante You Are not a Gadget está a punto de aparecer en castellano como No somos ordenadores gracias a Debate. Y es que cuando se combina la crítica de la tecnología mediática con la sugerencia de que la ausencia de jerarquías no necesariamente es algo positivo, la respuesta puede ser explosiva, como lo verifica la recepción de estos dos libros. ¿Será éste el tema del próximo libro de Gladwell? Ciertamente representaría un cambio de rumbo para él, pues hasta ahora sus libros presentan ideas de las ciencias sociales de forma muy atractiva para su fácil deglución por la legión de management consultants y "asesores de estilo de vida". Confieso que estoy prejuiciado a favor de la gente no sólo brillante sino también combativa. Veremos.

Miguel Llorens is a freelance financial translator based in Madrid who works from Spanish into English. He is specialized in equity research, economics, accounting, and investment strategy. He has worked as a translator for Goldman Sachs, the US Government's Open Source Center and H.B.O. International, as well as many small-and-medium-sized brokerages and asset management companies operating in Spain. To contact him, visit his website and write to the address listed there. Feel free to join his LinkedIn network or to follow him on Twitter.

Remembering the "Moneygeddon": Can You Say "Subprime" in Spanish?

It's hard to believe that two years have passed since the dramatic week that started on a Friday when the leaders of the major Wall Street banks converged on the headquarters of the New York Federal Reserve. As has been chronicled in many books, articles and movies, the head honchos failed to come up with a solution to save Lehman Brothers, which was allowed to go under on Sunday evening (despite one firm offer from Britain's Barclays), nearly bringing down the rest of the international financial system with it. There are many human anecdotes from that dramatic week that punctuate how dire the situation was. To select only a single one: Mohammed El-Erian, one of the leading fund managers in the world, called his wife after the run on money market funds and told her to withdraw as much cash as she could from the ATMs because banks (i.e., all banks) might not open their doors the following morning. You have to take a step back to gauge the gravity of this story. This man is probably a millionaire several times over and he is telling his wife to take out $500 or $1,000 or whatever she can get because that is the only thing they might have to live on for the next few weeks. That is simply Great Depression territory. Scary, scary.

As we all know, the "Clusterf**** to the Poorhouse" (as the Daily Show dubbed it) began with the least complicated of financial products: the humble mortgage. Except these mortgages had a twist: they were subprime mortgages. By now everyone is familiarized with the concept. Thanks to ultra-low interest rates, people with low credit scores began to be granted home loans. Back before the housing bubble, banks had found that some people with bad credit scores could actually be granted mortgages and that the default rate was relatively low, since payments on a house tend to be the last payment that is cut when economic hardship hits. This was a niche activity, however. But once everyone with good credit scores had remortgaged in the early 2000s, the market had no one else to turn to. So banks and originators expanded the subprime niche by many multiples to keep the profit machine churning. The theory was that as long as rates stayed low, even people with unspectacular credit could make their regular payments and renew at the ultra-low rates when the basement teaser rates ended. This time was different. Eventually, rates began to inch upward only slightly (as expected), but there were massive defaults (which was not expected), and institutions all over the world crumbled and the rest is history.

Now, given its status as one of the major buzzwords of 2008, the term has received several different translations in Spain's El País:

 La Comisión Nacional del Mercado de Valores del Reino Unido (FSA por sus siglas en inglés) ha multado con 17,5 millones de libras (21,2 millones de euros) a Goldman Sachs por no informar sobre la investigación abierta en Estados Unidos por un fraude relacionado con las hipotecas subprime, tal y como le obliga la ley británica.
http://www.elpais.com/articulo/economia/CNMV/inglesa/impone/Goldman/mayores/multas/historia/elpepueco/20100909elpepueco_7/Tes

hipotecas de baja calidad (subprime) [Eng. low-quality mortgages]
http://www.elpais.com/articulo/economia/Goldman/Sachs/gana/83/elpepueco/20100720elpepueco_11/Tes

 hipotecas de alto riesgo ("subprime") [Eng. high-risk mortgages]
http://www.elpais.com/articulo/economia/cumbres/G-20/inicio/crisis/financiera/elpepueco/20100621elpepueco_9/Tes

las subprime (hipotecas basura) [Eng. junk mortgages]
http://www.elpais.com/buscar/subprime/desde_30-06-2008/resultados-21-al-30

Therefore, you have a reasonably large selection for a single (often authoritative) source. However, "hipotecas basura" and "hipotecas subprime" by far get the most hits on that archive.

Now, one thing to keep in mind is that the word "subprime" is an elegant example of financial re-branding. To understand that, think of the analogous case of junk bonds, which are debt securities with a higher yield. Why do they offer a higher yield? Well, because they are issued by companies with less-than-sterling credit. To receive money from the market, they have to pay more than a more reputable company. Thus the less-than-admiring moniker of junk bonds. When these low-quality bonds became a hot property in the 1980s, bright young things began thinking up ways of selling them off. But for that you needed a shiny new name. "Junk" bond simply wouldn't do. "How about high-yield bond?" "Hmmm, that sounds a LOT better. Kind of like a new, improved sort of bond." After all, higher yield is good, right? And thus was born another speculative mania using completely inappropriate assets.


The term "hipoteca basura" suggested by the Spanish newspapers is a nod at this history. And it is certainly suggestive, since it points out emphatically (in a way the original English original doesn't) that we are talking about junk mortgages. The word "subprime" is a nifty little sleight of hand. See this pile of mortgages held by people with lower credit scores? They're packaged into junk mortgage CDOs. And, by the art of securitization and the intricacies of the rating system, they are transmuted into AAA-rated subprime bonds. Sounds better, right? "They're not junk, they're just not-good, less-than-prime, prime-minus, subprime." Voilá, another catastrophe is born.



Therefore, if it is up to you, by all means use "hipoteca basura." It is blunt, suggestive and calls to mind an entire spectrum of meanings that help us think about the Moneygeddon in Spanish. However, keep in mind that it is a loaded term, with heavily negative connotations that your audience or client may not like. In conclusion, all of the options taken from El País are valid, but weigh beforehand the nuances of every one of the options before committing yourself to one. And for God's sake don't buy subprime mortgage bonds.

Financial Terminology into Spanish: To Tighten Interest Rates

A word is simply a worn-out metaphor, a French poet once said (Breton? Apollinaire? I forget…). In the case of the word “tighten” in relation to interest rates, one can almost see a metaphor in the process of hardening from metaphor to commonplace usage to new meaning. The phrase “tighten interest rates” is now so commonplace that its users probably never realize that it is actually a figure of speech. If one looks it up in the dictionary, the technical sense of “tighten” as in “to raise interest rates” simply does not show up:

Definition of TIGHTEN
transitive verb
: to make tight or tighter
intransitive verb
: to become tight or tighter
— tight•en•er\ˈtīt-nər, ˈtī-tən-ər\ noun
— tighten one's belt
: to practice strict economy

This is just the monolingual English dictionaries. The bilingual English-Spanish dictionaries are no help either. The ones that come closest without exactly hitting the nail on the head are Alcaraz Varó and Hughes, with “tightening of credit (BANCA restricción de crédito)” and Marina Orellana’s Glosario internacional para el traductor, which also comes close without illuminating the perplexed translator with “tightening of credit: contracción (rigidez) del crédito.” Both options dance around the issue without solving the conundrum definitively.

And yet the phrase is as common as grass. Try googling "tighten interest rates" between quotation marks in order to get the exact phrase and you get 129,000 hits. Moreover, the phrase is not recent: a short search on Google Books reveals a first hit dating from 1934.

Interest rates can only go up or down (or stay static, if you're very fastidious). If the translator knows that much, she can just decide that her challenge is to decide which meaning (up or down) needs to be identified. To “tighten credit” is itself a metaphor, of course. It means to make lending more restrictive. The way to restrict lending is to discourage potential lenders from taking on more borrowing. And how do you do that? By raising rates, of course. The “tightening of credit” probably migrated to the “tightening of interest rates.” Therefore, the correct translation is “aumentar las tasas de interés” or “elevar los tipos.” Or, if your text is very repetitive and you can get away with it, "restringir la oferta monetaria." A good example of relatively common technical jargon that is not found in either monolingual or bilingual dictionaries.