How many likes for a rate rise? Monetary policy to be decided by Facebook posts
In this era of big data and real time analytics, just about everything can be counted, measured and used to inform decisions. For some years now, social media posts have been a part of this makeup, for example by informing brands about how they are viewed by their customers.
But when the central bank of one of the world’s largest economies decides to base its monetary policy strategy around what we post on Facebook or tweet on Twitter, it could seem like we've entered an alternative reality.
Nonetheless, this is in fact what’s happening, as the Bank of England announces a new taskforce to monitor social networks and the rest of the web for early signs of economic ups and downs.
It’s all about harnessing unconventional data as it’s often a lot more timely and relevant than official statistics.
According to Andy Haldane, the BoE’s chief economist, official data is “lagging and tend to be revised”.
“We have a new advanced analytics team who are constructing little models, algorithms and methods for extracting this data. We have a data lab. This is quite a big strategic change for the bank,” he told Sky News.
The bank is already using massive databases on mortgages, which helped it to roll out tighter lending criteria last year.
Banks of course already use big data and ‘unconventional’ data to inform their decision making, reduce risk and so on. But this is perhaps the first time that a central bank has taken such a large step in this direction.
Meanwhile, banks have turned to monitoring conversations to crack down on illegal behaviour by staff in light of the recent forex rigging and Libor scandals. Banks worry that traders could use Facebook and Snapchat to bypass internal compliance monitoring.
However, a Financial Times report last year highlighted how new compliance systems can monitor discrepancies between performance and internal communication use to flag concerns.
In the era of big data and social media, no online conversation is being ignored.