Setting regulatory standards and collecting data is only the start of the supervisory process. Working out what the data mean is a second stage. Recent research has demonstrated how machines can now outperform doctors in the diagnosis of certain forms of skin cancer: machines can be taught to recognise cell clusters more accurately than the human eye can. This does not, however, imply there is no role for doctors in the treatment of cancers; quite the opposite. By using technology to perform certain roles, doctors can free up time to focus on cancer treatment and patient care7. This is an example of what is sometimes referred to as human-centred automation “… which considers where humans can often do tasks or make better judgements than machines, and designs automation around these strengths”8. In a similar way, by introducing ML to perform complex tasks, we ought to be able to free up and focus supervisors’ time where it is most needed. Take the case of credit unions. Of the 570 or so U.K. domiciled credit institutions, about 450 are credit unions. These are very small and simple providers of credit facilities that between them account for 0.07% of the assets of the UK deposit taking sector. Because none of these lenders is sufficiently significant to the stability of the financial system as a whole, we supervise these entities in a proportionate manner.
To August, the central government, Social Security and regional government budget outturn evidenced a deficit of 4.3% of GDP, a 0.3 pp improvement on the same period the previous year. To meet the deficit target requires an improvement of 0.8 pp of GDP over the year as a whole; accordingly, the increase in revenue and/or the containment of spending in the final four months of the year will need to be greater than that recorded between January and August. This greater effort should be concentrated at the regional government level where, on the information available, the risks of slippage are located. For 2015, the Budgetary Plan sets a budget deficit target of 4.2% of GDP, 1.3 pp of GDP below that for 2014. In terms of the different agents, the reduction in net borrowing would amount to 1 pp of GDP in the case of central government and the Social Security system, while the regional governments should adjust their fiscal imbalance by 0.3 pp of GDP and local governments should run a balanced budget. In 2015, the improvement in the cyclical position and the reduction in government debt yields will contribute to enhancing public finances. On the estimates available, meeting the deficit target for the coming year will require a budgetary adjustment drive, measured by the change in the primary structural balance, that is appreciably less than that made in previous years. Overall, what we have is a more favourable macroeconomic scenario for the adjustment than that in place in 2012 and 2013.