Published: 19th July 2016

In a recent McKinsey Quarterly article, Where machines could replace humans—and where they can’t (yet) (download here), the financial sector is shown to display surprisingly high potential for automation.

The report is one of a series reflecting research McKinsey has been carrying out into the growing automation in the workplace.

The research analyses the time spent on various activities across different industry sectors and then matches that against the level of automation within these activities that is feasible with current technologies. Over 2,000 activities across more than 800 occupations have been analysed.

Layered on top of this analysis is the recognition that technical feasibility on its own is not a full indication that an activity will be automated and that the cost of development and deployment, the cost of the existing labour market, and follow-on benefits including higher levels of output and quality will also play a factor.

Although the research has been carried out within the US economy, it would seem highly likely that the results would remain valid across other western-style economies.

At a high level, the technical feasibility of any activity tends to be higher where the activity is predictable and repetitive, and automation of assembly lines and warehousing technologies would bear this out.

However, there has been a less visibly technological trend within the automation of data collection and manipulation with the rise of systems connectivity through the internet and common data formats and with the increasing accuracy of optical character recognition technologies and image processing capabilities.

Within the financial sector, these technologies are making their presence felt everywhere from automatic cheque paying-in machines to the automation of paper and pdf invoice input and automatic loan application processing.

Coupling the rise of data automation with the relatively high salary levels within the sector, one can start to see the financial services industry as a ripe target for further adoption of automation.

In the McKinsey data, the time spent by workers on data collection and processing in finance and insurance is put at 50% with mortgage brokers at the extreme with 90% of their time devoted to application processing.

Ultimately, for the financial sector, McKinsey gives the technical potential for automation in the sector as 43%. This is in the middle range, settled between some aspects of repetitive physical work with at 90% (welding, cutting, soldering) and highly people-oriented work at 13% (dental hygiene).

It is also probable that the encroachment of automation into desk jobs within the financial sector will not occur rapidly within existing organisations. The rise of web-only financial services automating the processing of pay-day loans, p2p lending, credit card application processing and credit scoring is a phenomenon that is likely to replace rather than transform.

Further on, the growing sophistication of what is generically referred to as robo-advice has started to signal the emergence within the sector of technologies capable not only of processing the letters of the written word, but also its meaning.

These technologies are already nascent in your pocket in the form of Siri, Cortana and “OK Google”. Provided with more domain specific expertise and they will start to sound very much like advisors.

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