26/12/2016 21:22:00 (GMT)
Computers are now able to take in data from the world around them and with the massive leaps forward in pattern recognition and learning algorithms they are now able to understand and give meaning to that data.
For a long time, there has been huge amounts of hype surrounding the technology of AI but if you look around the world today evidence can be seen that this technology is already being used in everyday contexts. Skype is able to translate conversations in real time and virtual assistants like Cortana, Siri and Google Now make use of Natural Language Processing to deliver their services.
More than just interact with humans such virtual assistants are used in aeronautics, the oil industry and call centers around the world. A system called Amelia is able to process and understand a manual for an oil-well centrifugal pump in 30 seconds, it can give directions for repairs and is able to carry out the tasks of insurance agent and call center worker. Moving away from the industry settings slightly IBM have partnered with several research institutions to contribute towards cancer research with their AI system, Watson.
With industry sectors all over the world adopting cognitive technologies it would seem that the financial sector, with the rate of data it produces daily, would naturally assimilate this technology also. With the complex nature of asset markets combined with the volume of data produced, the problems that face the financial sector seem to align themselves with solutions provided by automation and the increase in customer experience and understanding that cognitive technologies present.
As an example, in risk management and compliance AI can easily process every case while checking against the guidelines and policies that are in place. The markets move fast for every asset class and with all that data flying around analysis could be made much more accurate through the use of AI. Only a computer is able to take in that amount of information and understand it quick enough for the resulting meaning to be of any intrinsic value. Subtle, but key, trends that would otherwise have been missed by traditional analytics are clear for an automated system that is able to see data at every level at the same time.
The wealth management industry employs relationship manages to talk with their clients and advise them on how best to invest their money. They often do this by consuming as much relevant information as possible such as research reports, product information, customer profiles and so on. Sometimes this can take a team of researchers to get all of the necessary information collated so as to provide the comprehensive advice clients expect. Therefore, in a time when there is a lot of talk about AI replacing jobs, would it not make sense to outsource this kind of data gathering and analysis to a machine, to an AI system capable of doing this task? It would save the wealth management firm on its staff costs, and would help it become more competitive by being able to offer its clients the same level of service, but at a much-reduced cost.
Some might doubt if we are indeed close to being able to do this but in fact systems like IBM's Watson and Amelia are already used by top financial institutions: DBS Bank uses the former to advise wealth management customers, while one of the biggest US banks uses the latter to manage trading platforms and call centers.
Humanity has finally reached the tipping point where the capabilities and advantages cognitive technologies present are indeed powerful and reliable enough to be deployed in every day real life environments, not just an AI lab.
However, it should not be the case that we resist change as the fear of job losses increases with every advancement in technology. Rather, it should be looked at through an optimistic lens. Yes, some activities in the work place will be taken over by automation but this does not mean an instant loss of jobs. Investment advice for example will always be given by human professionals as many clients would demand this. However, they will likely be assisted by enhanced cognitive technologies that do the repetitive grind for them, freeing them to concentrate on more important daily tasks.