Reconfiguring the financial sector with A.I

Reconfiguring the financial sector with A.I

Artificial Intelligence (A.I.) has seen quite a bit of a boom this year, especially when it comes to analytics and in business solutions. While there have been advances in the wearable technology such as Microsoft’s Hololens and private sector A.I such as the Alexa, the dominating artificial intelligence has remained within the business sector and in business based solutions. And while most of these business solutions are set at a level which is not imposing upon the humanistic factor of financing, one has to wonder how artificial intelligence will reconfigure various markets, specifically the financial market.


Perhaps the biggest reconfiguration of the financial system will come from programs which are able to think and rationalise like a human. While artificial intelligence has been able to do so for quite a while, the programs have been rather limited. Yes, Cortana has given us a feeling like there is a human which can search and interact with us and yes, there have been analytics which have been able to predict certain trends in the market, but really nothing has been as big as the emergence of Watson.

Watson, a program developed by IBM, is a cognitive technology capable of understanding data, reasoning, learning, and interaction. The program is so advanced that the company says that it surpasses the standard definition of artificial intelligence. For the financial sector, the ability to evolve and analysis solutions to real time financial data, as well as learn trends in the market and project those trends to potential clients is huge. H&R block has seen the potential of the Watson program and has integrated the software into their tax solutions. However, it is not just the tax company who will benefit from the technology consider:

Should the program work as it is described, stock brokers will be able to use the program to predict trends in the market while simultaneously analysing investor’s portfolios and spending trends to target the best potential investors in a given market. By having access to global data and learning from such data, stocks will be traded in a more aggressive manner with a far slimmer margin for financial loss.

Business investors who use the program can not only compare the local markets but also see projected trends for their business compared to data which is available. The learning and understanding of the program may also lead to optimising spending and investments to further grow company benefits and profit margins.


Intel’s Artificial intelligence and analytics programs are already being used by financial institutions. Caixa Bank, the largest financial institution in Spain, is using the a.i and modules from Intel to cater to the digital world. Luis Esteban Grifoll, Chief Data Officer for Caixa Bank, stated that the millennials are transitioning to digital banking. His concern is that soon the only banking which will be conducted will be through digital devices. As this sector is the majority, solutions need to be catered to the majority.

The data and intelligence for financial institutions must be presented to potential clients in real time. It is no long acceptable for banks to have reports within a day or a week. Big-data solutions such as Oracle, must be available to give data to clients on the hour. As big-data is a necessity, artificial intelligence which can comprehend the large amounts of data, learn trends, understand the markets, identify potential clients, and relate the information effectively is needed.

The Ups and Downs of A.I. in the financial world

The financial sector must understand that artificial intelligence is based upon computer reasoning. And while there have been great advances in the security and the privacy of such programs, they are still programs. As such caution needs to be taken in making these programs. When too much goes digital, it can be expected that there will be a margin of manipulations. While this may be an acceptable risk in other sectors, when it comes to financial data and analytics, it is not. A minor “glitch” in A.I could mean billions of dollars lost, a crash in the market, or a foreclosure on a business.

Using artificial intelligence alongside the human factor is ideal. One must keep in mind that A.I. is a tool and not an alternative to the humanistic factor. Data which is collected should be screened for accuracy, clients should be treated as individuals and not just targets from a computer program, and finances must be secured by competent individuals who have the bank’s and the investor’s best interest in mind. Only in this way will a.i build and develop the financial institutions successfully.