AI: Evolution, Not Revolution
Unlike the sensationalist dramas of I, Robot or 2001: A Space Odyssey, AI adoption in financial services is set to only improve the human experience in the financial sector.
The financial sector has been especially keen to reap the benefits that Artificial Intelligence (AI) technology can provide, but there are still some fears that these innovations will cause huge job losses and remove the human role from businesses. Here Frank Abbenhuis, VP of Strategic Alliances at Axyon.AI, discusses the current AI landscape, touching on some the key steps ahead.
What is AI now?
Over the past 20 years, AI adoption has increased dramatically, due to some key shifts in the market. Firstly, technology has advanced hugely – not only in its ability to process large quantities of information in a fast, accurate manner but also in how inexpensive computing has become. The data that AI utilises has also become hugely prolific, with both individuals and businesses producing huge amounts of data on a daily basis. The result is not only cost effective and fast, but also incredibly accurate.
However, even with this foundation, AI would not be witnessing increased adoption if it were not practical for financial services. Through AI, financial institutions are now able to offer an improved customer experience, identify new sources of business growth, determine more effective models to follow, and develop broader aspects of the organisation: from enhanced productivity to better risk management.
AI as a tool
This increased adoption of AI has inevitably caused concerns over job security, with fears that jobs will become automated as a result. However, the reality is that AI has come at an ideal time to address the demands that banks are facing.
For example, the customer experience is now a key focus in building a business’ reputation. To remain competitive, companies need to move away from the ‘back office’ process-driven tasks and increase their client engagement strategies. As such, the more that AI can support these internal functions, the more that the business invests in building those vital client relationships.
Naturally, there are also concerns around how AI can be implemented. Fortunately, banks and other businesses in the financial sector often have enough historical data available to train an algorithm and run the task automatically. If this automated function is then combined with human oversight, the business can improve the quality of advice given to clients. In this way, AI no longer takes over a person’s role, but enhances their functionality in the business.
Making the most of data
Even with this progress, there are still certain areas in financial services where AI can be enhanced. For example, syndicated loans desks have a wealth of historical market data that is not leveraged to its full potential.
If AI were implemented here, algorithms could be used to analyse all previous deals and produce the likelihood of specific actions being taken. In this scenario, AI would not only be able to access which investors participated in every syndicated loan, but also the high-level structure of these loans – something that would be impossible for a single human mind to achieve.
This is just one example of how AI can enhance those in capital markets and asset management. The sheer amount of data that these sectors produce make them ideal for the predictive capabilities of AI. The only impact this level of automation will have on those working in these industries is smoother processes and improved output.
With all the fear that can surround new technologies in financial services, AI is set to only improve how people work in the sector. Through taking advantage of huge amounts of data, AI has the potential to streamline internal process and increase overall output – with the added benefit of improved accuracy and reliability.