It feels as if artificial intelligence is the biggest buzz word in technology at the moment, and seemingly not a day goes by without hundreds of news articles popping up about the use of AI in various industries. But there’s good reason for all that excitement, as the AI software market is forecast to be worth over $126 billion by 2025. Moreover, PwC estimates that AI will be contributing $15.7 trillion to the global economy by 2030.
In the financial industry, banks are particularly excited by the benefits that AI will bring. As technology advances and regulatory frameworks are updated to cover the implications of using AI across financial markets, the 2020 $7.1 billion global Fintech AI market is expected to rapidly expand over the coming years. Here are a few reasons why AI is such an important area for finance and how it’s changing it.
Making Credit Decisions
AI is increasingly being used to make credit decisions as it can supply a fast and more accurate assessment of a potential borrower. Due to using a more complex set of rules than existing traditional credit scoring systems, it’s able to examine those without an extensive credit history without blindly assuming that they have a high risk of defaulting. It can draw from other types of data to personalise the credit decision, ensuring that lenders have a better picture of the risk in lending. It also has the benefit of being less likely to be bias than a human.
Deploying Machine Learning
Machine learning, where algorithms are automatically improved by using massive amounts of data and allowing the computer to gather experience, has gradually become more popular in the financial sector, particularly in fields such as quantitative finance. Quants, as people employed in the field are known as, use mathematical models combined with massive datasets to analyse financial markets and securities. Machine learning can be a huge benefit when carrying out risk management, where algorithms can be deployed to help trawl through huge amounts of data, although it’s still a relatively new addition to the field.
During the trading process, machine learning can be applied to improve trades by highlighting when to take a risk and what the profit/loss outcome will be. It can automate trading processes and find opportunities that a human may miss amongst big data, as well as examining both databases and the news to ensure traders can stay on top of things.
In this sense, AI is acting more as an advisor and a predictor of market behaviour, and it therefore shouldn’t be blindly applied. Due to this, it won’t totally replace the human factor and remove quants from the equation, at least for the time being.
Providing Quick & Seamless Customer Service
In the personal banking sector, AI can supply fast, 24/7 customer service in the form of smart chatbots. These bots can answer common questions and provide self-help solutions, which takes some pressure off busy call centres. While it’s likely that people will always want the option of speaking to a human, AI is getting smarter every day and becoming increasingly capable of engaging in a conversation as natural language learning progresses.
Reducing The Risk of Human Error
When dealing with massive amounts of data and a busy financial workload, humans are generally prone to eventually making errors, especially when doing repetitive tasks. AI can be used to automate those mundane tasks that consume thousands of work hours. It also works out at a lower cost, meaning reduced payrolls too. By taking over these small yet time consuming tasks, it can free up workers to focus on the big picture and helps them concentrate on driving profit.
These are just a few of the ways that AI is changing the financial industry. AI is here to stay, and it will continue to reshape the financial industry alongside many other industries. While it may take time and money to implement AI into the daily workings of a business, neglecting to go down this path may well cost companies in the long run.
