Artificial intelligence has already made a significant, positive impact on the financial services ecosystem and we can only expect this trend to accelerate in years to come. AI has the potential to radically transform businesses but only if they deploy it with appropriate diligence and care. A 2020 report by EY and Invesco anticipates that AI will expand the workforce in fintech by 19% by 2030 as the industry stands to be one of the largest to benefit from the efficiency gains and innovation the technology can bring through operational optimisation, reduction of human biases and minimisation of errors in anomalous data. 


Talent Shortage Within FS 

According to a report by Bloomberg, listings for AI-based jobs within the financial sector increased by approximately 60% from 2018 to 2019. This demand for workers with AI expertise is not only seen within the financial industry but across a variety of other professional sectors, such as e-commerce, digital marketing and social media. The jobs market has had little time to respond, resulting in a shortage of access to talent. A study by SnapLogic found that whilst 93% of UK and US organisations are fully invested in the use of AI as a priority in their business, many lack access to the right technology, data, and most importantly, talent to carry these goals out. This ‘skills shortage’ is a major obstacle to the adoption of AI in business, with 51% of those surveyed acknowledging that they don’t have enough individuals trained in-house to make their strategies a reality. Machine learning can offer benefits in many forms and different businesses have varying needs. There is no ‘one size fits all approach’ when adopting and deploying AI, which can make it a costly process for many organisations not equipped with the right tools.  


Enhancing Fraud Detection

One of the biggest use cases of artificial intelligence within financial services is fraud protection. With the rise of online banking and the exponential growth of digital payments, banks have to monitor huge swathes of transactions for fraudulent behaviour. This huge influx of data points poses major issues for the human brain but actually maximises the effectiveness of ML systems. We’ve seen significant growth in the use of deep learning, with most major retail banks now relying on machine learning tools to recognise and flag suspicious activity. To keep up with the pace of criminals and comply with stricter regulations, service providers have to look beyond traditional methods and implement hybrid strategies built around holistic understandings of behavioural and anomalous data.


Better Serving Customer Needs

Financial services companies are increasingly leveraging artificial intelligence to deliver tailored services and products for their client base. For those banks mining data effectively, AI provides the ability to serve customer needs across multiple channels, and in some cases to grow operations at an unprecedented scale. Tools such as chatbots, voice automation and facial recognition are just a few of the ways banks are using AI to streamline and personalise the user journey for their customers. Importantly, consumers are increasingly literate in automated services and their expectations are constantly rising as the technology improves, meaning organisations must constantly adapt or risk being left behind.


Continuous Adoption of Artificial Intelligence

Artificial intelligence and machine learning have already enhanced numerous capabilities for the financial sector, improving recommendations, customer experience, and efficiencies via automation. AI will continue to dominate different parts of the financial sector, and the acquisition of machine learning and data science talent will become the norm. A recent survey from the World Economic Forum attests to this, with nearly two-thirds of financial services leaders expecting to be mass adopters of AI in two years compared to just 16% today.  Acquiring the right talent to drive machine learning and AI in organisations will remain a challenge as innovation is focused in different areas and new technologies are being implemented. However, the multiple benefits that come from implementing AI and machine learning are clear, and it will be a key area of focus and growth for businesses within financial services over the next decade.

Read the whole analyses of the recent changes in the role of AI and the impact it is set to have on the finance sector in years to come to by Alex Housley, CEO and founder of Seldon here.