While the inner workings of different FinTech products and services vary, there is an increasing reliance on artificial intelligence (AI) and automation throughout the industry. These technological advancements offer new possibilities for gaining customer insights, revolutionising security and enhancing the digital transaction experience for all users.
Looking into the future what are some key ways that experts believe AI will impact the future of FinTech companies, and what the flow-on benefits will be for the industry and consumers.
Improving the customer experience
AI will continue to enhance the experience of FinTech customers in a number of ways. Two prime examples include:
Chatbots: AI-powered chatbots are already being used to solve the most frequent problems for users of financial services. This automation of routine services reduces the workload on call centres and enables companies to offer customer support 24/7.
With chatbots handling the more mundane tasks, human staff can focus their attention on finding solutions to more complex, nuanced issues. They can also tackle emerging problems. The use of AI-driven chatbots is likely to increase over time in the FinTech space.
Personalisation of banking apps: AI will be increasingly leveraged to personalise financial advice to customers through banking apps. This has the positive impact on individuals being able to to track their finances better, be more money-savvy and ultimately reach their financial goals, and gives banking apps a marketing advantage over the competition.
Tighter security
AI is an important weapon in the fight against fraud and cyberattacks. It will continue to be an invaluable tool for helping often under-resourced security managers keep up with the many and varied threats to data protection and IT infrastructure.
Some specific ways in which AI automation will bolster security going forward including the prevention of identity theft. AI is already involved in varying degrees in banking apps that can only be accessed via fingerprint or face recognition.
With its eye-popping diagnostic capabilities, AI can analyse huge volumes of data to rapidly detect hidden patterns and anomalies resulting in faster and more accurate fraud detection. Anything that looks suspicious can be immediately flagged or blocked before it’s too late.
Efficient AI-powered fraud prevention systems will do their part in improving the image of finance companies, deterring existing clients from migrating and encouraging new customers to sign up.
Fraud is an ongoing issue for the finance industry. The ability to identify and respond to fraudulent activity is where many FinTech businesses recognise the high rate of return on investment in AI technology.
Enhanced risk assessment
AI algorithms will play a greater role in assessing a client’s risk. An example of this includes credit score evaluation where AI techniques such as neural networks are set to make an impact on the credit evaluation space where highly predictable and explainable credit scores are in demand. Lenders, regulators and consumers all stand to benefit from new generation AI. Financial institutions will have the tools to approve more customers for credit without exposing themselves to greater risk. At the same time, they’ll also be able to better explain their lending decisions to anyone who applies for credit.
Better customer insights
FinTech businesses will increasingly analyse and predict customer behaviour using AI application programming interfaces (APIs). An instance of this is when a client requests information about their expenses for a defined period. The FinTech company will leverage AI APIs to predict the client’s next request and provide that information in the same response. Not only will this enrich the user experience, but it will also reduce the burden of multiple requests on the company’s systems.
Financial forecasts
AI will also make its impact felt in financial forecasting where it will be deployed to identify and analyse changes in financial data patterns.
In particular, AI will be utilised to unlock the full potential of unstructured data – that is, data that lacks a predefined structure. Companies deal with large volumes of unstructured data from a variety of sources on a daily basis. This includes in-app reviews, customer feedback, social media and so on, all of which contain useful data that can assist companies in making financial forecasts.
This unstructured data will begin to play a greater role in decision-making, the improvement of processes and products, cost cutting, the fine-tuning of marketing strategies and the race to gain a competitive edge.
IT infrastructure and AI
As with any other digital business tool, AI requires the right IT infrastructure in order to perform at optimal levels. If your software and hardware infrastructure needs upgrading, reach out to our team today. We can help find a finance solution that optimises your company’s spending on IT infrastructure.
