The Impact of AI On Fintech
Everyone seems to be talking about AI at the moment. On the one hand, people are extolling the possibilities of Chat GPT and using it to write poetry, novels, and university essays. On the other hand, leading tech pioneers are issuing warnings to governments about possible human extinction at the hands of AI. Proceed with caution seems to be their advice.
However, many of us may not realise how embedded AI is already in our daily lives. While it might be making headline news right now, it is deployed in much of the tech we are accustomed to using. The fintech industries are probably one of the most significant users of Artificial Intelligence, and the market size is expected to be worth $31.7 billion by 2027.
AI and machine learning allows financial applications to have a more personalised approach to the transaction. The customer’s behaviour is understood better; therefore, proactive solutions that are relevant to the individual can be offered. This is possible due to powerful algorithms which process vast amounts of data.
AI is particularly useful for fintechs offering loans, as financial companies can use it to anticipate loan risks. In addition, AI is excellent at helping companies detect fraud through monitoring patterns of behaviour. It is instrumental in recognising anonymous or unauthorised attempts to get around security protocol.
Cybercriminals try to bombard secure online environments to obtain sensitive information. Likewise, phishing scams via emails and texts are trying to collect passwords and bypass security protocols. However, fintech apps like eWallets and digital payment systems use machine learning and AI to secure customer accounts.
These fintech apps use various techniques, but facial recognition is one of the critical ways accounts are kept secure. Therefore, for example, online casino customers betting with Apple Pay have a double layer of security; the platform’s security protocols and Apple Pay’s enhanced security features. Without AI, this process would be infinitely less safe, lengthier, and unreliable. With AI, each time an Apple device is unlocked using facial recognition, the TrueDepth camera is deployed. It recognises the user capturing accurate depth data and an infrared image. The information is matched against the stored representation. If they match up then the transaction is authenticated.
AI is also helping to improve customer service in the fintech sector. For a long time, people have complained of inefficient service. Historically, the banking sector has not been able to respond quickly enough to demands and queries from the public. However, people no longer have to wait for hours on automated phone lines, as AI chatbots can direct them to the correct call handler at a much faster pace. In addition, if the customer needs to deal with a live operator, one customer service operative can deal with multiple queries simultaneously.
Chatbots are often available 24/7, and there are customer service agents around the world who can take live chats if required. However, AI chatbots are often able to resolve customer questions. In the past, the customer had to trawl through the Frequently Asked Questions to find an answer. Unable to do so, they would call an automated phone line and have a long wait to get their question answered. Now AI can rapidly filter the FAQs and get a quick response back to the enquiry. This means that only non-standard queries have to go to the live operator.
Just as a chatbot can deliver rapid answers by filtering consumer queries, fintech can help lenders make immediate initial responses to lending enquiries. For example, AI is used to gather information on a loan application and run it against existing data sets to decide if the applicant is a reasonable credit risk. In the past, securing a loan or overdraft might have entailed a lengthy meeting with a bank manager. Now, Buy Now Pay Later fintech solutions like Klarna and PayPal Pay Later return a lending decision in seconds.