The disruptive power of fintech to change traditional banks and shape the future of financial institutions is growing because of the latest innovations and advances in Artificial Intelligence (AI). The 7 ways AI helps facilitate fintech include security, fraud prevention, data analysis, predictive machine learning, process automation and financial advice.
7 ways AI is used in fintech:
Fintech means ‘financial technology’, the way new technological innovations replace traditional, human-led processes in banks and financial systems. Some examples of fintech include online banks like Ally, digital payment methods like PayPal and cryptocurrencies like Bitcoin powered by blockchain.
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AI stands for Artificial Intelligence, and it means the way that computers and other machines are able to ‘think’ intelligently like humans. AI is generally used to solve problems faster and more efficiently than humans can by using more powerful processing units and smart programming.
One way of programming machines to be intelligent is by letting them learn for themselves, either as humans do or with a different learning technique that codes the limits of what the machine can’t do instead of what it must do. This is called Machine Learning (ML), and it’s a subset of AI. AI and ML are not the same because ML is a type of AI that is increasingly used to impact fintech, and now the Deep Learning technique for ML is becoming more popular too.
Artificial Intelligence vs. Machine Learning
“In 2021, we expect AI to become even smarter, with more sophisticated chatbots and advanced functionalities – including switching utility and credit providers – as well as fraud prevention becoming the norm. This will improve the accuracy and personalisation of financial services and enable individuals to better access personal finance products, ultimately improving people’s financial well-being and supporting those who are keen to stay on top of their finances during these uncertain times.”
AI is able to help banking apps and other online financial services to verify customers’ identities automatically and more securely. This is called ‘Know Your Customer’ or KYC. One way to confirm identity online is asking users to take a selfie and a photo of their ID document. The AI technology Optical Character Recognition (OCR) is then able to scan the photos to check whether or not they match up to save a human from having to do this manually.
As voice recognition software improves, too, the expectation is that computers will be drafted in to add this extra layer of security to eKYC processes.
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OCR tech is also increasingly used to enable computers to read contracts and other documents. By scanning the image and converting the text into a format the computer can work with, the machines are able to process thousands of times more documents than a human surveyor or accountant can.
Then, this is combined with the additional AI tech of Natural Language Processing (NLP), which aims to teach machines to recognise human speech and writing patterns and which most people will have had more contact with via their smart voice assistants. Using NLP, computers are able to find inconsistencies in labour and service contracts, for example, or discover whether a certain document may be a fake in the aims of preventing fraud.
In banking apps like Revolut, AI is used to analyse users’ finances and compare their personal expenditure with their income, savings goals and monthly bills. This is then broken down and presented to the user in a way that’s easy to understand for people who aren’t experts in financial planning.
The fastest growing fintech app of all time, Cleo, takes this one step further and communicates these financial insights to users via chat. Cleo capitalises on the trend towards commerce and other services being available via chat in the same way we talk to friends on WhatsApp, Facebook Messenger and the like to act as a digital financial advisor. The chatbot is enhanced with NLP technology to communicate with end users in a friendly, relatable way about their personal finances, in the same way human financial advisors used to do in the past.
Chatbots enhanced with Natural Language Processing, like Cleo, are used as virtual financial advisors
Another way AI is being applied to fintech solutions is by improving the search function of bank transactions. While the computer is able to search through millions of transactions using their identifying codes, this has never been easy information for people to access and understand until now.
By converting those strings of codes into clear details of who the transaction was made to, when, how and where the company is located, AI lets you search for a particular transaction like you would search for something on Google. It also helps people get a clearer idea of their spending and reduces the number of calls to customer service hotlines, which in turn saves the company money.
So much for the frontend, user-facing applications of AI for fintech. On the backend, banks use AI to prevent fraud and money laundering. AI advancements have enabled a far higher level of compliance with Anti-money laundering (AML) laws.
Criminal organisations have learned to hide the sources of their illegally gained money over many years, but now banks are fighting back thanks to the power of AI to trawl through enormous stores of data, identifying patterns and recognising suspicious movements.
Perhaps the most useful advantage of AI for fintech marketers and salespeople, as well as insurtech underwriters, is the use of big data and ML to develop predictive models of customer behaviour. Propensity models take vast amounts of behavioural data on past consumer actions and analyse it with cognitive processing to predict what they will do in the future. In this way, AI is used for decision making in business.
This kind of work was previously done by human data analysts, but they are obviously not able to process as much data as a computer can. For insurance companies, this technology is used to create more accurate predictions of applicants’ future behaviour, and they can adjust their insurance policies and premiums accordingly. For lenders, ML-powered data analysis is better and faster at predicting and assessing loan risks and in corporate finance it provides an additional tool in the risk assessment for mergers and acquisitions. For sales and marketing in the banking sector, these predictions help to create product propensity models for better targeted campaigns and product development.
“Process automation is one of the major drivers of artificial intelligence in financial organizations. However, it is further evolving into cognitive process automation, where AI systems can perform even more complex automation processes.”
Finally, and perhaps most importantly, AI can repeatedly perform tasks, freeing up employees in the financial industry to focus on more productive work. Wealth managers are using AI to speed up the creation of status reports for clients, while banks are leaving the decision-making process of who to grant a mortgage to in the hands of robots. This does speed up the process for both bankers and loan applicants, but it has the downside of leaving out the element of human empathy and trust from the loans process, if it was ever there to begin with.
IBM has a cloud-based AI tool called Watson, meanwhile, that has been trained to understand complex banking regulations so it can provide financial information to those who need it in a matter of seconds rather than days. AI automation of workflows in the financial sector is complementing the human factor to positively impact the working practices of the business world, and this trend is set to continue in the future.
AI is changing the world of fintech businesses with these seven applications, and in turn fintech is helping banks, government organisations and eCommerce retailers who use payment gateways to become more secure, agile and customer focused.
Companies around the world, from established corporations and non-profit organisations to SMEs, unicorns and other startups, are investing in AI-powered fintech to boost their financial capabilities. With the help of experienced and professional agencies dedicated to deploying this kind of digital transformation, everyone from schools to healthcare facilities to retail merchants can benefit from fintech.