The last couple of years have marked an important milestone in the development of AI. History will reveal these were the years that have seen AI going from a desirable step in changing the world to a tangible way to improve products, services and even lives. We have virtual assistants, robots that play chess better than world champions, programs that mimic the human brain (deep learning, neural networks), and this is only the beginning.
Having discovered the power of artificial intelligence, people all over the world are doing their best to integrate its capabilities into their businesses. According to data from Gartner, by the end of 2020, 20% of citizens in developed nations are expected to use AI for everyday operational tasks. Furthermore, the same study mentions that 85% of Chief Information Officers will be piloting AI programs for their organizations.
One domain that has fully enjoyed the benefits of artificial intelligence, and will certainly continue to do so in the years to come, is fintech. From friendly chatbots that help you open a bank account and manage your finances, to more reliable credit scoring and fraud detection, AI has significantly improved the traditional way of doing things in financial services.
Why is artificial intelligence an asset for fintech?
An increasing number of people are becoming more tech-savvy so companies and banks need to innovate in order to remain relevant. In a world that generates data faster than the speed of sound, it is difficult for them to keep up with such pace.
Here is where AI steps in. Artificial intelligence and machine learning process huge amount of data about customers. The information is then analyzed, compared and, in the end, translated into more suitable services and products. This way, customer satisfaction is achieved faster and their expectations are better managed.
Customer support revived
Customer-oriented systems such as text chats, voice systems and chatbots are no longer a novelty. They can carry on human-like conversations and deliver expert advice at a low cost. A lot of banks and companies offering financial services have these capabilities in place. For instance, Wells Fargo is the first US bank to pilot an artificial intelligence chatbot on Facebook Messenger. Wells Fargo Bot serves customers directly on social media and can be accessed through desktop, smartphone, and other mobile devices. Cleo is another AI interface that helps individuals manage their money. It can budget, save and track your spending. So, next time you’re wondering if you can afford a new purchase, just ask Cleo and the AI system will handle the calculations for you.
These are not the only AI-powered chatbots that are taking banking conversations to the next level. A lot of companies invest in such systems to save time, improve customer services and cut costs. A report by UK-based research company Autonomous predicts that the finance sector will leverage AI technology to cut 22% of operating costs – in total, reaching USD 1 trillion. Also, Kai-Fu Lee, CEO of the investment company Sinovation Ventures, which specializes in AI and high-tech ventures, believes that bank teller is the first profession that will be replaced by AI. However, he states that it will most likely take another decade before human interaction is completely removed.
Credit scores and loans
The use of AI in this field brings a major improvement to the decision-making process by turning it into a faster and more reliable one. This translates into allowing more people to apply for a loan or credit, thus increasing their chances of actually getting it.
Singapore-based SaaS company Lenddo uses alternative data points for credit scores. The company analyzes behavioral traits and smartphone habits to build models and decide whether a certain consumer is credit worthy or not. More important is the fact that the company does this for consumers in emerging markets, where standard credit reporting barely exists.
In addition to reviewing the traditional financial data, the company also takes into account personal interests of individuals and the financial apps they have on their smartphones. This shows how careful consumers are with their finances. Selfies are also an important indicator as they might reveal the age segment of the consumer – according to statistics, young people are more inclined to take selfies. Once the data is gathered, AI is able to analyze it and compile it into models that are later on used to make predictions. Furthermore, the system can help sort through a variety of data points that might indicate financial responsibility, in case the consumer has no relevant credit history.
Although not all companies approach credit scores as Lenddo does, the help of artificial intelligence is undeniable. With AI, lenders can get a more precise look into someone’s creditworthiness and also be able to address the individuals that would not normally be taken into account.
Since the advent of electronic commerce and online banking, payment fraud is a constant in our lives. A 2018 report from McAfee shows that the cost of cybercrime currently reaches 0.8% of the global gross domestic product. The most prevalent type of financial cybercrime is credit card fraud, which grows at a fast pace due to the increase in online transactions. But AI tools and machine learning algorithms are quite successful in detecting financial fraud.
Nowadays, the amount of customer data available to retailers or cybersecurity companies is huge. Together with transactional data that is updated as transactions occur, AI tools can be used to effectively identify credit card behaviour patterns that are not normal for specific customers. Most companies train machine learning models that are constantly updated to keep the quality of decisions high and the false positive rate low. This way, they are able to detect data anomalies in five to ten milliseconds and make decisions based on information as it happens, even anticipating results.
In the fintech industry there is a lot of hype around artificial intelligence. But this is not the only field in which AI has proved to be really efficient. Lately, we have witnessed a considerable surge in implementation of AI-driven use-cases in almost all domains. For most organisations, AI is quickly becoming a key technology to help automate instant decisions, maximize the detection performance as well as cut costs.