Which AI technologies are used in banking

Artificial intelligence is the future of banking

As far as the degree of maturity of artificial intelligence is concerned, the financial sector ends up on the relegation point. Data protection and job loss are pressing issues. However, the many advantages of the technology can be observed from the front to the back office and point the way to the future.

Artificial intelligence opens up a wide range of new opportunities for banks

FinTechs, restrictions due to legacy systems and conventional business models: Traditional banks have to face new challenges. The use of AI technologies can help. Machine learning, deep learning or algorithms for the further processing of big data bring advantages for the financial sector. For example, intelligent digital assistants improve service, data models automate credit decisions and fraud can be detected through pattern, face and voice recognition.

Artificial intelligence has positive effects on banks

A recent study by Infosys examined the influence of artificial intelligence and AI maturity level in companies. The survey confirms that more and more companies from a wide variety of industries are implementing AI technologies. According to this, organizations expect to generate 39 percent more sales with the use of AI by 2020 and at the same time save 37 percent in operating costs.

More than half (56 percent) of the respondents from the financial sector have been using AI for one to three years. In general, according to the study, companies from the financial sector invest an above-average amount (14.6 million US dollars compared to 6.7 million in the other sectors) in technologies. However, the market segment comes off the third worst of all surveyed sectors. The development is being slowed down primarily because of the reluctance of banks to deal with issues such as data protection or information security.

Another important factor is worries about losing a job: One in four respondents in the financial industry believe that automation and AI will soon make many positions redundant. A lot of monotonous work is taken over by AI-controlled machines and frees workers from time-consuming tasks. This gives employees more time to express their creativity and develop new ideas and can respond more intensively to the wishes of their customers. Employees are able to develop better products and services, define new models for creditworthiness, and manage risks. In short: human skills are expanded and even improved by new technologies - as history has shown in previous technical revolutions. The success of the introduction of AI technologies therefore also depends to a large extent on employees seeing the technology as an opportunity to cope with the ever-increasing demands from customers, competition and regulators.

Use cases for artificial intelligence from the front to the back office

But AI also improves the customer experience at the same time. Here are a few examples: Technologies are far more successful and accurate in facial recognition than humans. Intelligent software sends replies to customer emails faster and more efficiently than a human employee. AI improves customer contact through agility, precision and customer proximity.

The various technologies are already being used successfully in many banks. The Australian Westpac relies on visual recognition. For example, the bank's customers can activate new cards using their smartphone cameras. In turn, Santander recently became the first bank in the UK to introduce voice-activated payments. First Direct and Barclays, on the other hand, have been using voice recognition to authenticate their telephone banking customers for some time.

But AI is already being used in personal customer contact. In Japan, two banks are already working successfully with robots: "Pepper" entertains Mizuho Bank customers with games and a multimedia offering and provides product information on request. “Nao”, the other robot, greets customers in the Mitsubishi UFJ branches and asks what they want. This allows bank employees to concentrate on customer service.

However, adopting AI in banking isn't just about the front office. The technology also has advantages for the middle and back offices. In credit risk management, for example, banks are now using intelligent algorithms created by machine learning and prescriptive analytics. For example, they help financial institutions to interpret repayment histories. The Aidyia hedge fund is based purely on AI and all trading transactions take place without human support.

Another example comes from the insurance industry: a robot that costs around 10,000 to 15,000 US dollars processes five to ten times as many insurance claims as a human representative. At PayPal, on the other hand, an AI system running on open source can not only detect suspicious transactions, but also distinguish false reports from real fraud. The weighty US bank JPMorgan Chase & Co also uses a machine learning program. COIN (Contract Intelligence) decides on a loan application in a few seconds. A team of lawyers and loan officers would spend 360,000 hours a year on this task.

Artificial intelligence is the future

All of this shows: Artificial intelligence can no longer be stopped. In less than a decade, Generation Z will be the banks' most important customers alongside millennials. You will grow up with the latest technologies, work with multiple screens at the same time, communicate with emojis and enjoy the ease of interaction using natural language. But it takes more than just human skills to understand and deal with the needs of these customers. In order to meet this challenge, humans and machines have to work together in symbiosis. After all, completely different tasks await bankers in the future: anticipating products, recognizing customer trends and maybe even managing digital currency portfolios.