How Will Artificial Intelligence (AI) Impact The Banking Industry
The use of artificial intelligence (AI), machine learning, and robots is no longer a tribute to fashion, but a profitable investment. The unrealistic expectations that the excitement around these technologies inevitably generated are being replaced by very real business scenarios.
Introduction to Impact of Artificial Intelligence:
In the field of finance, this is especially noticeable. Most financial specialists are ready to entrust the algorithms with accounting for transactions. They detect fraudulent schemes. They plan resources and generating reports. However, the introduction of new tools is not easy, and their use generates new risks.
Artificial intelligence that has successfully survived the early stages of the maturity cycle is reaching a plateau of productivity. This has been fueled by exponential data growth and the parallel development of computing power. As a result, in the first half of 2018 alone, there were nearly 3,400 AI and machine learning startups globally. Of course, some of them will fail. But someone will certainly manage to create real instruments for the banking ai solutions.
Scope of application
Impact of Artificial Intelligence (AI)has a wide field of application in modern finance. The main directions are the fight against fraudsters, the credit assessment, control, and analytics of operations.
Algorithms can detect fraud before it occurs and verify transactions. It’s across all of the bank’s portfolios in minutes. And AI makes an assessment of a potential borrower more accurately than a human. While taking less time and taking into account more parameters. In 2018, more than ten domestic banks have already used this tool.
Collector robots, which now work primarily with bank customers with little debt, are also AI. A human operator manages to make about two hundred calls a day. And a robot is capable of a much larger number of such operations. Automation of routine processes can also save you from human error that occurs due to fatigue. As well as reduce company costs.
Many financial institutions are implementing AI chatbots that can answer the most basic and common customer questions. Impact of Artificial Intelligence includes chatbots. The largest banks have launched mobile applications with Robo advising. Now the algorithm answers customers’ frequent questions and in a matter of seconds. It can form an investment portfolio in accordance with the capabilities and interests of a particular client. He can also remind you to pay bills. And prepares detailed cost analytics, which allows the client to manage their cash flows. And in this, companies have gone far ahead compared to many European and even American banks. They are more conservative.
Another important area where AI is already irreplaceable is compliance. In terms of legislative changes, the financial industry is like an active volcano. Small shifts occur every day. AI can learn, remember and help comply with all the requirements of legislators. It’s from KYC and anti-money laundering regulations to laws governing asset management. No human error – no claims from the regulator.
How to teach the machine
One of the artificial intelligence subsystems is called machine learning. Impact of Artificial Intelligence (AI) is based on a mathematical model that identifies certain patterns in datasets and predicts the development of a situation. It allows you to work with a large amount of structured and unstructured data, including photos, videos, and speech. And then it analyzes and identifies acting insights. And technologies are already doing better with these tasks than humans.
Difficulties on the way of implementation
A common problem with a new technological solution is confusion with terminology. You are unlikely to find two specialists who adhere to the same definition of AI or machine learning. Oftentimes, intelligent systems, in which there really is nothing like the work of the human brain. They are credited with exceptional capabilities. And this lack of understanding gives rise to fear of new tools.
Last words on Impact of Artificial Intelligence:
The accuracy of the results of AI work critically influenced by the quantity and quality of the initial data: if on a small sample the probability of error is 20%. Then when working with a large data set, it is reduced to 2%. According to the ACCA survey, 17% of professionals working in the financial sector believe that there is not enough data or it is of low quality to fully launch AI.