The financial services industry was one of the first to appreciate and apply artificial intelligence. It has long been used by financial and technology companies seeking to improve the quality of existing services and introduce new ones. Due to the ubiquity of artificial intelligence, banks, credit and insurance companies have also adopted this technology to retain customers and market share.
Financial companies constantly collect complete data about service users, but they do not use it effectively to predict the needs of their customers. They need to find ways to combine such valuable information with modern technology, and that’s where artificial intelligence (AI) solutions can help.
Financial technology (FinTech) is digital innovation in the financial sector. At first, the term was limited to innovative ways to simplify payments and transfers. Thanks to the revolutionary advances in mobile and internet technologies that have occurred in recent years, fintech has become a participant in explosive growth. Nowadays, this phenomenon belongs to a wide range of technological interventions in the financial services industry:
Fintechs are also companies that provide exclusively financial services using digital technologies, for example, online and mobile banking, electronic and mobile payments outside banks.
In 2018, a related concept—techfins—appeared. These are tech companies that additionally offer financial services alongside their main technology-based products. And financial products are technically better than those offered by banks. Currently, it is a narrow segment of the IT industry that includes corporations such as Google, Amazon, Apple, and Facebook in the US or Alibaba and Tencent in China. They are not considered financial companies, fintechs, or digital banks, because they operate without the support of traditional banks, and their main activity is not related to finance.
Although AI has long existed as a technology, it is becoming more and more necessary for companies that pay attention to actively developing areas: smart automation, machine learning, robotics, analytics. Of course, financial service providers are working hard to implement these features for the sake of automating recurring tasks, consistent customer service, in-depth behaviour analysis, and effective fraud detection.
Strong market competition and new customer demands have led advanced financial companies to trust artificial intelligence. And AI turned out to be a reliable assistant to stay ahead of the competition and provide customers with personalized service at a reduced cost. Here are some institutions that get help from technology in upgrading old services or providing new ones:
AI-based solutions help fintech startups compete with these types of organisations or establish cooperation with them through B2B. And in B2C, there are intermediaries who make money on creating complex services from many small ones provided by different companies.
In addition to solving tasks in finance, AI is able to establish any business processes for smooth operation. For example, it can automate internal procedures, reduce processing time for unstructured and big data, reduce repeated costs, and generate reports. AI quickly gains knowledge and self-learns, improving human-machine interaction.
Financial companies were the first to use mainframes and relational databases. They were looking forward to the next level of computing power.
In the last 20 years, the computing race has revolutionised again. Now in finance, artificial intelligence is helping to increase efficiency and improve results. Machine learning, deep learning, neural networks, big data analytics, and other technologies have enabled computers to process diverse and vast datasets.
In the early days of banking, bankers were pretty tight with their clients to help them manage their finances competently. But in today’s digital world, the personal connection is gone. To restore it, you can use artificial intelligence in banks. After completing machine learning, it will be able to process a large amount of information about customers. Then AI will analyse this data and select the products that are suitable for customers. This personalized approach helps to achieve a high level of their satisfaction.
According to the prediction of Autonomous Next, by 2030, AI will help banks cut expenses by 22%. In money terms, the global economy will reach $1 trillion.
As per research results of Emerging Technologies, companies that use AI in financial and operating activities have increased annual revenue by 58% and annual net income — by 80%. The research was conducted by Enterprise Strategy Group together with Oracle in 2019. Their researchers surveyed 700 CFOs and COOs from 13 countries online.
Russian banks have been boosting revenue through saving for a couple of years now. For example, in 2020, Sberbank earned an additional $3 billion by using artificial intelligence and data analysis to manage risks.
Data-driven management decisions lead to a new style of management at a lower cost. Instead of asking expensive experts, bank and insurance executives can ask the right questions to machines.
AI will analyse patterns and trends in data, eliminating the need for a team to process huge amounts of information. Then, it will provide guidance to help leaders and teams make the best decision.
According to an assessment of IDC, a company, which employs about 1000 members of the intellectual labour staff, annually spends $5 million on information search, unsuccessful attempts to find data, and duplication of existing documents (if it’s impossible to find necessary ones). AI helps to find data in corporate systems by defining a general idea of a request and finding documents with important information, for example, financial reports, agreements, and presentations.
Predictive analytics can influence business strategy, drive sales, and optimise resources. It can change the rules of the game, improve business operations and internal processes.
In the financial services industry, predictive analytics is used to collect and organise data and analyse it using advanced algorithms. Amounts of data are then used to find patterns and predict results.
Predictive analytics made by AI can help calculate credit scores and prevent delinquency of loans. Its recommendations will tell you what will happen next: what services consumers will buy, how long employees will work, and so on. Thanks to AI, it is possible to create a customised prescriptive solution for each client.
AI can help insurers automate underwriting and use draft information to make better decisions about customers. Automated agents will assist users in making insurance requirements.
The need for insurance usually appears after a loss has occurred. Automatic underwriting will significantly speed up the process by providing the necessary tests and linking the relevant datasets. Instead of paying for expensive treatment (if without insurance), it is better to immediately identify the risks of diseases and prevent them. Previous data can be used to determine risks in order to reduce the likely losses to a policyholder and an insurer.
Your customers will also appreciate the benefits of artificial intelligence and use it. Offer them automated tools to facilitate investment or financial accounting; help cut expenses and increase income. Providing such an opportunity will increase audience loyalty to your fintech company.
Financial planning virtual assistants advise the company’s clients on high-yield solutions and assist in asset management. They automatically monitor events and trends in the stock, forex, and commodity markets taking into account the user’s financial goals and portfolio.
AI competently chooses recommendations for buying or selling assets, much like experienced financial advisers. That is why such systems are also called robo-advisers. They are often included into services offered by both reputable financial companies and fintech startups.
Financial institutions have long offered advisory services on savings management and cost savings in the B2C segment. Fintech companies do the same, only cheaper.
The potential to expand services, reduce costs, and improve customer experience through automation no longer seems like science fiction, as companies now have access to artificial intelligence and machine learning. However, the fintech industry needs to work closely with developers, designers, engineers, and technicians. Only they can implement your new concept of a financial product so that you can effectively monetise it.
In the face of tough competition in the financial sector, modern AI-based software will help increase the competitiveness of your business and attract new customers.
If you want to gain a foothold in the financial services market using AI, then Polygant is ready to develop the necessary solutions for you. To find out the cost of work and development timeframes, as well as to receive detailed information about the services, fill in a short application, and we will immediately contact you.