The financial services industry was one of the first to appreciate artificial intelligence (AI). AI 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, traditional financial institutions such as banks, credit and insurance companies have also adopted this new 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 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 in recent years, fintech has exploded in growth. Nowadays, this phenomenon belongs to a wide range of technological interventions in the financial services industry:
Fintechs are also companies and startups 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 and more convenient 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, and others. 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 personalised service at a reduced price. Here are some institutions that get help from AI 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.
Besides, AI is able not only to solve financial issues but also 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 is rapidly gaining knowledge and self-learning, 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 fintech, where artificial intelligence is helping to improve efficiency and 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 wisely. 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 huge amount of customer information. Then AI will analyse this data and select the services and products that are suitable for customers. This will help banks find what their customers want and achieve a high level of customer satisfaction.
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.
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. Huge amounts of data are then used to find patterns and predict results.
AI predictive analytics can help calculate credit ratings and prevent delinquent 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 customer decisions. Automated agents will assist users in drafting 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 both the policyholder and the 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 costs and increase revenues. Providing such an opportunity will increase audience loyalty to your fintech company.
Financial planning virtual assistants advise the company’s clients on profitable solutions and assist in asset management. They automatically track events and trends in the stock, forex, and commodity markets taking into account the user’s financial goals and portfolio.
AI competently selects recommendations for buying or selling assets, much like experienced financial advisers. That is why such systems are also called robo-advisers. They are often incorporated into services offered by both reputable financial companies and fintech startups.
Financial institutions have a long history of offering advice on savings management and cost savings in the B2C segment. Fintech companies do the same thing, 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. But 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, it is AI-based applications and programs that will 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.