The future generation of financial services will already be built on the foundation of artificial intelligence. However, this technology’s prime is still ahead.
AI in FinTech is indeed in a period of large-scale piloting and testing and so far focuses mainly on highly specialized applied tasks. For example, in chatbots and voice assistants, AI helps to close large blocks of communication with customers, but so far the solutions are not always optimally trained and configured. On the other hand, in some areas, artificial intelligence shows itself as a fairly mature technology: for example, in customer scoring, biometrics, computer vision, and antifraud.
Without long conversations, let’s discover what is happening with AI in the FinTech market and a little bit more detail about fintech application development.
Why Should FinTech Use AI?
AI in financial market has sped up access to products for many clients and automated some processes, which also covers the speed of service. Another reason is cost optimization.
In particular, thanks to predictive analytics, which can influence business strategy, sales promotion, and resource optimization. It can change the rules of the game, and improve business operations, and internal processes. Therefore, you should be involved in this AI marathon, and if you need to boost your team’s productivity, and save time and money, contacting a prestigious AI Consultancy is the answer to shorten this progress.
The Most Popular AI Use Cases
- Customer scoring: Automated evaluation of loan product applications from customers. An application for a loan from a major company used to be examined for two to three weeks, which required the time and effort of several professionals. Now, it takes less than 10 minutes from the client’s request to the receipt of money when these applications are taken into account by AI. Since there is no paperwork and everything is done remotely, there are practically no delays anymore.
- Virtual assistants and chatbots: AI can speed up staff work and cut down on wait times when a customer calls a call center or a bank chat.
- Anti-fraud and financial monitoring: By examining unusual behavior in people and businesses, AI can fight financial fraud.
- ATM maintenance: AI predicts ATM occupancy and reduces cash collection costs.
- Document processing: For instance, financial institutions use AI to process and enter client data automatically when creating accounts and carrying out banking operations that need identification verification. AI recognizes details from scans and docs in two seconds and performs automatic data checks.
AI now plays a major role in the market of financial technology thanks to the development of industrial data processing, advancements in machine learning, decreases in the cost of delivering procedures, greater competition, and inflated customer expectations. Furthermore, it has a good track record for consistency in marketing strategy, risk, privacy, and human aspects.
AI-based technologies enable financial firms to stay ahead of the curve and deliver personalized service at a lower cost than ever before. In fact, AI can process much larger amounts of information qualitatively, self-learn, and accumulate knowledge at record speeds, enabling better human-computer interaction: computer algorithms that are constantly improving in the process of obtaining new data.
Risks of Using AI
The scientific and industrial professional communities are starting to voice concerns about the ethical implications of using AI, the safety of doing so, and the potential economic costs. For instance, what should be done to prevent job losses as a result of the automation of work with the aid of AI? How can the problem of bias be eliminated from algorithms? Artificial intelligence must be unbiased, just, and under the human direction.
The concerns include the potential for out-of-control computers to damage people and society, the misinterpretation and unpredictable nature of algorithmic behavior, and insufficient stability and dependability of decision-making systems. It might be challenging to understand why the AI selected a certain course of action, which may lead people to distrust artificial intelligence-based systems.
Prospects for AI Tech in Finances
FinTech enthusiasts see AI as the most effective technology in the long run. Approximately 70% of FinTechs are using AI today, and the tech is foreseen to dominate the market in just three years, according to the Tribe report. For the FinTech sector, the benefits of AI and machine learning include improved internal workflow efficiency as well as external customer communication.
Three of the most prevalent use cases for AI in the financial sector include customer verification, compliance, and trend forecasting. But no matter what, businesses need to concentrate on producing high-quality data for AI integration.
Automation has the potential to extend services, cut costs, and enhance the customer experience, and since businesses now have access to AI and machine learning, this potential is no longer considered to be science fiction. However, the development, design, engineering, and IT communities must collaborate closely with the FinTech sector. Only they will be able to efficiently execute a new financial product concept.