Financial technology (FinTech) is the new era of finance that has completely revolutionized the payments network. It uses digital tools and technologies to process financial data, speed up operations, and automate tedious checkups using sophisticated solutions. FinTech is not only banking; it allows customers and business owners with a wide range of options from creating and tracking budgets to buying and selling of assets. You can even apply for mortgages on the go with FinTech innovations. Now, after the introduction of AI in FinTech space, the industry is leveling up further with a much faster rate of transformation and automation. This blog post will cover the pivotal role of AI in modern finance, highlighting the top ways both businesses and customers can leverage the potential of AI in financial development.
Digital Finance – A Quick Look
The process of automation in the finance sector has been around since the late 20th century when the first ATM (Automated Teller Machine) was deposited in 1967. However, the growth from the 1970s to modern-day platforms such as PayPal, Google Pay, and Payoneer have changed the industry dramatically. AI has had a pivotal role to play in this transformation from the early days of its development until now, when generative AI is taking over every sector. The APIs of modern-day FinTech platforms enable businesses to incorporate intelligent AI-powered payment networks right into their website. This enables firms to use a combination of services from web-based applications to BNPL (Buy Now, Pay Later) solutions. This is why most startups you see nowadays are FinTech-based. All of this is due to the scope of this industry and the incorporation of AI.
AI in FinTech – A Deep Dive
Artificial Intelligence improves the FinTech platforms significantly by analyzing and predicting financial data, which can be used in a number of ways:
Regulation and Compliance: AI analysis can help businesses (especially startups) in navigating the global compliance and regulations landscape.
Decision-Making: AI feeds on financial data and provides valuable insights which are crucial for business decision-making in the long-run.
Security & Fraud Prevention: AI solutions can completely transform security and fraud detection protocols with intelligent identity verification solutions, enabling firms to verify their customers, investors, stakeholders, and the people who try to bypass the business network security (fraudsters).
Trading and Market Analysis: Trading platforms are also part of the FinTech landscape. AI solutions with intelligent machine learning algorithms are becoming popular for their auto-trading module that learns the market trends for forex, crypto, and other digital assets.
Top 5 Use Cases of AI in Fintech Sector
Artificial intelligence has a wide range of applications in the FinTech industry. From banking to investments, AI offers intelligent solutions that help the user make informed decisions. The global landscape is changing with AI adoption. For instance, in Mexico, AI adoption for local businesses (especially for FinTech) was 28% in early 2020. However, the rise of these solutions became prominent, with the numbers climbing significantly to 68% in terms of AI in FinTech adoption. This shows the importance of AI in the business sector, leading us to its top 5 use cases globally.
Automation
At first glance, AI improves digital finance automation with the intelligent processing of data. It enhances transaction processing, payment refunds, online gateway channel clearance, validation, and verification across each step of the financial cycle. This bolsters customer satisfaction, increasing their loyalty and trust towards the FinTech platform. Moreover, the businesses that do not incorporate AI automation and stick to traditional manual methods fall behind in the race of market leadership FinTech solutions.
Risk Assessment
Sometimes, the existing customers of a company can become bad actors or fraudsters. This can impact business operations and financial stability. To cater to this problem, the AI risk assessment solution contributes substantially by analyzing customer transactions and financial patterns. Upon any irregularity or unusual behavior or transaction, the system flags it automatically. For instance, it tracks the customers that have loans or any sort of liabilities and notifies the FinTech experts to make more informed decisions. This significantly mitigates risk factors. Moreover, there are several AI algorithms that are designed specially for risk assessment, replacing traditional models for credit score calculations.
Fraud Detection & Prevention
Fraud is becoming prominent in the era of AI and Deepfakes. However, countering these modern tactics, AI battles AI. The FinTech space incorporates deepfake detection tools that are powered by AI. These tools are excellent for identifying AI fraud patterns. In the end, AI can recognize AI much more efficiently than humans- or isn’t it? Well, humans can further train these AI models with a specialized approach to spot fraud. Identity verification with biometrics is key in the process of KYC (Know Your Business) and transaction risk assessment. Both these operations are part of AML (Anti-Money Laundering) compliance for the FinTech firms. AI in FinTech solutions can monitor multiple accounts and their transactions at a time, making them efficient security solutions for the financial space. This is why it is a key component of modern Cyber Security protocols.
Decision-Making Assistance
We have been discussing the power of AI that enables businesses to make good decisions. But how do AI assistants process decision-making workflows in the backend? This is possible with NLP (Natural Language Processing) and machine learning. NLP enables the system to understand the user intent through the chatbot interface and their interaction cycles. The conversational AI comes in handy in fetching user perspective by communication and chat cycles. This tailors a more personalized decision-making ability specific for every customer. Other than getting customer data, these conversational AI bots can also promote or present new features of the FinTech platform, making the customer buy or use the service more effectively. This increases the ROIs for companies significantly.
Portfolio Management
AI provides robo-assistants to businesses that can help analyze data and information. These assistants work as complete resources, just like human assistants, but with better performance and rates of operation. One of the key advantages of these robo-assistants is Portfolio Management for businesses. AI takes one step ahead of traditional portfolio managers with 24/7 analysis, enabling firms to get personalized financial advice. Customers can also develop their financial portfolios in visual formats with artificial intelligence. AI robots extract the situations in which a financial decision is taken, its time, place, and purpose. Then, it calculates the risk tolerance that aligns with investment strategies and specific financial objectives for both businesses and customers.
Wrapping It Up
In a nutshell, Artificial intelligence is shaping every aspect of the FinTech sector, from transaction processing to record-keeping. Businesses operating in the FinTech space can take advantage of the processing power of AI. Intelligent data processing, insights generation, and business ledger tracking operations are becoming simpler than ever with artificial intelligence. However, there are still governance and regulatory concerns for AI in FinTech that need to be addressed. So, it is necessary to do comprehensive research before giving away your financial data to any AI model for learning and processing business information. For third-party AI service providers, it is crucial to trust their policy and ensure transparency of operations.
