The use of Artificial Intelligence (AI) is changing the landscape of the financial services industry. As per a report released by Report Linker in March 2021, the global AI in the FinTech market is predicted to grow at a compound annual growth rate of 23.17% from 2020-26 to reach USD 26.67 billion by 2026.
As stated in the same report, Artificial Intelligence is further on its way to becoming mainstream in financial services in a short period of time. As per a survey conducted by Cambridge Centre for Alternative Finance (CCAF) in 2020, 85% of all respondents in the study used Artificial Intelligence in some form, with FinTech companies being slightly ahead in the adoption of the technology.
Owing to the various benefits of Artificial Intelligence for FinTech businesses in the form of efficient processes, automation of manual tasks, and so on, the demand for AI solutions by FinTech software development companies is increasing.
If you too are contemplating on adopting AI for your financial services business, read on to know the various applications of the technology in the FinTech industry that can lead your business on the path of unprecedented success.
AI in Finance – Business Applications & Benefits
The FinTech industry is using AI in areas such as risk management, algorithmic trading and fraud detection to unlock revenue growth opportunities, automate manual processes, minimize operating costs, and so on.
As per Statista, among the various use cases of AI in financial services, fraud detection is the most important use case followed by finance processes analysis and cybersecurity.
Read on to know more about the major applications and benefits of Artificial Intelligence in the FinTech industry.
Fraud Detection & Prevention
In the past, companies used to fight fraud with sets of hardcoded rules designed by domain experts. However, the potential danger lies in the fact that fraudsters could discover the rules and exploit the system.
Artificial Intelligence helps detect and reduce frauds by analyzing a customer’s buying behavior and triggering an alert if something does not seem normal or contradicts traditional spending patterns of the customer.
Risk Assessment & Management
The FinTech industry uses AI for risk assessment of an individual or a company. For instance, Artificial Intelligence and Machine Learning (ML) algorithms determine a person’s loan eligibility and also offer personalized options, thereby making the whole process quicker and more accurate.
AI in finance is also used for risk management. The technology allows vast amounts of structured and unstructured data to be managed in a short time, a task that would take far too much time for a human to do. The AI algorithms also analyze the history of risk cases and identify early signs of potential future issues.
Automation of Manual Processes
AI automates repetitive and mundane tasks such as reviewing documents or pulling information from applications, thus allowing financial professionals to focus on other higher-value tasks including cultivating deeper relationships with customers.
For instance, when a customer submits a credit card application, it must be entered into the system, reviewed and verified by professionals. It must be safe to say no one particularly enjoys spending their day carrying out these kinds of repetitive tasks. This is where AI comes in by reducing the time required to approve an application while increasing accuracy by avoiding human error.
Many financial institutions and banks are in the business of lending money. For the same, they need to assess the creditworthiness of a potential customer or another company.
Earlier, such decisions were made by analysts after collecting relevant data points. However, using more complex methods in comparison to the scoring systems of the past, the AI-enabled solutions allow for a faster and more accurate assessment of a potential borrower.
The cyberattack surface in modern enterprise environments is massive and it is continuing to grow rapidly. This means that improving an organization’s cybersecurity posture needs more than mere human intervention.
AI technology draws data from the past as well as present and tracks down a variety of cyber threats from malware menaces to phishing attacks. Using various algorithms, AI systems are also trained to run pattern recognition and detect even the minutest ransomware attacks.
Artificial Intelligence technology has reduced the time spent on the phone by customers waiting to speak with a customer service representative. Thanks to the AI-enabled chatbots and virtual assistants, customers can now check their account balance, schedule payments and receive personalized banking advice by a virtual assistant in merely no time.
Organizations in the FinTech industry are using AI applications such as smart wallets to monitor the user’s behavior and detect patterns, based on which recommendations are made for micro-investing, savings, and more. Such AI tools are making FinTech more accessible to users.
AI in Finance – Future Outlook
The “AI revolution” is impacting the FinTech sector in a big way and will continue to do so in the future. As stated by Forbes, 54% of financial services organizations with over 5,000 employees have already adopted the technology in their business processes. Moreover, over 70% of all finance organizations are using ML to predict cash flow events, fine-tune credit scores and detect fraud.
Therefore, adopting Artificial Intelligence technology is the need of the hour for all financial services businesses. It is no longer only an option but a survival strategy for your business.
You can consider implementing AI in your business using in-house resources. However, the process can actually be cumbersome right from choosing the necessary Artificial Intelligence tools to setting up the right data inputs.
To take your business to another level using AI-enabled solutions, it can help to partner with an experienced and reputed FinTech software development company that can not only develop solutions but bring to the table an AI strategy that best suits your financial business needs.
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