AI in FinTech: Opportunities and Challenges Defined
Artificial Intelligence is revolutionizing the fintech space. AI helps FinTech in many ways, including wealth management, fraud detection, customer support, and more.
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Join For FreeArtificial Intelligence (AI) has been widely used to analyze and manage data in the financial sector. AI plays a key role in making a lending decision, offering customer support, protecting against fraud, predicting credit risk assessment, and many more. Knowing the advantages of AI, many modern FinTech companies are keen on adapting to AI technologies to improve their efficiency.
The level of process automation and digital transformation activities is increasing in financial services. AI technology has seen rapid growth in the global financial industry. Based on industry data, experts have predicted that the global market size of AI in FinTech will reach USD 26.67 billion.
This article briefs you about the opportunities and challenges of AI technology in the FinTech Industry.
Types of Artificial Intelligence in the Financial Industry
When compared with humans, AI technology is far more efficient in identifying data patterns. This is why finance companies prefer applications powered by AI technology. There are two types of AI that are prevalent in the financial industry:
Weak AI:
Weak AI, also referred to as a Narrow AI system is specifically implemented to fulfill or complete a particular task or to solve a specific problem. AI technology is bound by a set of rules, and it delivers the best job without going beyond the rules. Apple's Siri is the best example of Weak AI.
Strong AI:
Strong AI is also referred to as a full AI system. As its name suggests, it is designed to do bigger prospects than weak AI. Applications powered with full AI come with huge capabilities and functionality. It also has understanding and consciousness; because of that, many broadly say the full AI system mimics the human brain.
Artificial Intelligence Applications in Financial Services
Algorithms based on Artificial Intelligence (AI) are being implemented in almost every financial service in the Financial Industry. Here is a list of a few key applications of AI in financial services listed for your reference; take a look.
1. Personal Finance
Modern consumers prefer to be financially independent and seek the ability to manage their financial health through adopting AI technology. This is where finance companies are forced to implement AI in personal finance. Companies prefer 24/7 customer support through AI-powered chatbots and offer personalized wealth management solutions to their consumers.
The US-based bank Capital One's Eno launched an SMS text-based assistant to its customers way back in 2017. The text-based assistance offers 12 proactive services, including altering suspected fraud or price hikes to customers.
2. Consumer Finance
Preventing fraud and cyberattacks is the most significant ability of AI technology when it comes to business cases. Consumers always look for banks that ensure high security for their accounts. As per data released by insider intelligence, it is expected around $48 billion in online fraud activities to happen in 2023. Knowing that banks prefer AI with the ability to analyze and single-out irregular patterns in finance services.
JPMorgan Chase has successfully adopted a key fraud-detecting AI application for all its account holders. The proprietary algorithm of AI detects fraud patterns every time a customer performs a credit card transaction.
3. Corporate Finance
AI technology is the first and foremost choice for corporations to predict and access loan risks. Apart from reducing financial risk, AI technology lessens financial crime by introducing advanced fraud detection actions.
To avoid anti-money laundering and identify bad customers, U. S Bank uses AI technology for its middle and back-end operations. The AI-powered application will unlock and analyze the customer's relevant data through deep learning.
Real-World Use Cases of AI in the Financial Industry
In the finance sector, several companies use numerous AI applications in practical ways to solve their problems and save time and money. Here are a few real cases where companies use AI applications for effective operations.
- Applications with AI technology like 'Virtual Financial Advisors and Chat Bots' will automate customer support services. Consumers are now engaging with chatbots to seek the answers they look for.
- An AI-powered application like 'Contract Analyser' detects fraud actions through anomalies. If a customer applies for multiple identical loans within a few minutes of gap means, the AI application will detect and mark it as suspicious.
- Data analysis is carried out by AI-powered applications like 'Churn Prediction. It takes most of the tedious jobs of analysts and allows them to focus on high issues. Meanwhile, it keeps working in the background to identify similar and smaller problems. Also, this application with AI technology helps companies to analyze a large amount of data efficiently in real time.
- AI technologies are widely used by finance sectors to identify the creditworthiness of someone. The app with AI tech will help to avoid overcharging and undercharging risky customers while lending loans by checking their credit scores in real time.
Analyze the Challenges and Solutions of the Fintech Industry in 2022
1. Data Breaches:
The first and foremost priority of a financial service firm is to protect its sensitive data from a cybercrime attack. When compared with other businesses, the financial industry receives 300 times more hits from cyber-attacks.
Solution: Implementing innovative solutions like AI technology-powered applications will ensure financial services stay ahead of cybercriminals.
2. Complying With Regulations:
Regulations and terms set by the governing authorities for financial services continue to increase. Financial service providers are forced to spend a lot to make sure their businesses run compliant with all those regulations. Also, they need to change their systems often to keep up with evolving regulations and standards.
Solution: Adapting to AI technologies will help financial service providers avoid a lot of costs in adhering to ever-changing regulations. AI tech provides the needed flexibility for companies to define their set of rules.
3. Consumer Expectation:
Modern consumers are expecting more from financial service providers like personalized finance services.
Solution: Introducing AI-powered chatbots will help companies to understand the needs of consumers and offer the exact services which they are looking for.
Benefits of Adoption of Artificial Intelligence in the Finance Industry
Apart from just enabling finance companies to do task automation, fraud detection, and providing personalized financial services to their valuable consumers, AI technology offers a wide range of benefits to the finance industry.
The perfect implementation of AI technology in the front and middle office of a finance sector will create a significant positive impact on its operations. Let’s take a look at a few key benefits a finance company can get through AI-powered applications.
- Eliminates the time wastage of doing repetitive tasks.
- Reduces human errors significantly through automation.
- Superior & frictionless, 24/7 customer interaction.
- Regulatory Compliance and Fraud Detection.
- Helps in Fraud prevention.
- Cost savings and more.
Also, AI technology offers unique solutions to the FinTech sector to address all modern problems. The ability to discern patterns and suspicious behaviors helps finance companies to offer sensitive financial services efficiently.
The Future of FinTech Is Artificial Intelligence
Over the last few years, the financial landscape has experienced substantial growth. To address modern problems and empower customers with smarter services, finance companies need to adapt to innovative tech powered by Artificial Intelligence. By offering a wide range of benefits, AI technology provides the potential for financial companies to undertake innovative financial transactions without altering the traditional banking intermediary.
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