Finance and Technology coalesce to form a whole new technology-enabled innovation, ‘FinTech’. The development of the FinTech industry depends on technologies underlying financial products and services. Artificial intelligence has the potential to play a transformative role in financial services. Companies in the Fintech industry leverage artificial intelligence to analyse and manage data from various resources for concrete insight. The minimalist use begins with using AI Chatbot to attend to the potential customers and keep the promise of 24x7 customer support. Artificial intelligence has moved from the fringes to the centre of the debate, owing to improved cognition and social simulation. Continue reading to learn about the benefits of Artificial Intelligence in Fintech.
Benefits of Artificial Intelligence as a Financial Technology
Artificial intelligence (AI) has had a significant impact on the fintech industry, by automating routine tasks, improving efficiency, and reducing costs. AI-powered Finance technologies like machine learning, natural language processing, and computer vision have been applied in several areas of fintech, such as:
- Automated Customer Support
- Stronger Security
- Credit Scoring
- Fraud Detection
Customer Services and relationship management is another critical yet crucial area that needs to be catered to with utmost care. Artificial Intelligence provides tangible value in this aspect and makes sure to add to the customer experience. Apart from the AI chatbots, Automated Customer support in Fintech can also predict users’ behaviour. Using a common interface to integrate various artificial intelligence and machine learning techniques, Merchants and users can gain detailed insights into their data. It not only contributed to efficient assistance but also reduces operational costs by using NLPs to understand customer inquiries and render appropriate responses which includes identifying potential issues, such as a customer's account becoming overdrawn, and alerting the customer before it becomes a problem.
AI in fintech is used to enhance security measures and to detect & prevent fraud. Machine learning algorithms can be trained to identify patterns and anomalies in financial transactions that are indicative of fraudulent activity. Analysing transaction data, identifying unusual behaviour, and monitoring suspicious activity in real time can prevent fraudulent activities to a great extent. AI-based systems can also be used for identity verification, by using facial recognition technology to match a user's face to a government-issued ID, or by using voice recognition technology to match a user's voice to a recorded sample. Another use case of Artificial Intelligence in Fintech security is, the ability to detect and prevent phishing attempts, by analysing email content, sender reputation and other factors to identify fraudulent emails. Overall, AI can play a crucial role in fintech security by providing financial institutions with more accurate and efficient means of detecting and preventing fraud and ensuring the security of customer information.
Credit scoring can be improved by analysing large amounts of data to identify patterns and make more accurate predictions about a borrower's creditworthiness. This can include using machine learning algorithms to analyse financial transactions, social media data, and other relevant information. AI-based credit scoring can help financial institutions make more informed decisions, reduce risk, and increase the efficiency of the loan application process.
AI-based fraud detection in FinTech Industry, allows financial institutions to automatically identify and prevent fraudulent activities in real-time. By using unsupervised learning algorithms, such as anomaly detection, which can detect unusual patterns that are not part of normal behaviour, it also can detect frauds that were not seen before and are not linked to predefined fraud patterns. The fraud detection systems driven by Artificial Intelligence can also be integrated with other security measures, such as biometric authentication, to provide a multi-layered approach to fraud prevention.
Pitfalls of Artificial Intelligence in Financial Technology
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No Ethical Justification: AI algorithms can be complex and difficult to understand, making it challenging to explain the decision-making processes. This lack of interpretation leads to mistrust in the technology making it difficult for regulators to evaluate the risks. Also, a flawed algorithm can lead to faulty analysis.
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Biased Outcomes: AI models can perpetuate and even amplify biases in the data they are trained on, leading to discriminatory outcomes, particularly in areas such as lending and credit scoring.
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Lack of Human Oversight: AI systems can make decisions and execute trades without human intervention, which can lead to errors or unintended consequences. Even though clients are the direct beneficiaries of the automated system, they still prefer to connect with humans, as a minor glitch in the system can spell disaster for a client.
The Fintech Landscape has grown substantially over the year with artificial intelligence at its centre, which furthers exceptional scalability to countless companies. Artificial intelligence provides financial industry with the unique opportunity to reduce costs, improve customer experience and increase operational efficiency, among other things. While the AI-driven approach cuts down on workload, streamlines protocols and offers innovative approaches, it is accompanied by its share of challenges. Artificial intelligence (AI) has the potential to greatly impact payment gateways by improving security, streamlining the checkout process, and reducing fraud