Fraudulent activities have been a major concern for the Indian banking system and its customers lately. Further, technological advancements have changed financial services in India and spawned a new industry known as fintech. The Fintech trend has grabbed the attention of both investors and fraudsters, who have devised inventive and innovative ways to defraud the system and make easy money. However, fraudsters constantly find unique ways to dodge security measures and target new channels. Hence, planning a robust fraud detection system that processes real-time data processing is critical in this age of digital uncertainty. Fintech companies can leverage Artificial Intelligence (AI) and Machine Learning (ML) to improve their ability to detect and prevent fraud.
Biometric authentication- Fintech companies can also use AI to improve their ability to onboard customers. One way to do this is through biometric authentication, such as voice recognition, facial recognition, fingerprint scanning, or retina scans. The AI can also use the physical characteristics of the individuals, such as their typing speed or how they swipe their phone, and unique body odours to create a unique behavioural profile that systems can use to authenticate the customer.
Machine Learning- Money laundering is one of the biggest threats in the financial world when we talk about financial crime. Money Laundering is considered one of the most famous ways to convert black money into white money. Various financial institutions follow some preventive methods of money laundering. In this technologically advanced era, it is difficult to avoid such activities with traditional methods. One way fintech companies can use AI to combat money laundering is through the use of machine learning algorithms. These algorithms can be trained to identify patterns and anomalies in financial transactions that may indicate fraudulent activity. For example, a machine learning algorithm could be trained to identify transactions significantly larger or smaller than the customer's typical transactions or transactions made at unusual times or from unusual locations. Hence, monitoring customer transactions using rule engines reduces the investigation time and gives accurate results.
Likewise, various Fintech companies can also use AI to monitor customer behaviour and transactions over time to identify patterns that may indicate fraudulent activity. For example, an AI-powered risk management system could analyse a customer's spending habits over time and flag any unusual spending patterns or large transactions that may indicate fraudulent activity. Such a system allows fintech companies to quickly investigate and potentially block the transaction before it is completed.
AI can also enhance fintech companies' security by identifying and responding to cyber threats in real-time. AI-powered systems can monitor network traffic and identify patterns that may indicate a cyber attack. Additionally, AI can be used to analyse data from various sources, such as social media, to identify potential threats and take appropriate action.
Natural Language Processing (NLP)- Another way fintech companies can use AI to protect customers from fraud is through Natural Language Processing (NLP). It gives machines the ability to read and understand human languages. NLP can be used to analyse customer behaviour and identify patterns that may point to the fraudulent activity. For example, an NLP algorithm could be trained to identify instances where a customer is pressured or coerced into providing sensitive information. Moreover, Financial institutions can also employ such analytical techniques to process the unstructured or textual reports accompanying the financial statement of borrowers, for example, the auditor's report, the statement of directors' responsibilities, generic shareholder information, etc. Analysis of quantitative and qualitative data through technology will enable financial institutions to increase work efficiency and avoid human errors.
In addition to using AI to detect and prevent fraud, fintech companies can also use it to improve the customer experience. For example, fintech companies can use AI-powered chatbots to provide 24/7 customer service and assist customers with their financial transactions. It helps increase customer satisfaction and trust in the fintech company.
In conclusion, AI can be used to authenticate customers, monitor customer behaviour and transactions over time, improve the customer experience and enhance the security of fintech companies by identifying and responding to cyber threats in real time. However, it's important to note that AI is not a silver bullet and should be used with other security measures to protect customers from fraud.
The faster AI is integrated into the system, the more chances are of minimising the severity of fraud-related damages. Manual verification of the operations is labour-intensive and time-consuming, though. With the digitalisation of various processes, the effectiveness of the manual approach has dropped, particularly in operation-intensive industries such as banking. The clients who have suffered from the repercussions of the fraudulent operations may migrate to other companies.
Hence, Fintech companies can leverage artificial intelligence and machine learning techniques, which has the potential to improve the efficiency and accuracy of financial service institutions. It is expected to see more innovations in AI-powered fraud detection methods to automate processes and make more accurate predictions.
