It has been seen that FinTech’s early days were marked by digitised payments and e-wallets. Even as emerging technologies gained more popularity, banks and other established financial institutions remained wary of largescale deployments. However, the sector couldn’t resist the lure of AI and data science for too long. The use of AI in financial services today has become so prevalent that it is being used by every organisation in the sector, such as banks, insuretch, credit card companies, trading platforms, cryptocurrency exchanges, stock exchanges and even the market regulator SEBI in India.
Let’s take an overarching view of the various applications of AI in the FinTech sector.
- Know Your Client (KYC): The Know Your Client or Know Your Customer is a standard procedure for customer identification and verification in the financial services industry. What was once a cumbersome process of conducting in-person verifications and signing numerous documents has now become a virtual-only seamless experience, facilitated by AI. Using facial recognition, it is possible to carry out biometric authentication using the Aadhar database. This has revolutionised the onboarding experience for customers and service providers alike.
- Information Extraction and Contract Automation: For the financial service industry, many processes such as underwriting, investment analysis, legal processes, KYC processes, and regulatory processes require key details to be extracted from unstructured documents and then analysed. Further, being a highly regulated industry, there’s a lot of paperwork pertaining to legal documents. Using Natural Language Processing, it is possible to automate both of these tedious processes which have traditionally required teams of analysts and lawyers. For instance, Capital Quant’s FinStinct is one such AI solution.
- Fraud Detection: For an industry as sensitive and highly regulated as financial services, it is imperative to be wary of nefarious actors who indulge in fraudulent activities. If left unnoticed, white collar crime can cause a major blow to the whole economic ecosystem. Various financial organisations use AI to red-flag objectionable or suspicious activities. For instance, Visa uses AI models to learn a credit card-holder’s spending patterns and assess fraud risk, enabling the issuing bank to approve or deny a dubious transaction.
- Personal Finance Management: For wealth managers and advisors, the value of AI has progressed from data parsing and processing to augmented advisory. Prescriptive and descriptive analytics make accurate, detailed predictions, automate portfolios and provide recommendations to balance out one’s portfolio. For instance, For over 10 years, Morgan Stanley has been working on its Next Best Action system to provide its financial advisers (FAs) with insights to present to clients. This system uses ML to identify investments of interest and relevance to particular client.
- Chatbots: Intelligent Virtual Assistants have completely transformed man-and-machine conversations. With the integration of conversational AI, they have become far enriched than basic Q&A with a chatbot, giving the impression of natural interaction as one would have with a human. Moreover, these assistants understand intent, preferences and are built to learn with every conversation. Most major financial institution has such chatbots deployed on their websites and social media channels to facilitate easy query resolution for their valued customers.
Source: indiaai.gov.in
