Question

"Fintech" is one of the most talked-about buzzwords in finance these days.

Fintech (short for Financial Technology) can be characterized as the movement to bring transformative and disruptive innovation to financial services through the application of new and emerging technologies.

A fintech revolution has been going on inside Wall Street’s biggest firms. At asset management giants from Blackrock to Third Point, banks such as Goldman Sachs and Citigroup, and financial service behemoths Nasdaq, MetLife and American Express, new technology applications in Machine Learning, Big Data, and Artificial Intelligence (AI) are revolutionizing the way they operate. In markets, algorithms that study language are helping trading houses and exchanges spot manipulation. Algorithmic traders use automated trading programs to determine when, where, and how to trade an order. Mega-banks are using AI to get a better, real-time understanding of their market and operational risks. Based on blockchain technology, cryptocurrencies have been created.

Recognizing that even the generalist investment managers need to be exposed to the changing world of technology-driven investing and portfolio management, CFA Institute added Fintech in their exam curriculum since 2019. Specific topics include big data, machine learning, artificial intelligence, cryptocurrencies, and robo-advising, etc.

How can Fintech (financial technology) and emerging technologies affect the role of a financial analyst? What do you think are the opportunities and challenges facing by the investment industry with the presence of Fintech?

Answer 1

The aggregate potential cost savings for banks from AI applications is estimated at $447 billion by 2023. The use of AI in Banking can be attributed to three-channel modes:

• Front-end, which makes use of features such as using chatbots and voice assistants for conversational banking, ensuring seamless customer identification, etc.
• Middle-office, which includes engaging in fraud-detection activities, enhancing systems for anti-money laundering, and KYC regulatory checks, among other things. For example, Ayasdi, which helps to combat money laundering with its anti-money laundering (AML) detection solutions.

• Back-end, which refers to smarter underwriting services and decisions. For instance, ZestFinance an AI-powered underwriting solution which assesses borrowers with little to no credit information or history: