The Transformational Potential of Artificial Intelligence within Financial Services

Artificial Intelligence (AI) refers to the capability of a computer system to replicate human cognitive functions and simulate the reasoning that humans use to learn and solve problems by employing maths and logic. Machine Learning (ML), a subset or application of AI if you will, involves using mathematical models of data to facilitate computer learning without direct or explicit instructions. This empowers a computer system to continuously learn and enhance its capabilities, developing ‘intelligence’ through experience. ML is therefore the underlying mechanism by which computer systems are empowered to ‘think’ independently and execute tasks, simulating the human cognitive function (Azure, n/a).

By harnessing this transformational potential, financial institutions can enhance their operational processes, augment their decision-making processes, and deliver truly personalised products and services to their customers. The use cases for AI in financial services span across various organisational functions including front-office operations such as conversational AI, customer service and personalisation, middle-office operations such as Know Your Customer (KYC), fraud detection, compliance, and cyber-security, and back-office operations such as loan and credit decisioning, portfolio optimisation, hyper-automation and Robo Advisors, automated claims processes, risk modelling and pricing.

Contents

1. Introduction
2. AI in Banking
3. AI in Wealth Management
4. AI in Insurance
5. Challenges and Considerations
6. Best Practices
7. The Social Impact of AI in Financial Services