Artificial intelligence (AI) refers to technology based on algorithms and is designed to simulate human intelligence.  Under this general term, we have subcategories such as machine learning, natural language processing (NLP), and deep learning.

Artificial intelligence has gained prominence in finance as the sector is driven by innovation and a focus on automation. From trading technologies to algorithms and the use of AI in smarter fraud prevention, risk management, customer support, and tighter compliance, the financial industry is highly reliant on AI. AI is essential in

streamlining internal business processes and improving the overall customer experience. This trend is expected to accelerate to meet customer demands for faster, more efficient and secure financial processes.
What is AI and Machine Learning?

  • AI

AI is the general term which refers to the creation of machines simulating human cognitive capabilities such as learning and problem solving, with machine learning being the most widely used application of AI. With machine learning, computers learn and improve based on experience.

  • Machine Learning

Machine learning involves the training of computer algorithms to recognise data and perform certain tasks based on that set of information. Because it involves developing an algorithm that focuses on completing a task based on one set of data, it can be used to improve  solutions for a singular task over time.

Machine learning was worth an estimated value of $1.41 billion in 2020 and is expected to reach $8.81 billion by 2025.

Applications of AI

The majority of AI today is considered to simulate aspects of human behaviour and intelligence. However, more specialised tech companies are working on developing robotic systems that can be more advanced, exhibiting autonomous processes such as acting or thinking on their own.

  • Natural language processing: NLP analyses text, voice, and other communication data to communicate with users.
  • Computer vision: Law enforcement is using computer vision to help identify people, analyse images and detect potential dangers in a specific environment.
  • Accessibility tools: This has to do with helping people in their daily routines by using autonomous vehicles, medical diagnostic tools and virtual assistants at home.

AI in Finance

The financial sector is interested in AI as a way to streamline processes and improve trading systems through automation. For example, the human element and the possibility of error is minimised with the use of AI-powered robo-advisers which can provide automated, algorithm-based financial planning services.

Examples of AI In Finance

  1. Automating Back-End Operations

Big financial firms can scale their operations through the automation of transaction processing and back-end operations.

  1. Improving Trading Activity

Quantitative trading relies on AI to detect investment opportunities while algorithmic trading provides analysis and opens/closes positions on behalf of the  trader.

  1. Banking

AI is used in banking services such as  customised offers and alerts via a bank’s website and mobile app, customer service call routing and problem resolution.

  1. Credit Decisions

AI allows banks to use behavioural attributes, such as phone information, bills/payment records, and social media information to create machine learning (ML) models for credit risk and worthiness.

  1. Security

AI is used for detecting suspicious spending patterns by credit customers, and can inform wider investigations relating to data breaches.