Artificial Intelligence (AI)

AI algorithms can analyse transaction patterns in real time to identify and prevent fraudulent activities, reducing financial losses and protecting customers. Machine learning models, especially anomaly detection systems, are used to identify patterns and outliers that may suggest fraudulent behaviour.

AI streamlines back-office operations, such as account opening or claims processing, by automating routine tasks and paperwork. Robotic Process Automation (RPA) is widely used for automating repetitive tasks, not only in finance but also in sectors like manufacturing, healthcare, and retail.

Machine learning models offer more sophisticated and accurate credit scoring by analysing traditional and non-traditional data sources, leading to better lending decisions. Supervised learning techniques are applied to analyse credit history, transaction data, and even alternative data to predict creditworthiness and other risk levels. AI is increasingly being used to assess risk more accurately across portfolios, identifying potential issues and suggesting mitigation strategies quickly.

Chatbots and virtual assistants powered by AI can handle customer inquiries and transactions, providing 24/7 service without human intervention. Powered by NLP for text interaction and voice generation AI for automated voice services can handle a range of customer service tasks.

AI systems improve the detection of suspicious activities and help in the efficient analysis of data to prevent money laundering. Machine learning and NLP are used to analyse transaction data and customer communication for patterns that might indicate money laundering activities.

NLP and image recognition technologies are used to digitise, categorise, and analyse documents for faster processing and decision-making. Extensively used in areas such as customer onboarding, processing large volumes of legal documents, invoice processing, medical records translation, and many other areas that are heavily reliant on paper documentation.

AI helps in monitoring and ensuring compliance with regulatory requirements by automatically updating systems in response to regulatory changes and detecting non-compliant behaviour.

AI enables the delivery of personalised financial advice and product recommendations to customers based on their behaviour and preferences.

Increasingly investment firms are using sentiment analysis to gauge the public's perception of various stocks, market conditions, or the overall economy. By analysing vast amounts of data from news articles, social media posts, financial forums, and blogs, the firm's AI system can determine whether the sentiment around a particular company or sector is positive, negative, or neutral.