Category: Financial Services

The UK motor finance industry faces Complex challenges following the Financial Conduct Authority’s (FCA) review of Discretionary Commission Arrangements (DCA). Financial institutions must now analyze historical lending data, calculate accurate redress amounts, and manage customer communications effectively, all while working with fragmented data sets and tight regulatory deadlines. In this post, we’ll explore how AWS […]

Scott Mullins, Managing Director, AWS for Financial Services Over 750 financial services leaders convened for the AWS Financial Services Symposium in New York City last month to share, build relationships, and explore how their peers are leveraging cloud technology to tackle their most pressing business challenges. Under the theme “Pushing the Envelope,” the Symposium featured […]

Overview The payments industry has seen significant growth and transformation in recent years, driven by the rapid adoption of digital and mobile payment technologies. According to McKinsey, “Payments revenues grew at 11 percent in 2022—a double-digit rate for the second consecutive year—reaching more than $2.2 trillion, an all-time high”. This growth brings challenges in ensuring payment […]

Introduction Factor modeling in hedge funds is a quantitative approach that identifies and analyzes key drivers of asset returns. It lets fund managers to optimize portfolios, manage risk, and generate alpha by leveraging vast amounts of market data. This technique facilitates the development of sophisticated trading strategies, enhancing investment performance and providing a competitive edge […]

This AWS FSI Blog post outlines how Zurich Insurance in the UK, or ‘Zurich’ in the remainder of this post, is leveraging artificial intelligence and machine learning (AI/ML) with Amazon SageMaker AI to anticipate flood claims, thereby proactively protecting customers against potentially catastrophic events. Zurich Insurance Group (Zurich) is a leading insurer providing property, casualty, […]

Backtesting plays a critical role in algorithmic trading. Firms leverage XGBoost for backtesting to build predictive models that forecast market movements based on historical data. Training XGBoost models is computationally expensive though, and can quickly become a bottleneck, especially when working with large historical datasets. This blog post shows how quantitative trading firms distribute XGBoost […]

Introduction Mastercard’s AI-powered real-time fraud prevention platform, Brighterion, has been delivering advanced fraud detection and risk management solutions to enterprise customers for over 20 years. Trusted by more than 2,000 clients worldwide, including 74 of the top 100 U.S. banks, Mastercard’s Brighterion AI platform scores over 150 billion transactions annually, helping organizations prevent fraud while […]

The banks who are delivering value from generative AI (gen AI) and machine learning (ML) investments are building AI stacks that are scalable and well governed. These stacks accelerate proofs-of-concept/proofs-of-value into production reliably so that business needs are met. Introduction There is a lot going on in banks related to both gen AI and more […]

Introduction In today’s fast-paced world of financial technology, sub-milliseconds can make the difference between success and failure in financial transactions. The demands of high-frequency trading, real-time market data processing, and complex financial transactions require an infrastructure that will deliver unparalleled performance, reliability, and fairness. AWS is addressing these needs through a new category of Amazon […]

The rapid advancement of generative AI promises new strategies for innovation in the insurance industry, and insurance carriers should implement it in compliance with regulatory requirements. The National Association of Insurance Commissioners (NAIC) has adopted Principles on Artificial Intelligence and released a Model Bulletin on the use of artificial intelligence systems by insurers to provide […]