The financial industry is victim to an estimated £14b worth of economic crime a year. With significant sums at stake for both consumers and financial institutions, Mark will explore the role ML can play in driving down fraud, without compromising UX. He will focus on ML’s ability to analyse vast amounts of data to accurately flag suspicious transactions and new fraud attacks in real-time that analysts alone may miss.
Mark will address pitfalls to avoid and give tips on fine-tuning ML models and boosting system efficiencies. He’ll highlight the business benefits of ML: analysts can focus on genuine threats; reduced false positives and costs of anti-fraud operations; and regulatory compliance.
As well as discussing the technical capabilities of ML, Mark will place the technology into the real-world context of fighting financial fraud, demonstrating why it should be an essential component within any anti-fraud operation.
Basic knowledge of finance and fraud is helpful.