In January this year, the Federal Reserve Bank (FRB) published a working paper which assessed impact on the financial system from a hypothetical cyber attack
Author: amits99
Review of the 2019 World Economic Forum report on ‘Responsible Innovation with AI in Financial Services’
A summary of the 2019 World Economic Forum report on key obstacles preventing AI from being fully adopted and transforming the financial sector.
ML Implementation – lessons from Booking.com
Business lessons learnt by the data scientists at Booking.com after deploying 150 Machine Learning (ML) models. These observations are insightful and offer a practitioner view regarding implementation of ML models for business purpose and some are even non-intuitive.
Regulatory Expectations for use of AI in financial sector
Another month and another publication on Artificial Intelligence (AI) by regulators is out. This time it is by the De Nederlandsche Bank (DNB). The principles
Machine Learning (ML) & Anti-Money Laundering (AML) – made for each other
Money laundering is a massive drain on the world’s financial, legal and economic institutions and current rule based AML controls with a false positive rate of 90% are just not adequate to detect and monitor them. AML is ripe for disruption and innovation through use of Artificial Intelligence (AI) and Machine Learning (ML) and even the regulators are encouraging the same. Key areas of AML where AI and ML have been shown to work through recent published papers are risk scoring; customer segmentation and transaction monitoring using clustering (k-means); classification (support vector machines) and deep learning (graph convolutional networks). These approaches shows us a glimpse of the near future state of AML controls and how new technology can help solve the seemingly insurmountable problem of money laundering as it exists now.
Machine Learning Explainability – QII, Shapley Values and Data Shapley
Introduction: One of the key challenges of using machine learning (ML) is the lack of explainability which progressively decreases as the model complexity increases starting
