4 papers · 1 filter
MINT: A Universal Zero-Shot Predictor for Transaction Data
Parameswaran Kamalaruban, Viktor Drobnyi, Maeve Madigan +3
Banks analyse sequential financial transaction data to perform many tasks, including fraud prevention, credit risk assessment and offer personalization. To improve the predictive a…
Emergent Bias and Fairness in Multi-Agent Decision Systems
Maeve Madigan, Parameswaran Kamalaruban, Glenn Moynihan +3
Multi-agent systems have demonstrated the ability to improve performance on a variety of predictive tasks by leveraging collaborative decision making. However, the lack of effectiv…
Fairness-Aware Low-Rank Representation Fine-Tuning
Parameswaran Kamalaruban, Mark Anderson, Stuart Burrell +3
Pre-trained foundation models can be efficiently adapted for specific tasks using Low-Rank Adaptation (LoRA), but the fairness properties of these adapted classifiers remain undere…
Evaluating Fairness in Transaction Fraud Models: Fairness Metrics, Bias Audits, and Challenges
Parameswaran Kamalaruban, Yulu Pi, Stuart Burrell +4
Ensuring fairness in transaction fraud detection models is vital due to the potential harms and legal implications of biased decision-making. Despite extensive research on algorith…