DeepAI AI Chat
Log In Sign Up

Navigating the Dynamics of Financial Embeddings over Time

by   Antonia Gogoglou, et al.

Financial transactions constitute connections between entities and through these connections a large scale heterogeneous weighted graph is formulated. In this labyrinth of interactions that are continuously updated, there exists a variety of similarity-based patterns that can provide insights into the dynamics of the financial system. With the current work, we propose the application of Graph Representation Learning in a scalable dynamic setting as a means of capturing these patterns in a meaningful and robust way. We proceed to perform a rigorous qualitative analysis of the latent trajectories to extract real world insights from the proposed representations and their evolution over time that is to our knowledge the first of its kind in the financial sector. Shifts in the latent space are associated with known economic events and in particular the impact of the recent Covid-19 pandemic to consumer patterns. Capturing such patterns indicates the value added to financial modeling through the incorporation of latent graph representations.


page 7

page 9

page 11


DeepTrax: Embedding Graphs of Financial Transactions

Financial transactions can be considered edges in a heterogeneous graph ...

Scalable, Trie-based Approximate Entity Extraction for Real-Time Financial Transaction Screening

Financial institutions have to screen their transactions to ensure that ...

LaundroGraph: Self-Supervised Graph Representation Learning for Anti-Money Laundering

Anti-money laundering (AML) regulations mandate financial institutions t...

Temporal Motifs for Financial Networks: A Study on Mercari, JPMC, and Venmo Platforms

Understanding the dynamics of financial transactions among people is cri...

Visual Analytics approach for finding spatiotemporal patterns from COVID19

Bounce Back Loan is amongst a number of UK business financial support sc...

Understanding Self-Predictive Learning for Reinforcement Learning

We study the learning dynamics of self-predictive learning for reinforce...

Allocating Stimulus Checks in Times of Crisis

We study the problem of allocating bailouts (stimulus, subsidy allocatio...