Data analytics in road transportation
You could use the tools from Network Science (1) to model (A,B) as edges in a network. Since you have timing information on the transactions you can reconstruct paths on that network.

Using statistical network analysis you can find for example which points A from your dataset (or nodes in the network) are of importance, as in how many routes lead to that point. For this you'd study a centrality measure (degree centrality, closeness centrality, betweenness centrality, etc.) (2)

Or you can find which points are close together in terms of transactions between them, for this you'd look for community detection or clustering. (2)

You can also look at the timing data, to calculate the intra- and inter- transaction time distributions.

(1): Barabási, A. L. (2016). Network science. Cambridge university press.

(2): Salter‐Townshend, M., White, A., Gollini, I., &amp; Murphy, T. B. (2012). Review of statistical network analysis: models, algorithms, and software. Statistical Analysis and Data Mining: The ASA Data Science Journal, 5(4), 243-264.