

Hi All,
I have a bunch of financial transactional data and I was wondering if there is any ML model that can give me a graph structure for this data? other words, show how a transaction had evolved over time?
Any suggestions or references would help.
Thanks!


What do you mean by “how it evolved over time” ? A transaction describes basically an action at a certain point of time. Do you mean how a financial product evolved over time given a set of a transactions?
> On 28. Apr 2018, at 12:46, kant kodali < [hidden email]> wrote:
>
> Hi All,
>
> I have a bunch of financial transactional data and I was wondering if there is any ML model that can give me a graph structure for this data? other words, show how a transaction had evolved over time?
>
> Any suggestions or references would help.
>
> Thanks!
>

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Hi,
I mean a transaction goes typically goes through different states like STARTED, PENDING, CANCELLED, COMPLETED, SETTLED etc...
Thanks, kant


One potential approach could be to construct a transition matrix showing the probability of moving from each state to another state. This can be visualized with a “heat map” encoding (I think matshow in numpy/matplotlib does this). Hi,
I mean a transaction goes typically goes through different states like STARTED, PENDING, CANCELLED, COMPLETED, SETTLED etc...
Thanks, kant


Hi Nick,
Thanks for that idea!! Just to be more clear. The problem I am trying to solve is that when a bunch of financial transactional data is thrown at me I am trying to identify all possible relationships and lineage among them without explicitly specifying what the relationships are among transactions.


Maybe not necessarily what you want but you could, based on trans attributes, find out initial state and end state and give it to a decision tree to figure out if you if based on these attributes you can oreditc tinal stage Again, not what you asked but an idea to use ml for your data? Kr One potential approach could be to construct a transition matrix showing the probability of moving from each state to another state. This can be visualized with a “heat map” encoding (I think matshow in numpy/matplotlib does this). Hi,
I mean a transaction goes typically goes through different states like STARTED, PENDING, CANCELLED, COMPLETED, SETTLED etc...
Thanks, kant


The transactions probably describe from which counterparty assets are transferred to another counterparty at the different stages of the transaction. You could use graphx for that if the algorithms there are suitable for your needs. Still trying to understand what you mean evolve over time? Eg a counterparty has cancelled a lot of transactions or sth like this? Normally it looks like you have a rather straight forward state machine for your transactions. Hi Nick,
Thanks for that idea!! Just to be more clear. The problem I am trying to solve is that when a bunch of financial transactional data is thrown at me I am trying to identify all possible relationships and lineage among them without explicitly specifying what the relationships are among transactions.

