Mindset Payments

Mapping the payment graph

I have posted before that payments could be the foundation of implicit social graphs. Implicit graphs are social graphs based on an underlying common activity but moving in terms of members and relationships. I have been thinking some more about it (also ran that idea across people) and believe the payment graph can be described with the following attributes:

– Actors: Businesses or People – Nodes (with E: Employers, I: Individual and R/S: Retailers/Service providers)

– Payments – Connections

– Meta data around payment (for example, product type, location, etc..) – Data around connections

There are different way to see the payment graph, depending the connections. Some examples:

Business to Person to Business

E: Employer – I: Individuals – R/S: Retailer, Service Provider

Business to Business

P: Provider – C/P: Customer, Provider – Customer

Peer to Peer
Very similar to the B2B graph.


What could be the value of the payment graph?
There is tremendous value, I believe  in “owning” the payment graph or part of it. To take the example of the B2B network:
– Value of the aggregate data of invoice / account receivable information: average payment time in a specific industry, costs structure, number of clients etc..
– By extension, possibility to have more accurate representation of the risk of a company, creation of new credit scores based on default / payment time information.
– Possibility to facilitate financing flows, for example by easing the connection to exchanges such as the Receivables Exchange.
– On top of financial information, communication with clients and providers could be eased and place in a specific context.


Who will control the payment graph?
Several companies have started taking “ownership” of the payment graph whether knowingly or not:
– Invoicing platforms such as or Tradeshift, which recently raised 7 millions at a high valuation are in an ideal position to create and develop the payment graph.
Intuit, with its sheer size in the small business world and the width of its services is another company that has a shot at it.
– Banks have a lot of data of the payment graph that they could leverage. Whereas they can establish themselves as a trust partner or have sufficient chunk of the payment graph to make its value possible remains to be seen.
– Messaging platforms such as SWIFT could also play an important role, as they control some of the main “pipes” of the payment graph.
– Outsiders, such as accounting companies as Xero may also have the size and centralization necessary.


However, it remains to be validated that a single company, in the current model, can control the payment graph. But I think it may open new vertical, where a message network acquiring an invoicing platform makes business sense. The fact that Swift and Bottomline are collaborating more closely may be an example of this.
The Business to Individuals payment graph may offer different values to its owners: Companies such as have show there is a strong potential in the big data of credit card payments, from the popularity of businesses to maybe statistical value on which products may interest a customer based on its existing payment pattern.

3 replies on “Mapping the payment graph”

Great post, and I totally agree there’s immense potential in B2B purchase-to-payments (P2P), from driving far greater value in supply chain financing (e.g. there are $1 trillion of receivables in the US alone).

The challenge, certainly here in the UK, is that – exactly because the various P2P participants have historically evolved as separate silos – existing data flows are disconnected: for example, default data from UK cheque guarantee providers (our equivalent to Certegy) would be immensely valuable to a commercial credit bureau, but the formers’ databases use bank account numbers as the unique company identifier & the latter use company registration number, so the two data sources cannot easily be unified.There is probably a valuable business model – for the right participant – in mapping between these disparate legacy data sources, because – however enticing their business models – it’s difficult to see any one P2P participant (e.g. Xero, Tradeshift or even Bottomline) creating sufficient near-term network-effect momentum to unify purchase-to-payments alone.

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