1. Cold Hard E-Cash: Friends and Vendors in the Venmo Digital Payments System
Xinyi Zhang, Shiliang Tang, Yun Zhao, Gang Wang*, Haitao Zheng and Ben Y. Zhao
UC Santa Barbara
*Virginia Tech

2. Person-to-person payments become viral
Venmo
Mobile payments between friends
11M users by May 2016
From $1B to $2B monthly volume in 2016
Verbified: “Just Venmo me!”
Big companies also launching person-to-person (p2p) payments
Snapchat
Facebook
Banks
Apple

3. Interplay with social network
Just Venmo me!
Social
Jane paid John
Financial
Jane paid Mike
Jane paid Elizabeth

4. Questions The global interaction patterns
Q1: what is social behavior like in financial context?
Q2: what is financial behavior like in social context?
Understanding individual users
Q3: what kind of people are using p2p payments?
Q4: what binds these users to the system?
Financial
Social
Financial
Social

5. Data collection Payment records Social network
Crawled the “public” stream
April May 2016
7.1M users, 91M public transactions (49.3% of all transactions)
Data fields: payer, payee, time, message
Social network
Queried friend lists for all users
May 2016
9.8M users, 544M social connections

6. Q1: social behavior in financial context
Financial interactions are more selective and stay in close groups.

7. Payment targets are more selective
Venmo social network
Closely resembles traditional social networks
Sparse payment activity
81% users make payment with less than 10% of their friends
Median: 40
# of Friends

8. Payments stay within groups
Interaction graph: Venmo payments vs. Facebook & Twitter
Users are nodes, edges represent user interaction
Financial
Interactions
Traditional interactions
vs.
CC = 1
CC = 0

9. Q2: payments in different social context
Payment behavior is heavily influenced by close friends.

10. Payments happen in different social context
Payment graph between friends vs. between strangers
Use Venmo’s social graph as a filter
Social
Payments
vs.
Non-social Payments
Transactions between Friends
Payment Graph
Social Graph
Transactions between Strangers

11. Strong social influence on payments
Payment graph between friends vs. between strangers
Assortativity: nodes to attach to others that are similar
Low Assortativity
High Assortativity

12. Q3: different user types in Venmo
We can identify vendors through their behavior.

13. Roommates and vendors in Venmo
Hierarchical clustering using behavioral metrics
Label clusters based on behavior and messages
Splitting utilities, groceries
Niche users
Roommates only
Paying cashback, collecting airbnb rent
Diverse users
Vendors

14. Q4: what binds users to Venmo?
Friends bind users in groups; businesses bind in star-shapes.
Social bonds are better at keeping users.

15. Social bonds keep users active
815 highly separable communities
Bind through friends or businesses
Different clustering coefficient
High CC: friend; low CC: business
Friends increase activeness
Friendship-driven communities has more active users
Friendship-driven
Business-driven
Median Active Ratio
0.69
0.43

16. A case study of a gambling community
Social Ego-network
Bookie Ego-network
A case study of a gambling community
Bookie: a person who takes bets on sporting and other events
“$20 for NCAA, $150 for Super Bowl”

17. Conclusions
Financial interactions tend to be more selective, within close groups
Financial interactions ⊆ social interactions ⊆ friending
Payment behavior is heavily influenced by friends
Normal users and businesses show highly distinct behavior
Businesses are easily identifiable
Normal users create social bonds that improve stickiness

18. Thank You! Questions? sentence structure shorter
don't connect independent sentences
remove unnecessary things
the tempo, stress
slower, more natural