Conference item
Distributed company control in company shareholding graphs
- Abstract:
- The Company Control Problem is of central importance to banks, financial intermediaries, financial intelligence units, regulatory and supervisory authorities such as the Central Banks. It consists in understanding who takes decisions in a large company network, that is, who controls the majority of votes for each single company. This has an impact on a large number of business areas, with examples including evaluation of creditworthiness, economic analysis of the control dispersion, anti-money laundering, prevention of potentially hostile takeovers, evaluation of risks, and shock propagation.This paper is based on our experience with the Central Bank of Italy and presents an approach to the solution of the company control problem in distributed settings, especially relevant, as large and distributed ownership graphs reflect European-size applications where scalability is paramount.In particular, we formalize the problem as query answering on a large distributed database. We study how independent subqueries can be executed in each partition and the partial results assembled at a master site to produce the answer. We study the formal properties of the problem, that is not easily parallelizable, and then present a method that supports parallelism at best.We present a thorough experimental evaluation of our approach with the Italian company graph of the Bank of Italy and the European Register of Financial Intermediaries and Affiliates as well as many artificial graphs to fully assess scalability.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 3.8MB, Terms of use)
-
- Publisher copy:
- 10.1109/ICDE51399.2021.00294
Authors
- Publisher:
- IEEE
- Host title:
- 2021 IEEE 37th International Conference on Data Engineering (ICDE)
- Pages:
- 2637-2648
- Publication date:
- 2021-06-22
- Acceptance date:
- 2021-02-09
- Event title:
- 37th IEEE International Conference on Data Engineering (ICDE)
- Event location:
- Chania, Crete, Greece (Virtual event)
- Event website:
- https://icde2021.gr/
- Event start date:
- 2021-04-19
- Event end date:
- 2021-03-21
- DOI:
- EISSN:
-
2375-026X
- ISSN:
-
1063-6382
- EISBN:
- 9781728191843
- ISBN:
- 9781728191850
- Language:
-
English
- Keywords:
- Pubs id:
-
1173365
- Local pid:
-
pubs:1173365
- Deposit date:
-
2021-04-25
- ARK identifier:
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2021
- Rights statement:
- © 2021 IEEE.
- Notes:
- This paper was presented at the 37th IEEE International Conference on Data Engineering (ICDE), 19-21 April, Chania, Crete, Greece (Virtual event). This is the accepted manuscript version of the paper. The final version is available online from IEEE at: https://doi.org/10.1109/ICDE51399.2021.00294
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