A corporate action is an event initiated by a public company that will bring an actual change to the securities i.e. equity or debt issued by the company. Corporate actions are typically agreed upon by a company’s board of directors and authorized by the shareholders.
Corporate actions data can be used to improve decision-making, as well as ensure the best possible outcome for clients, the front office no longer want slow manual processes holding them back, and instead are looking to get data continuously throughout the day. Examples of corporate actions:
|Dividend||Dividend with choice of cash or stock|
|Stock splits||Tender offers|
|Reverse stock splits||Rights issues|
|Mergers and acquisitions||Buyback offers|
|Return of capital||Mergers with elections|
Despite the fact that the economy and the companies in it have continued to evolve, the traditional methods for sector classification have remained relatively unchanged for decades.
Traditional classifications tend to group companies with historically similar characteristics into a single sector, often overlooking some of the likely drivers of those companies in the future.
Xoriant CDi’s sector approach seeks to provide a more fully detailed sector classification framework through the use of data science techniques, including machine learning and text analysis.
Our technology-driven approach can capture a more forward-looking view of companies and redraw the boundaries of the modern economy.
Risk associated with counterparty corporate actions:
Operational risk: Inefficienciesgaps in the corporate actions chain, including misinterpretation and processing failures, late payments, and untimely information to the front office triggering poor trading decisions, can lead to operational risk and subsequent losses borne by intermediaries in the chain.
Reputational risk: Failure to properly track even a single corporate action can result in significant reputational damage and exposure to financial risks. The need to interpret, transform and summaries corporate actions information can lead to inaccurate communication of an issuer message. Pricing errors and the associated reputational and financial loss are a significant concern for fund administrators.
Liquidity risk: Effective liquidity risk management entails understanding the interplay between complex financial factors such as the relationships between issuers of financial instruments, the instruments themselves, the counterparties and clients involved.
With years of experience Xoriant CDi has developed an innovative delivery platform CDi OnDemand to fulfill any reference data projects need. It has easily automated the process of delivering data projects related to corporate action announcement and implementation, supporting regulations of US & Europe based on AML guidelines.
Tracks corporate action associated with the entity and implements same to maintain accuracy in customer relationship and ownership.
CDi OnDemand offers a clear view of beneficial ownership; ultimate or complete structure. Also showcases scenarios with broken tree & circular relationships
CDi OnDemand has a unique feature that allows effective cross-referencing of beneficial ownership information by certain identifiers.
Self-service model for gold copy database creation and management
Unlimited queries of Xoriant CDi entity database
Customized operational workflows
Rapid data aggregation
Elastic manpower – 24×5 access to CDi data stewards
Proactively managing data quality errors, such as duplicity in counterparty hierarchy, invalid values, etc.