The valuation imperative – Part III
IPV market solutions: how can Asset Control help?
At Asset Control, we know the best practices in market data management. We group these requirements into system requirements, data inputs, workflow requirements, business rules, reporting and monitoring requirements.
Managing market data sources
- A solution must be able to handle multiple sources for different data types and cross-compare these to gain a comprehensive market view and improve data quality. New sources must be easily onboarded
- A solution must be able to cross-reference information, consolidate sources of price information and apply validation and cleaning routines to create market derived prices. Comparing and contrasting market data sources is needed both to spot inconsistencies but also to check/monitor the quality of a market data source.
- A solution must be able to handle complex structures such as curves and surfaces so that fair value triggers can be based on them
Historical market data and handling large data volumes
- A solution must be able to store historical data so that the operational user can perform operational efficiency, data quality, vendor performance, and back testing analysis without the need to store historical data separately in Excel
- A solution must be able to store historical adjustment factors so that operational users can include these in their analysis
- A solution must be able to retrieve historical price data from vendors so that the operational users can backfill historical data for new securities in the system
- Ability to create, manage and maintain price curves and surfaces and apply rules and models.
- Ability to easily see the dependencies of curves and surfaces, to accurately diagnose why certain price differences occurred – remediation and improvements
- Integrate external pricing and valuation libraries with minimal IT development effort to use libraries for XVA adjustments and Prudent Valuation
- Monitoring and exception processing
- A solution must be able to alert the user when a feed is delayed so that the user can take preventive action
- A solution must be able to alert users to missing and late data
- The solution should summarize KPIs in a dashboard so that users can promptly act
- The system must trigger audit/validation rules to re-apply when making changes so that risks of manual input mistakes is reduced
Data distribution and discovery
- A solution should provide easy access to data scientists van quants for modelling and backtesting via integration with typical languages such as Python and R.
- A solution must be able to distribute data by file transfer, APIs or streaming
- A solution must be able to distribute a given set of data immediately, while another set will wait for approval so that different processes can use different mechanisms
- A solution must fit into existing information architectures and supply different downstream applications
Security and permissioning
- A solution must be able to recognize different users with different permissions so that only specific users can perform specific tasks, and thereby reducing operational risks
- A solution must be able to assign ownership of data elements (meta data and values) so that only the right users can make modifications and thereby enabling a larger group of user access for analysis purposes
- A solution must be able to enforce a 4-eyes/review principle so that the same user cannot perform cleansing and approval tasks
Audit and lineage
- Full audit trail to record changes and decisions on changes in business rules and data source hierarchy
- Lineage to explain to internal audit and regulators what sources have been used
- Keep track of what market data you use and what is redundant.
In summary, Asset Control helps improve legacy internally build IPV solutions by tackling the following:
|Legacy infrastructure||Asset Control|
|High cost of maintenance and inability to scale||Scalable solution with flexible deployment options|
|Often time consuming and difficult to get to data, especially in new use cases||Business user enablement to self-service data needs lowers cost of change|
|Infrastructure dependent on numerous spreadsheets and internally build software||Single product that can comprehensively cover all IPV requirements
Full data linage and audit of all changes
|Manual processes and high workload||Data sourcing and screening business rules and workflow that lowers manual intervention|
|Inconsistent use of standard data sources||Large set of fully maintained interfaces with external data sources and easy incorporation of internal sources
Cross-reference between multiple sources for easy comparison
|Difficulty to oversee entire data process leads to operational risks and data quality issues||Ops360 insight into data supply chain including quality stats and SLAs
Fully maintained and documented product solution