By Steve Barnes, CTO
At AQMetrics we make our business applications user friendly for both power users and non-power users alike. To this end, we have recently looked into ways to make loading fund and related data accessible to all of our clients regardless of their technical knowledge.
Creating file based extracts for data loading into any system is a task which typically requires an I.T. function or a data warehouse team to build extracts from the source system e.g. a fund accounting platform, and deliver that data securely to a system which will load it and process it in a secure and performant manner.
At AQMetrics we know that we need to offer flexibility to both large asset service providers and hedge funds alike across our applications. Further, customer facing teams, compliance and other business functions are realising that data warehouse issues are their issues when it comes to regulatory risk. Ensuring data quality has typically been a responsibility of back office teams only, but this is no longer acceptable.
In consideration of this, we have a three-way data management which embraces automation making the process easier on teams of all sizes and expertise.
- Flexible APIs allow for machine to machine data loading automation with real time error handling and reporting.
- User initiated batch uploads places the power in the hands of the business user, to create their own files in .csv or Excel and upload through their personal dashboards.
- The AQMetrics Data Maintenance hub allows for niche data to be maintained in the application that requires it.
The above capabilities allow all users to upload their holdings, security master, counterparty and many more risk and regulatory data feeds into the system and easily maintain it once it is there. For user initiated data feeds, the platform applies the same rigour for validation and error handling as it does for the automated API driven processes. When a user uploads a file via the AQMetrics dashboard, the dashboard widget reads the Excel file and ensures it is correctly formatted before handing it to a powerful ETL tool behind the scenes which loads the data. This will suit firms with a short supply of IT skills in house. The AQMetrics data management dashboard provides feedback on data loading with additional applications for users to check data performance. As a result, firms are more in control of their data accuracy and quality.
Once the data is loaded into the AQMetrics platform, there are many ways it can be used. As we discussed in our recent webinar, the data required for regulatory reporting is a valuable asset and should be repurposed to do more for a fund manager. Innovative strategies including Machine Learning and Artificial Intelligence (AI/ML) can be used on repurposed regulatory reporting data.
- Business Rules, such as the well known prospectus based limitations on how a fund invests or regulator driven UCITS or ‘40 Act rules can be executed on the data to ensure investment compliance is adhered to on a quarterly, monthly or daily basis. Specific fund based rules can also be created using the AQMetrics rules engine such as limits to counterparty or geographic exposure. My next blog will be about the AQMetrics rules engine and what it can do for you.
- Intuitive Dashboards, which update in real time, gives a manager a top down view of their portfolios under management or a bottom up view of each fund one by one. Using this view combination managers can see their data sliced and diced in a way which is rarely accessible. This transparency becomes useful when a manager has their funds managed across multiple administrators.
- Outlier Analysis AI/ML technologies find outliers in data, helping the fund manager identify red flags and look deep into the underlying data.
Flexible data management provides for deeper insights and better operational outcomes for all users through a combination of the strategies above. With this kind of approach, the risk and regulatory reporting system becomes available to all to augment and provide data insights beyond the original intended purpose. Intelligent user interfaces, machine learning and data analytics are now becoming widespread. The opening of these applications and technologies to all will lead the industry into an era of rapid learning and improvement, and ultimately a solid foundation for compliance.