Steve Barnes, CTO
In our previous blog, we took time to pause, reflect and consider some lessons learned from the compliance processes for MiFID II transaction reporting. In this blog, we take a step further and look at five ways innovation can create a resilient MiFID II transaction reporting framework.
In his speech of 3rd July 2018, Mark Steward, Director of Enforcement and Market Oversight at the Financial Conduct Authority, stated1 that the FCA now processes over half a billion transaction reports per month, coming from 23 submitting entities, representing 3,150 firms. The FCA has invested heavily in its technical capacity to ingest, process and analyse the information reported. In its transaction reporting forum from July 2018, the FCA provided further analysis on the quality of those transaction reports, highlighting the major sources of rejection rates. Duplication, content validation and instrument validation errors feature highly in the top ten.
From this analysis, it is clear that a resilient framework is required to achieve robust reporting. Effective use of technological innovation can help achieve this by enabling firms to harness data to proactively monitor, identify, and correct situations that can lead to poor outcomes.
Here are five key areas where innovation can make a difference.
- Data is imperfect. In order to achieve the accuracy requirements, firms need a realistic, flexible process for managing data. This can be achieved by combining APIs or automated data feeds from trade repositories with user self-service, in-application data management and maintenance functions. A well-designed self-service intelligent reporting platform will usually have data preparation tools that store, manage, and provide access to source data, prepared data, and data models, with appropriate governance measures. This helps reduce the headache of managing all data ‘at source’.
- Don’t be an outlier with high rejection rates. Industry rejection rates have been cited at 5% of total reports submitted. Not only is it undesirable to be identified by the regulator has having poor accuracy, dealing with high volumes of rejections can also be operationally burdensome. Early validation is key to achieve accuracy. Validate the data at each point; on loading, on processing and on generation of XML to be submitted to the regulator. Inaccurate data should not pass through these three gates. At AQMetrics, we see a rejection rate at less than 0.5%. This is achievable for all firms and submitting entities.
- Leverage external data sources to your advantage. Industry available external data sources are maturing. The GLEIF2 infrastructure has achieved excellent levels of stability since launch date. DSB ANNA3 and FIRDS4 have continued to mature over the course of the year. The commitments from ANNA and GLEIF to link ISINs to LEIs in an effort to assist with accurate reporting, will further strengthen the quality of external data sources that can be leveraged to the firm’s advantage. An intelligent reporting platform will integrate these sources, and will leverage appropriately in the validation process.
- Timing is key. Validating the data early in the process, rather than downstream at reporting time, can eliminate bottlenecks at the t+1 deadline. The rise of the Intelligent User Interface (IUI), stemming from breakthroughs in machine learning, allows intelligent user prompting. Timely alerting of critical path issues via secure mobile applications can help prevent end-of-day delays.
- Achieve continuous reconciliation. In accordance with regulatory technical standards, the firm’s reconciliation responsibilities include checking the timeliness of the report, the accuracy, and the completeness of the individual data fields. Reconciliation should be on-demand, continuous and part of ‘business as usual’ daily processing. Firms can achieve this with configurable data analytics dashboards, where multi-dimensional data insights can drive improved reconciliation processes.
Finally, resilience is achieved through a combination of these innovation strategies. With this kind of approach, the reporting framework becomes stronger and can be augmented further to provide data insights beyond the original purpose of the reports. Intelligent user interfaces, machine learning and data analytics are now becoming widespread. The careful application of these technologies will lead the industry into an era of rapid learning and improvement, and ultimately a stronger foundation for compliance.