It’s no secret – financial services firms often face significant issues with their data when performing trade reconstructions. Compliance teams usually encounter two key challenges – sourcing the data and using the data.
Frequently, when reconstructing the conditions surrounding a trade or order, compliance teams will struggle to locate the data required to recreate the sequence of activities and communications requested by the regulator. Internal data can sit in silos and be difficult to track down. External data can be even more challenging. For example, obtaining the right social media material or data from chat or messaging platforms, can take significant time and effort.
The second challenge is larger – ensuring the data is high quality, accurate and valid. Financial services firms are finding data quality issues are significant and are experiencing a range of negative impacts. For example, the poor quality of trade reporting data is being highlighted by regulators on a frequent basis now. Firms are also encountering other difficulties, such as with the quality of the output of voice communication data solutions. So, what can be done to improve data governance for enhanced compliance? There are 5 main steps which we have highlighted in our latest e-book "5 Steps to Great Compliance Data Governance."
The need for high-quality data for trade reconstruction is clear – the ability to find and analyse potentially problematic trades rests on having good data to work with. However, compliance teams should not feel they are alone in this struggle – that they have to fix their data issues before they can engage with trade reconstruction technology.
Instead, financial firms should seek to find a solution that can help them overcome their data challenges and improve data quality. An ideal solution should be able to suggest best practices around internal processes, as well as support the cleansing of existing data sets. So, what can be done to improve data governance for enhanced trade reconstructions?
In summary, good data governance – including data quality and data lineage – is foundational for accurate trade reconstruction. However, it worth noting that today, a robust approach to data governance is now becoming essential for all compliance obligations.
As a result, firms need to think in a more strategic, data-centric way, as discussed in our complete guide to financial services compliance. Not only does such an approach to compliance provide firms with the confidence that they are operating within the rules, it also opens up possibilities for the data to be used in new ways that create value for the organisation.
SteelEye is a RegTech and data analytics firm that was established to reduce the complexity and cost of financial compliance and enable firms globally to manage their regulatory obligations through a single platform.
SteelEye’s ability to bring together, cleanse, index and analyse structured and unstructured data across all asset classes and communication types enables clients to effortlessly meet their regulatory needs, because when all this data is in one place, compliance becomes both easy and cost-effective. And with everything under one lens, firms also gain fresh insight into their business, helping them improve their efficiency and profitability.
To date, SteelEye has launched solutions for record keeping, trade reconstruction, transaction reporting, trade and communications surveillance, best execution reporting, transaction cost analysis and advanced analytics for regulations including MiFID II, EMIR, Dodd-Frank, SMCR and MAR. For more information, visit: www.steel-eye.com.
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