Regulatory compliance in data reconciliation
Data reconciliation is the linchpin of accurate and consistent data throughout the operations of financial firms. Making sure that data sets match up across systems, departments and entities is central for maintaining integrity and making sound business decisions.
However, reconciliation processes are about more than just operational efficiency. They also play a pivotal role in satisfying regulatory mandates from bodies like ESMA, FINRA, the SEC, and others. Non-compliance can lead to substantial penalties and restrictions, and no one wants that.
In this guide, we examine the increasing regulatory scrutiny around data reconciliation practices, looking at areas of focus that meet requirements while streamlining operations.
The importance of regulatory compliance
At its core, regulatory compliance refers to adhering to the relevant laws, regulations and guidelines that govern a particular industry or sector. For capital markets firms, this encompasses everything from anti-money laundering rules and accounting standards to data privacy mandates and reporting obligations.
Maintaining compliance is paramount in the highly-regulated financial services world. The industry plays an important role in the functioning of the global economy, with deadlines and commitments that simply can't be missed. Firms operate under an incredible amount of scrutiny from regulators like FINRA, SEC, FCA, ESMA and others.
The consequences of non-compliance can be devastating. Fines for violations can run into the tens or even hundreds of millions. Perhaps even more damaging is the reputational hit that often accompanies regulatory reprimands, which can impact a firm's ability to attract and retain clients.
In worst-case scenarios, particularly egregious infractions can lead to temporary or permanent business restrictions, or even criminal charges against individuals. Playing fast and loose with regulatory obligations is simply not an option. The risks in terms of monetary penalties, reputation damage and potential legal action are existential threats to the entire business.
Therefore, strong compliance policies and rigorous adherence to regulatory mandates must be baked into a firm's DNA at this point. There's just too much on the line.
Key regulations affecting data reconciliation
Financial firms need to navigate a complex web of regulations that touch on various aspects of their data reconciliation processes. While requirements differ across jurisdictions, some of the major areas of regulation in this space include:
Trade and transaction reporting
Regulations like Dodd Frank, CFTC, JFSA, EMIR Refit, ASIC, MAS, HKMA, Sec 10c-1, SFTR, FINRA TRACE, FINRA MSRB, MiFIR/MiFID II, MiCA, and upcoming Canadian rules. These mandate reporting of trades and transactions to regulators in specific timeframes like T+1 or near real-time.
Reporting and messaging standards
Standards and formats adopted by the industry like those set by CPMI IOSCO with Critical Data Elements (CDE), and ISO 20022.
Financial market regulators and supervisors
The major financial watchdogs like FINRA, SEC, FCA, and ESMA that oversee compliance with regulations.
The specific rules vary across these areas, but there are some common themes around data reconciliation requirements. Firms must be able to demonstrate their ability to successfully reconcile transactions, positions, trade details, accounting figures and other data sets across systems, entities, departments and geographic regions.
Many regulations also mandate actions based on reconciliation findings within set time periods. For example, MiFID II requires firms to investigate and resolve trade breaks within strict deadlines based on asset class and settlement cycle.
This increased regulatory scrutiny around data reconciliation is forcing firms to rethink their data management and reporting practices from the ground up. Using automated, auditable processes for reconciliation is a must for maintaining compliance.
The regulators aren't messing around – they expect us to have an enterprise-wide view into data with full transparency and traceability. The stakes are just too high now to rely on error-prone manual processes.
Challenges in achieving regulatory compliance
Achieving and maintaining regulatory compliance around data reconciliation is no easy feat for capital markets firms. A multitude of technological, organisational and resource issues can hamper efforts. Let's examine some of the major obstacles:
Complex and overlapping requirements
Navigating the sheer number of applicable regulations is a huge challenge in itself. As discussed, mandates like those covering trade reporting, standards, and regulator oversight all have different specific rules around data reconciliation. Making sense of how requirements may overlap or even potentially conflict across these various regimes is an incredibly complex undertaking.
Data quality and consistency challenges
Many firms struggle with data quality and consistency issues that can completely undermine reconciliation processes. When data definitions, formats and standards are not synchronised across systems, entities and departments, it creates perpetual breaks that are difficult to resolve.
Reliance on manual processes
Even at large, well-resourced firms, data reconciliation responsibilities are often highly manually intensive. Trade entries may need to be compared line-by-line in spreadsheets. Discrepancies frequently require back-and-forth communications and investigative work. This lack of automation and embedded controls opens the door for human error that can lead to compliance failures.
Keeping pace with changes
Regulatory requirements and deadlines are constantly evolving, creating a continual struggle to keep processes and controls updated. Whether it's tweaks to existing rules or entirely new regulations like the upcoming T+1 settlement cycle changes, firms must be able to adapt reconciliation practices rapidly to maintain compliance. Failing to move quickly enough can quickly lead to costly lapses.
Best practices for regulatory compliance in data reconciliation
While achieving full regulatory compliance for data reconciliation processes is undoubtedly challenging, there are some established best practices that can help keep firms on the right side of mandates. These include:
Establish a strong compliance culture
Regulatory compliance must be a firm-wide commitment that permeates from the top-down. Executive leadership needs to ingrain a culture of compliance that is reflected in governance frameworks, well-defined policies and procedures, extensive training initiatives and clear accountability. You can have all the technology and processes in the world, but they're worthless without the right mindset.
Implement reconciliation processes that work
Firms must design and implement comprehensive reconciliation processes covering all critical data domains - trades, positions, risk data, accounting figures, customers, entities and more. These should use automation and embedded controls as much as possible for better accuracy and consistency. Leading practices include runbook documentation, segregation of duties, defined risk tolerance thresholds and remediations workflows.
Ensure data quality and lineage
Regulatory compliance lives and dies by the quality of underlying data fed into reconciliation processes. Firms must establish data governance programs, definitions and standards to promote complete, accurate and timely data across all sources and consumers. Effective metadata, data lineage and audit trails are also fundamental for demonstrating full transparency to regulators.
Continuously improve policies and procedures
Compliance policies, processes and procedures cannot be static. As new regulations and requirements emerge, firms must be able to quickly assess impacts and update their data reconciliation practices accordingly. Regular reviews and testing should be conducted to identify gaps. Having flexible, adaptable reconciliation frameworks is table stakes.
Use compliance technology solutions
The volume, complexity and importance of regulatory compliance today necessitates using purposeful technology to automate and streamline efforts. Solutions with intelligent reconciliation engines, embedded automation, exception management workflows, auditing capabilities and analytics can help firms achieve accuracy while optimising resources.
The role of technology in regulatory compliance
Technology plays an indispensable role in enabling capital markets firms to cost-effectively achieve and maintain regulatory compliance around data reconciliation in today's environment. By automating reconciliation processes and embedding continuous controls, purpose-built software solutions can drive vastly improved accuracy, consistency and transparency compared to manual methods.
Leading compliance and reconciliation platforms offer intelligent matching engines, customizable reconciliation rules, exception management workflows, audit trails and analytics to adapt to evolving regulations. Solutions that seamlessly integrate across the technology ecosystem provide unified data governance, universal data ingestion, and enterprise-wide reconciliation masking.
With Gresham Technologies' industry-leading cash, data, and regulatory solutions, firms can streamline compliance efforts through comprehensive automation while benefiting from unrivalled reconciliation thoroughness and speed. Our cloud-native, API-first architecture enables continuous adherence to mandates while optimising reconciliation quality and productivity.
Innovation in Regulatory Compliance Reporting
Recent collaboration with market participants and trade associations like ISDA, ISLA and ICMA are producing innovative solutions to post trade regulatory reporting. Allowing efficient submission of transactions to trade repositories such as DTCC, Regis-TR, KDPW, Unavista and others. With further adoption of the Common Domain Model (CDM) and Digital Regulatory Reporting (DRR) expected to reduce cost and complexity whilst increasing data quality.
By adopting the CDM effectively, we can achieve standardised and consistent trade and transaction reporting, enhance data quality and interoperability, and streamline compliance processes. It enables improved transparency, efficiency, and collaboration ensuring compliance with evolving regulatory requirements.
By leveraging DRR effectively, we can streamline trade and transaction reporting processes, ensure regulatory compliance, reduce operational risks, and gain valuable insights from reported data. DRR allows us to implement machine readable rules for data harmonised into the CDM model.
Auditing and reporting for regulatory compliance
Rigorous auditing, reporting and documentation practices are at the heart of demonstrating regulatory compliance in data reconciliation to examiners and stakeholders. Firms should implement regular internal audits and assessments to continuously evaluate the effectiveness of their reconciliation processes, controls and technologies. This allows any gaps or deficiencies to be promptly identified and remediated before inspections occur.
When regulatory examinations do take place, having well-organised artefacts like runbook documentation, end-to-end data lineage tracking and complete audit trails from reconciliation systems is essential for supporting findings and responding to inquiries. Equally important is the ability to generate accurate, high-fidelity compliance reports and certifications covering all regulated data domains on-demand.
Advanced reconciliation platforms facilitate this level of preparedness by providing transparent, auditable oversight across all reconciliation activities with in-depth reporting capabilities. As one chief compliance officer stated, "If you can't show our work in a clear, comprehensive way to regulators, you've already failed the exam."
Summing up: The importance of regulatory compliance data
Achieving and maintaining regulatory compliance for data reconciliation requires a holistic, technology-enabled approach. Staying on top of aspects like establishing a culture of compliance, implementing reconciliation processes and adhering to data quality means firms can avoid costly penalties while optimising operational efficiency. With the right strategy and solutions, compliance becomes an enabler rather than an obstacle.
