A primary cause of the 2008 global financial crisis was the conversion of mortgage debt into credit derivatives and collateralized debt obligations.
These credit derivatives and collateralized debt obligations trade in over-the-counter (OTC) markets which are neither transparent nor monitored to identify large or vulnerable positions. The crisis put the global over-the-counter-derivates (OTCD) markets in the spotlight due to lack of transparency. Consequently, OTCD markets came under the radar of policymakers after the crisis. The post crisis scrutiny revealed that insufficient data compromised the assessment of risks arising from the accumulation of unsustainable exposures, which in turn resulted in the failure of some leading financial institutions. It also hindered regulators and central banks in effectively fulfilling their responsibilities during the crisis.
Consequently, there was a deluge of regulations (see Figure 1) aimed at reforming the OTCD market, preventing market abuse, and mitigating systemic risks. These regulations were introduced to address five critical areas of the OTC value chain and streamline the OTC derivatives market.
Though these regulations have been in place for quite a few years now, financial institutions have not been able to achieve complete compliance. They are at different stages of implementing the reforms related with reporting to repositories. Inaccurate and incomplete reporting due to data issues is still a major challenge, often resulting in deficient risk management and sub-optimal decision-making by regulators. All of this can also affect systemic financial stability.
In response, regulators have had to introduce steep penalties, lowering the tolerance for inaccurate trade reporting. Reporting failures have resulted in heavy fines for financial institutions, as is evident from the data on regulatory actions released by FINRA (see Table 1).1 Firms have also had to bear remediation costs and contend with the reputational fallout.
Establishing a robust reconciliation framework to ensure that the data reported to the repositories are accurate and complete is an urgent imperative. The process should include checks to ensure that all the trades in scope are reported, and transactions out of scope are not reported. To this end, financial institutions must adopt a customized approach encompassing technology tools and streamlined reconciliation systems and processes to ensure effective control.
Reconciliation is not just a process but an end-to-end control framework.
An end-to-end automated reconciliation model allows firms to have complete control over the transactions, mitigate risk, reduce costs, improve the time to market for offerings, and ensure optimal utilization of the workforce. In our view, financial institutions must implement a robust reconciliation framework with features such as auto-matching, both prior and post reporting to trade repositories, and exception management. An end-to-end scalable solution that covers reconciliation platform, support, and infrastructure, as well as operations will help address all reconciliation challenges.
As transaction volume continues to increase, manual reconciliation will become an uphill task. Automating regulatory reconciliation is another step toward improving control and enhancing compliance. The reconciliation framework should incorporate standardized or customized rules to maximize straight-through processing (STP) and minimize the exceptions that require manual matching. The manual touchpoints should be reviewed periodically to explore opportunities for enhancing automation.
The reconciliation process must be automated to enable three-way matching of data between financial institutions’ internal source data, data fed into the regulatory reporting solution, and the data consumed by the regulator from the trade repositories (see Figure 2).
The solution must include:
Low straight-through processing rates pose difficulties to regulators in accurately monitoring exceptions. To increase the processing rate, reconciliation must occur at a more granular level and at different stages—prior to reporting to trade repositories and within trade repositories post reporting.
Trade reconciliation systems match data across several fields to ensure accuracy and completeness. For example, in reporting repo trades to comply with the Securities Financing Transactions Regulation (SFTR), more than 100 attributes are matched, and the absence of an efficient exception management system can give rise to many exceptions. Financial institutions must establish a robust exception management process to resolve differences quickly. Some common difficulties in resolving exceptions include incorrect account data, unique transaction identifier (UTI) mismatch, timing issues, duplicate bookings, booking of non-reportable trades, and so on.
Successful implementation will demand a clearly defined execution road map with appropriate deadlines.
Also, establishing robust communication channels can ensure a seamless rollout, replacing manual or semi-automated reconciliation processes with new, upgraded ones. However, operationalizing changes will require considerable effort to configure match logic with exception workflows and alerts. Timely and hassle-free compliance will depend on collaborating with the right partner, and banks must make this decision post an elaborate, well-rounded market analysis and evaluation.
The TCS Capital Markets Reconciliation and Reporting Service (see Figure 3) can be customized to individual financial institutions’ requirements. In conjunction with our domain expertise and knowledge, the solution helps banks meet key performance indicators (KPIs) in reconciliation. TCS can help build, the trade repository reconciliation framework by leveraging its in-house platform or market platforms.
The centralized reporting of derivatives transactions to trade repositories was expected to provide information that could be leveraged by public authorities to define policy.
Derivatives data offer a host of insights, which can inform policy definition at the micro, market, and macro levels, in turn improving risk assessment at the systemic level. In this context, the reconciliation process gains significance in the entire value chain to ensure accurate data is reported to the trade repositories.
Over the past few years, banks have primarily focused on improving data quality by establishing central data warehouses and embracing standardization to overcome challenges in reconciliation. However, data capture issues persist in the absence of strategic automation initiatives. Banks must explore building in-house automated solutions and leverage third-party tools to develop more robust reconciliation processes. Banks and financial institutions that fast-track their reconciliation transformation journey stand to gain an edge and steal a march over their peers.
1©2024 FINRA. All rights reserved. FINRA is a registered trademark of the Financial Industry Regulatory Authority, Inc. Reprinted with permission from FINRA.
2ESMA, EMIR and SFTR data quality report 2021; April 2022; Accessed September 2024