The financial services industry in the EU has been confused with the introduction of a revamped version of the Markets in Financial Instruments Directive (Mifid II). The ambitious regulatory reforms that took almost seven years to be materialized were intended for the greater protection of investors and more transparency into asset classes such as equities, fixed income, exchange-traded funds and foreign exchange. Having rolled out on 3 January 2018, the lengthy legislation with more than 1.4 million paragraphs of rules had brought in controversies with regard to its far-reaching prospects and practicability. After its implementation, a lot many institutions were finding the new legislation tougher as they were underprepared for the changes.
Data reconciliation with its regulatory reporting requirements is one of the processes that Mifid II rendered financial institutions clueless. The crux of the problem lies in EU’s attempt to push the most of trading on to electronic platforms to have better audit and surveillance capabilities. Now, financial institutions need to deal with data sizes ranging to petabytes, and timely reporting more information about most trades with data stretching to more than 65 fields. Financial institutions that are depending on spreadsheets and rules-based applications for reconciliations and data control have a crucial situation at present, as their tools are not effective and sustainable given the depth and breadth of required data for Mifid II. They need to look out for automated reconciliation process in order to ensure proper regulatory compliance.
Mifid II and its Implications in Reconciliation Space
In general, Mifid was updated to add more transparency in data dealings and to include new products in reporting obligations. The reforms also bring in accounting for the buy-side and sell-side counterparties for dual reporting and real-time reconciliation. Mifid II puts forth a number of reporting and data requirements. One of the important requirements is the need for investment firms to fulfil statutory reconciliation under RTS 22 and RTS 6 for trade data from competent authorities (NCAs) versus trading records. The regulation also mandates reconciling reference data like Legal Entity Identifiers (LEIs), International Securities Identification Numbers (ISINs), and personally identifiable information (PII) available within the investment firm. In addition, it requires Approved Reporting Mechanisms (ARMs), Approved Publication Arrangement (APAs) and NCAs to timely reconcile the data that is reported to firms and the data they publish back to their clients. The core idea behind the update is cutting short touch points for data transfer across the entire value chain and applying set standards between market participants so that the time spent on manual processing and data administration can be reduced.
However, having a compliant data reporting and reconciliation system is a challenging task for financial institutions due to a number of reasons. They include a higher number of reportable instruments and trading venues, inefficiency of existing reconciliation systems as well as a larger amount of information required. Mitigating data risk is one of the crucial challenges under Mifid II. One important problem that firms face is the quality of data. Data quality inconsistencies and reliability issues with data would create detrimental effects as firms look to integrate existing data into various data management systems to ensure compliance with Mifid II. “Quality of data will be of utmost importance to the investment firms as it will not only be required to meet the firm’s regulatory obligations but also take strategic decisions. Retention and easy availability of data might require some firms to evaluate their record-keeping arrangements,” PwC says in a report titled Understanding the business landscape post MiFID II.
There are also high chances of errors and mismatches as data pass through a number of external firms from the source firm before it reaches the regulator. During the journey, the original data from the source firm may become subject to multiple transformation and enrichment processes. The additional reference information such as LEIs, ISINs and ESMA eligibility checking required by Mifid II would make legacy systems and processes prone to more errors. With existing systems, what financial institutions can expect in this scenario are higher costs due to a lot of manual work and potential fines due to lapses in compliance.
Automation is Crucial and the Key to Sustainability
In light of the new requirements, the traditional methods of spreadsheets and rules-based applications for reconciliations and data control are not sustainable as they are impractical, expensive and risky to maintain in today’s complex environment. Financial institutions should take the help of automated reconciliation solutions that can source, clean, transform and then reconcile data without user intervention or security concerns in order to stay relevant in the business and adhere to the new regulatory requirements. RegTech firms, especially those modern technologies such as AI and machine learning, can play a vital role in this scenario. As PwC says these firms “not only bring in much-needed expertise to implement these regulations but also help keep a strong control on compliance costs.”
AI/machine learning-based solutions came into play to address the drawbacks of rules-based solutions. They can streamline and automate reconciliation processes across any line of business, dramatically enhance internal controls while enforcing standardization to improve the quality and accuracy of financial data. In addition, these solutions can help increase transparency in financial reporting as they can generate dynamic configurable reports in connection with data remediation and reconciliation. Given the novelty in the approach and the multitude of operational benefits, AI/ML-powered solutions, such as Tookitaki’s Reconciliation Suite, will undoubtedly define the future reconciliation processes in the financial services sector.
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