A Three-Pronged Approach to Prevent Naked Short Selling
How to safely short
Naked short selling is an illegal practice that is increasingly coming under the regulatory microscope in capital markets. In 2023, the Financial Services Commission (FSC), South Korea’s financial regulator, imposed a total penalty of KRW 26.5 bn (USD 20.4 million) on two global conglomerates for naked short selling.
In our 9 September, 2024 article, we outlined the nuances of the short selling process, which brings with it a host of regulatory and governance requirements if it is to be conducted licitly.
As such, GreySpark has designed a model which will allow firms to prevent and identify instances of naked short selling.
Three-pronged Approach to Prevent Naked Short Selling
GreySpark’s three-pronged approach, shown in Figure 4, encompasses robust governance, system level Order Management System (OMS) configuration and an adherence to regulatory-compliant data standards, with the objective of strengthening controls against naked short-selling.
Figure 4: GreySpark’s Three-pronged Model to Prevent Naked Short Selling
Source: GreySpark analysis
Step 1: Perform Traceability and Gap Analysis on Regional Regulations and Exchange Rule Books
The Traceability and Gap Analysis focuses on an independent assessment and review of the firm’s current e-trading conduct related to short-selling activities in the various markets to measure its compliance against the rules set out by each market and the regional regulatory body. This analysis allows the firm to gain insight into the completeness of its procedures and controls. High, medium and low risk hot spots are identified and an estimate of the scope and effort of remediation is then devised to drive remediation priorities.
Figure 5: Two Key Activities and the Related Deliverables of Step 1 of GreySpark’s Three-pronged Approach
Source: GreySpark analysis
Figure 6 (a to d) illustrates this methodology for transitioning from gap assessment to the establishment of a compliance and documentation framework for the exchange rulebook policy. While a comprehensive traceability and gap analysis are of paramount importance to firms, conducting an effective traceability and gap analysis presents significant challenges:
Resource Intensive: Conducting a thorough gap analysis requires a substantial number of people, time and expertise. Internal teams may lack the specific knowledge or experience needed to perform an in-depth analysis effectively.
Complexity and Volume of Regulations: The sheer volume and intricacy of regulations make it difficult to ensure a thorough and accurate analysis. This process involves handling and comparing large amounts of data from different sources, and adhering to complex short-selling regulations, such as disclosure, reporting, up-tick price rules and restrictions on stock eligibility for short-selling.
Frequent Updates and Interpretation Variability: Regulations and exchange rules are frequently updated, necessitating continuous monitoring and updating of knowledge. Establishing clear internal standards and procedures driven by systematic controls is crucial. However, different team members might interpret regulations and rules differently, leading to inconsistencies in the analysis.
Balancing Operational Adequacy and Efficiency: There is often a paradox in balancing operational adequacy and efficiency with regulatory requirements. Firms must maintain records in accordance with regulatory guidelines and obligations while ensuring their operations remain efficient and effective.
The initial analysis phase, shown in Figure 6a, identifies relevant rules in the Regional Regulations and Exchange Rule Books, measures gaps against first line (1LOD) system controls across in-scope markets. Applicable rules are segmented into traceable audit rule objectives, for example:
Trading (pre-trade checks, order book, etc)
Market making
Admission / membership
Conduct
Obligations (transparency, reporting)
Technical requirements
The high-level heat map represents the current effectiveness of the FIs internal policies and procedures for discharging exchange rule book requirements.
Figure 6a: Regional Regulations and Exchange Rule Book Audit Process
Source: GreySpark analysis
The deployment of an efficient approach for addressing identified gaps discovered in the previous phase is achieved via the compliance and documentation framework (see Figure 6b). This framework is utilised to structure and organise firm’s existing documentation for discharging exchange rule book policy. The approach facilitates a targeted remediation planning process across the organisation, through each line of defence and to specific stakeholders.
Figure 6b: Proposed Compliance and Documentation Framework
Source: GreySpark analysis
Figure 6c shows how gaps can be addressed by:
Utilising standard templates and policy/procedure mapping tools from in-house experience and best practices.
Referring to the Regional Regulations and Structured Exchange Rule Book and 1st Line playbooks and system/control documentation framework.
Managing a common procedure library referencing existing procedures, including completeness and effectiveness measures.
The deliverable should include a traceable exchange rule procedure inventory containing data points for gaps and directly mapped to the prioritised remediation plan.
Figure 6c: Compliance Documentation Framework
Source: GreySpark analysis
Repeating the gap analysis, as shown in Figure 6d, provides an updated view of the overall documentation and control gaps, illustrating improvements following the completion of remediation actions in a useful visual map.
Figure 6d: Rerun Regional Regulations and Exchange Rule Book Gap Analysis
Source: GreySpark analysis
Step 2: Configuring the Regulatory Rulebook in Order Management Systems
The successful integration of rulebooks in Order Management Systems (OMS) helps to prevent illegal short selling by enforcing compliance with regulatory requirements and internal policies. OMS rulebooks include checks and controls that ensure trades adhere to short-selling regulations, such as verifying the availability of securities for short-selling, monitoring compliance
with borrowing requirements and implementing pre-trade controls to prevent violations. These rulebooks integrate real-time monitoring and alerts to notify operations teams and compliance teams of potential breaches, enabling prompt intervention and enforcement of corrective actions. Additionally, comprehensive reporting functionalities within the OMS can add to audit trails and regulatory reporting, demonstrating adherence to short-selling rules and deterring illegal activities.
Meticulous planning is essential for analysing, defining, configuring, testing and implementing these rulebooks in the OMS. Figure 7 outlines the steps necessary for this implementation.
Figure 7: Process for Compliance Rule Setting in Order Management System
Source: GreySpark analysis
Step 3: Integrating Regulatory-compliant Data Standards into a Technology Solution
To facilitate the inspection process by the regulator looking for illegal short-sales trading, an industry-wide convention should be developed and enforced for financial institutions to adopt. For example, in Hong Kong, the electronic data standards of DS-OL were established to readily reconstruct order life cycles from initial receipt of an order instruction to final execution or cancellation. Control deficiencies and instances of non-compliance with the regulator’s Code of Conduct can be detected using data standards such as DS-OL. The implementation of a technological solution that incorporates the DS-OL standards can only be achieved when:
Firms agree to and follow a convention that is able to handle the heterogenous data formats of all financial institutions.
There is the capability to ingest and analyse large datasets.
Analysis can be done on data as it is ingested, rather than waiting for the complete dataset to be ingested.
With modern streaming frameworks, such as Apache Spark Streaming or Apache Kafka, massive volumes of data can be handled by distributing the processing across multiple nodes in a cluster. This approach provides sufficient scalability to allow for the analysis of massive datasets. Analysis can be done before the entire dataset has been ingested, which enables real-time insights and decision-making. The capability to generate instant red flags is crucial for applications that detect illegal short-sell trades.
Figure 8 illustrates a simplified end-to-end workflow for implementing DS-OL, highlighting the essential components, intermediate processes and the generated output. By carefully planning test cases to identify potential fraud patterns and red-flag data, DS-OL establishes a standard protocol that significantly reduces the inspection workload for regulatory bodies. This protocol minimises the need for customisation or fine-tuning, thereby facilitating the efficient inspection and identification of potential fraud cases.
Figure 8: Workflow to Perform Data Analytics on Large Trading Dataset using DS-OL as an Example
Source: GreySpark analysis
Regulatory bodies are tasked with preventing incidents like the recent one in South Korea. However, financial institutions face challenges due to limited implementation experience and understanding of the necessary procedural controls.
Financial institutions must undertake the following measures to ensure robust internal control processes to prevent illegal short-selling activities:
Evaluate the effectiveness of current compliance controls for short selling throughout the entire trade life cycle, designing and adopting rulebooks in line with local regulations and exchange rules;
Gain a deep understanding of OMS vendor capabilities, including configuring and implementing system rules to generate real-time alerts for flagged short-selling trades, and;
Understand the nuances and implementation intricacies of rule-based algorithms like DS-OL, particularly concerning regulatory standards for handling large volumes of trading data.
GreySpark Partners recommends firms follow our comprehensive three-pronged approach model, supported by subject matter experts, who can help implement advanced data analytics technology to prevent illegal short-selling.
For more information, please head over to our website.