Standardizing Broker to Regulatory Authority (SEC/FINRA) Communication with DeepSight^TM

We trust you were able to read our first blog (Are you ready for Sec T+1 Settlement reforms?) on the impending shift to T+1 settlement in the US, where we highlighted the reasons why broker-dealers and clearing brokers must automate and standardize communication related to trade. Here in this blog, we evaluate why regulatory filings must be automated as well.

Once a trade has been executed, the broker-dealer is expected to update the regulatory body as the case might be, with appropriate details related to the trade transaction. These reports or regulatory filings are a comprehensive summary of the trade that is submitted to the regulatory bodies on a timely basis. Regulatory filings involve trade status and timestamp details for all the actions like Order Initiation, Execution, confirmation, affirmation, matching, settlement, partially settle, rebook etc. In case there is a settlement failure or a rebooking, the broker dealer is expected to update the regulatory authority on that as well. The sole objective of this regulatory filing is to ensure transparency and to enable the regulator to assess and supervise the business being transacted by individual Counterparties within the marketplace. It is critical for protecting the interests of the investor and keeping the integrity and the security of the capital markets intact.

Typical Challenges in Regulatory Filings

Provided below are some of the typical challenges that broker-dealers face in ensuring a timely delivery of regulatory filings:

Operational Risk: Broker/dealers carry out trade lifecycle operations across multiple platforms and FinTech systems, often relying on complex manual processes to bridge the gap between these disparate platforms. However, they frequently face challenges due to outdated legacy processes and system performance issues and most importantly Data transfer issues due to Data compatibility, which hinder their ability to file regulatory reports in a timely manner.

Asset challenges: Investment managers face challenges related to diverse Asset types, including equity, fixed income securities, and ETD derivatives. Regulatory requirements for each instrument depend on the market in which it is traded, such as Organized Trading Facility (OTF) or Regulated Market (RM), as well as the specific guidelines set by regulatory bodies like the SEC, FINRA, and CFTC. As a result, the regulatory filing process becomes complex when broker-dealers do not automate or use a rule-based approach for FO-MO-BO data reconciliation and transformation.

Data quality and governance challenges: Excessive reliance on manual labor only for the classifying, aggregating, consolidating, and validating data during the multiple stages of the trade – initiation, confirmation, affirmation, rebooking, settlement constitutes a problem when it comes to meeting regulatory timelines or ensuring that all data is up-to-date and accurate.

STP challenges: All broker-dealers are typically required to report trade details to the SEC and other regulatory bodies in a timely manner. The reporting frequency and specific deadlines for filing these reports can vary based on the size and activities of the broker-dealer. In the absence of automation and STP, timely regulatory filings are difficult.

Finding the right vendor: Finding the right vendors for automating processes without impacting the existing business activities might not be as easy as expected. And that’s why broker-dealers need a partner with a thorough understanding of the capital markets and are capable of designing solutions that are tailored to fit.

Automating Regulatory Filing with Magic DeepSight^TM : The 7-point advantage

Capitalizing on its immense experience in Capital and Financial Markets, and bespoke AI/ML platform that customizes solutions as per need, Magic FinServ ensures that regulatory filings are seamless and smoother than before – beginning with faster, smoother, aggregation and consolidation of data (using automation) and benefiting from a rules-based approach that adapts to evolving regulatory environment (including shift to T+1, and others) easily.

1. Ensures data quality and governance: An AI-enabled platform like DeepSight can make a huge difference in the quality of data. Instead of inaccurate, inconsistent, and incomplete data, from manual data entry, broker-dealers are assured of clean, complete, consistent, and accurate data, for submission to the SEC and other regulatory bodies. DeepSight also validates and cross-references data, further minimizing the likelihood of errors and discrepancies. Most importantly is also creates an audit trail thereby enabling replaying of the transaction if needed.
2. Simplifying reconciliation/transformation of trade data: An AI/ML and rules-based solution can ensure a faster, smoother, and more accurate reconciliation and transformation of trade data emanating between the front, middle, and back office when compared to the manual approach. This is most critical as the Data Models, Formats and Templates differ for each application and area, a key reason why the manual approach is simply not feasible for the impending T+1 settlement cycle.
3. Easy integration: DeepSight can be easily integrated with existing systems. It supports data in all formats. The platform is format-agnostic and has the capability to support all sorts of data formats such as Excel files and spreadsheets, CSV files, emails and attached documents, API integration from multiple systems, and unstructured data.
4. Shared database for data multi-purposing: Whatever the file format, DeepSight parses through data seamlessly from disparate sources such as back office, middle office, front office and processes, transforms, enriches it, and creates a single source of truth in a shared location or database.
5. Enables timeliness and compliance: With DeepSight, broker-dealers can ensure that regulatory filings are done as per the timelines set by the regulatory authority. By automating the workflows, extracting the data from multiple sources (the back, middle, and front offices) and compiling it together becomes easier.
6. Single solution: Straight through processing (STP) results in seamless and smoother regulatory filing. This integration enables seamless data flow and enhances overall workflow optimization. It reduces manual data transfer and improves the accuracy and efficiency of the trade reporting process.
7. Adopt new regulatory changes easily with a rules-based approach: In an evolving regulatory environment, a rules-based solution makes it easier to reconcile data and file reports with the regulatory body becomes easier.

As the market gears up for T+1, this was how we could enable your transition to it. For more you can write to us mail@magicfinserv.com.

Enhancing Broker and Dealer Transition to new Sec T+1 Settlement with AI/ML Intelligent Data Automation Solution

In trading, time is of the essence, as every moment wasted in settling or reconciling a trade incurs higher costs and greater risks. Today, as the US proposes a shift to the T+1 settlement cycle, the primary objective is reducing the time it takes to settle a trade. And in the process, decrease the risks. That seems justified as the markets have experienced severe shockwaves in the last two years, due to market volatility, pandemic, fall of meme stocks, etc.

The T+1 settlement cycle essentially means that all settlements relative to trade must be carried out the next day and is expected to yield benefits like reduced costs, increased market efficiency, and reduced settlement risks.

So, while earlier, the settlement cycle (t+2) looked like this:

Now we have a settlement cycle (T+1) that looks like the one below:

Implications of Transition T+1: Unveiling the Key Challenges in Broker-Broker (Executive and Clearing Brokers) Communication

Though the transition to T+1 provides multiple benefits, the shift from T+2 to T+1 is not easy. We elucidate this using the example of brokers/dealers, who are a vital part of the trading chain. T+1 settlement of institutional trades lowers margins for broker/dealers. Brokers are required to pledge cash and securities to a clearing house, benefit enormously from the lower margin requirements (difference between the current value of the security offered the collateral and the value of loan granted). But it is not a win-win situation for them yet.

One of the biggest challenges in transitioning to the T+ 1 settlement cycle is the lack of automation in any communication emanating between broker-broker or the Executing Broker and the Clearing Broker when it comes to Trade File Processing. This broker-broker communication is centrally a part of the back-and-forth information processed by the middle office (MO) and settlement information/status received from the Clearing House or Back Office (BO)system.

Another significant challenge is the reconciliation of trade files and other reports. Without automation, manually updating these details, typically in Excel or spreadsheet format, can be quite cumbersome. The executing broker shares trade details with the clearing broker, usually in the form of spreadsheets, which are then processed and imported by the analyst team into the clearing system.

When investment manager, broker-dealer, clearing dealer rely more on manual processes than automated, time lags and delays are bound to happen as everything happens sequentially instead of bi- directionally. With automated processes, the majority of trades can be processed on the same day without requiring manual intervention.

Markets and prices are in a state of flux when it comes to trading. Hence, broker dealer, clearing broker must always be in a state of alert. Even remote chances of error or trade fails must be rooted out, unfortunately with manual mistakes that can have major consequences are higher.

Additionally, there are other unresolved issues such as:

• Manual entry of data from documents received via email or fax from the investment manager when a trade is blocked. There is also a substantial amount of manual effort involved in the reconciliation and communication between the executing broker, the clearing broker, and other parties, for final clearing and settlement that must be automated for ensuring SDA(Same Day Affirmation).
• There is still a substantial amount of paper involved
• Sliced, dicing, and digesting the unstructured data in emails and faxes in time for T+1
• Most firms are burdened by a crumbling legacy architecture that cannot scale up fast enough. If that were not concern enough, building a new one that could ensure adherence to t+1 from scratch would be time-taking and excessively expensive.
• For (T+1), broker/dealers and clearing broker must speed up affirmations, confirmations, and allocations processes. But how do they do that when they have not yet automated their processes and there is no STP.

So better late than never! We are here to help firms navigate the transition to T+1, by redefining and re- strategizing the options and integrating our magical solution DeepSight^TM that leverages the power of AI and ML to ensure a win-win. But first here’s a brief on T+1:

Automation is pivotal for T+1: How AI/ML and RPA helps reach the magical Same Day Affirmation (SDA)

The biggest challenge for T+1 transition is the lack of automation in institutional “allocations and affirmations.” This is one area that requires massive transformation to achieve the proposed settlement cycle timeframe. An automated solution can play a crucial role in facilitating same- day affirmation (SDA) processes for broker-dealers and clearinghouses.

With automation, broker-dealers and clearing houses can also:

• Reduce the risk: As the volume of unsettled trades over a single trading day and the time between trade and settlement are reduced, counterparty, system-related, and operational risk is reduced.
• Trade capture and validation: Perform real-time validations, ensuring that trades meet pre- defined criteria and are eligible for SDA.
• Enables seamless transition: By automating various aspects of the settlement workflow, broker- dealers and custodians can minimize manual intervention, reduce operational risks, and enhance overall operational efficiency.
• Eliminates the need for manual intervention and errors: Eliminating the need for manual intervention and reducing the risk of trade discrepancies.
• Exception handling made easier: Automatically identify and flagging trades that require manual intervention. focuses on the resolution of exceptional cases promptly, paving the way for smoother SDA processes.
• Seamless data validation and reconciliation: Validate trade data and reconcile it with external sources, such as market data providers or reference databases.
• Prompter resolution of errors: Potential discrepancies or errors can be identified and resolved promptly, reducing risks associated with inaccurate or incomplete data.
• Enables straight-through processing: Eliminates the need for manual rekeying or intervention at different stages.

Revolutionizing T+1 Settlement: Empowering Broker-Dealers and Clearing Houses with DeepSight^TM

Now is the time for broker dealers and clearing houses that have not yet implemented automation to take to aggressively pursue automation if they are to abide with the proposed new rules. For broker dealers and clearing houses, the focus would be on ensuring SDA.

Here’s how Magic FinServ’s AI Optimization framework – DeepSight^TM that has at its core AI/ML and Data builds tailored solutions that reduce the need for human intervention stoking up processes and ensuring optimal levels of efficiency for processes related to confirmation, allocation and affirmation and trade matching.

Magic FinServ’s innovative digital solution leverages the power of data and AI/ML technology to standardize business processes related to trade file processing by automating the broker-broker communication. Our highly intelligent and scalable solution shifts through data sources in different formats: Excel/spreadsheet/CSV files/Email body/Email attachment/API integration from multiple systems/ and other unstructured formats with ease and creates the “Reconcile Report” for other market player. It also supports the setup of the Golden Copy Data Management for multiple other sub activities related to the trade lifecycle. Other aspects of our solution include – Exporting the reconciled trade file, configuring any Business Rule/Mathematical rule which is required for generation of trade file, and generating reports based on customer need, i.e., in JSON, API, excel or any standard template.

While DeepSight^TM can help automate processes, the move to T+1 settlement will still require fundamental changes throughout the trade processing lifecycle.

• Consolidation of data feeds between new and legacy systems to centralize data management.
• It is necessary to adopt technology (e.g., DTCC’s ITP CTM) and/or messaging protocols (e.g., FIX) to automate the communication of allocations and CTM’s Match to Instruct to facilitate more timely trade affirmations.
• As firms move to T+1 settlement, they must adopt technology (e.g., DTCC’s ITP CTM/M2i) and/or messaging protocols (e.g., FIX) to automate the communication of allocations.

The Incredible Benefits of DeepSight^TM

When broker-dealers, whether they are small boutique firms or subsidiaries of investment banks, consider their options, they can reap several benefits.

Eliminate the friction: Firms can eliminate the friction that exists at multiple touchpoints when data is entered manually. They can leverage the AI/ML capabilities to extract relevant data from documents, pdfs, mails/faxes, etc.

Fasten the post-trade agreement and affirmation by almost 50%: A solution like DeepSight^TM can scale quickly and is ideal for periods when trade volumes are high or market volatility is high or both, as it trained to extract the appropriate data from the swathes of information available infinitely faster than humans.

Benefit from data-driven approach: Trade is ultimately about data. As the data experts, we can quickly identify which are the processes that would require automation. So, whether investment managers/portfolio managers who need help analyzing their performance or peers and counterparties/broker-dealers, custodians, our solutions can ensure that the transition to T+1 is smoother.

Reduce operational risk: With standardization and STP, operational risks are reduced considerably. When organizations opt for a solution like Magic Deep Sight, that leverages the power of AI and ML, and that can be easily integrated with existing systems, allocation, conformation, and central matching is given a boost. With SDA, firms can easily ensure the next day’s settlement.

Reference data management: Reference data management is a critical part of data management. To ensure transparency and efficiency, firms must update their reference data (e.g., the asset type, counterparty information), security pricing data, and standardized settlement instructions (SSIs). With DeepSight^TM , the processes are streamlined and there is no chaos.

Easy and seamless integration with legacy architecture and workflows: No need to replace legacy: DeepSight^TM biggest advantage is the heuristic approach wherein firms do not have to replace the existing workflows, as our solution can be integrated with traditional workflows and legacy architecture.

Exception Management: This metric assesses the ability to identify and resolve exceptions or discrepancies promptly during the settlement process. Efficient exception management helps streamline operations, reduces manual intervention, and enhances overall settlement efficiency.

Conclusion: A Shorter Settlement Cycle Benefits All!

Shorter settlement cycles benefit all. Some of the benefits are:

Shorter settlement cycles benefit all. Some of the benefits are:

• Improved straight-through-processing (STP)
• Quicker settlement
• Less margin required
• Reduction of operational and systemic risk
• Decrease in costs and resources from reduced number of unsettled positions

Irrespective whether it is an investment manager, broker dealer, clearing dealer or clearing house, custodian, or settlement agent, T+1 is good for all. Ideally, T+0 settlement cycle offers the best deal; however, it would require a massive overhaul of the existing architecture, hence the SEC and other regulatory bodies have opted for transition to T+1 for the time being. Though some amount of re- strategizing is required to get in sync.

By embracing automation and STP, broker-dealers and custodians can enhance their operational resilience, reduce settlement risks, and improve client experience. They can focus on value-added activities and provide faster and more efficient services to market participants. If there is more that you would like to know as a broker dealer or clearing house, you can drop a mail at mail@magicfinserv.com

In today’s fast-paced world, technological advancements are reshaping industries, and businesses must adapt to stay relevant and competitive. This infographic explores the importance and inevitability of modernizing applications and platforms, uncovering the transformative potential that lies within this process.

Unlock the power of modernization and embark on a journey towards a brighter future for your business. By breaking the shackles of legacy, you embrace the inevitability of progress and position your organization for success in a rapidly evolving digital landscape. Stay tuned as we delve deeper into the world of modernization and share insights on how to navigate this transformative journey. Together, let’s shape a new era of possibilities.

Managing shareholding data is a complex business. Understanding how corporate events such as buybacks, mergers and acquisitions, dividends, bonus shares, spin-offs, and others affect a company’s total share outstanding value and total voting rights is even more complex due to the proliferation of often expensive data sources, complex shareholding disclosure rules, and multiple jurisdictions. Additionally, companies invest in multiple equities spread across diverse geographies, which further increases the complexity of the task. The data itself comes from various jurisdictions and exchanges in different formats, and changes are notified in different ways, which adds to the level of complexity. Therefore, analysts must be familiar with the form and type of notifications issued by various exchanges.

Another key concern is to maintain up-to-date shareholding information, including an account of the company’s total outstanding shares, their value, and total voting rights. This information is critical not only from a fiscal and financial perspective – to calculate business growth, equity per dividend, and other downstream calculations – but also to ensure compliance with predefined compliance and disclosure rules.

Since the rules governing voting rights for a certain set of corporate actions differ across multiple jurisdictions, these actions could impact your beneficial interests due to indirect investments. To address these problems, data must be collated and extracted, incorporating the rules governing that data for the particular jurisdiction and updating their impact on the value of outstanding shares, voting rights, and more. It is critical to keep shareholding information up to date, as there have been serious consequences and hefty fines levied on Asset Managers, Hedge Funds, and Portfolio Managers in recent years for not being up to date with shareholding disclosures. For instance, French regulators recently penalized an activist fund and recommended a fine of 20 million Euros for failing to provide correct and timely information to the Autorité des Marchés Financiers (AMF) about a takeover bid, thereby harming the interests of minority shareholders and impacting the market’s integrity.

Decoding Shareholding Disclosure Rules

There are shareholding disclosure rules that asset managers and hedge funds must comply with. These rules help establish control and trigger warnings in a timely manner, ensuring that the interests of the market and investors are not compromised.

Shareholding Disclosure Rules

Not a cakewalk!

Although not keeping an updated record of shareholding can result in serious consequences, keeping track of shareholder data and voting rights is not a simple task that can be done with a flick of a wrist like a magic trick. Many firms still rely on manual data collection and aggregation, making the process even more challenging. This is how the traditional, largely manual As-Is business flow for shareholder disclosure and shareholder data management operates:

Secondly, globalization has led to firms investing in equities globally. This trend has made shareholder data management complicated, as firms now have to contend with multiple jurisdictions.

Getting Clear and Updated Shareholding Data! What are the options available?

Asset managers require a comprehensive understanding and reporting of various types of shares, including equity shares, authorized share capital, issued share capital, right shares, bonus shares, sweat equity shares, preference shares, cumulative and non-cumulative preference shares, participating and non-participating preference shares, and convertible and non-convertible preference shares. These shares should be available in both structured and unstructured formats within company reports such as the balance sheet and financial statement, as well as data terminals.

Additionally, it is necessary to consolidate and aggregate the different types of shares mentioned earlier. A precise centralized data system must be in place, complete with a rule-based intelligent process that accesses data sources in a timely manner and stays up to date with corporate events that impact shareholding and voting rights.

As highlighted earlier, managers who hold international stock holdings that fall under different jurisdictions face complex regulatory and compliance issues. For example, the company issuing the stocks, also known as the issuer, may have different share capital requirements depending on the jurisdiction and market, including preference shares, unlisted shares, or derivatives trading.

As an asset manager or hedge fund, firms have three options to consider:

A) They could use their own platform/product to process compliance or regulatory filings. This would result in the firm managing shareholder information on its own while using the data services of a data vendor.

B) Alternatively, the fund could use the services of a third-party platform such as a Reg-Tech and compliance product. In this case, the third-party platform/product would use shareholder information from another data provider for the securities portion of the portfolio. The third-party organization will charge costs depending on the jurisdiction they are covering, as this is an on-demand service.

C) Alternatively, funds and wealth managers could outsource the shareholder disclosure and reporting task in its entirety to a BPM vendor to save time and effort while keeping up with the latest requirements. This would give them everlasting peace of mind as they would no longer have to worry about missing deadlines or regulatory requirements.

Process Automation: Benefits of Automated, Rules-Based, Comprehensive, End-to-End Solution

Since the 2008 financial crisis, shareholding disclosures have become an obligatory reporting requirement. However, over the years, the associated complexities with reporting have increased manifold. It is no longer feasible to manually review financial statements and public website data to ensure timely compliance. Process automation is the solution to simplify shareholder data management and shareholding disclosures, ensuring accurate and timely insights for downstream calculation, compliance adherence, and other activities related to the organization’s health.

A complete end-to-end niche solution, like the one offered by Magic FinServ, that combines technology and managed services and is driven by a team of experts in both the financial and technology domains, can help eliminate the pain points associated with shareholder data management and shareholding disclosures. With a unique “rule-driven” solution that aligns with geographical requirements, such a solution can keep funds and wealth managers up to date with the latest developments.

Key Features of Magic FinServ’s Solution Component:

• Data Management: This feature manages all instrument identifier data and all other information required for extracting information from exchanges in multiple jurisdictions.
• Document Record Management: This feature manages all documents and stores them in a structured or normal PDF format after conversion from unstructured formats.
• Rule Engine: The rule-based engine is a critical component of Magic FinServ’s offering as it defines the rules for extracting information from documents.
• API Integration: The solution can be easily integrated with other existing platforms and systems for data consumption.
• Reporting and Dashboard: This feature demonstrates and generates a report based on business criteria.

Solution Features

Timely and accurate data is always important, especially with regards to shareholding disclosure and voting rights, particularly when the threshold is crossed for substantial shareholders and takeover bids. However, extracting and feeding correct information into workflows can be an excruciating exercise and not as simple as pulling a rabbit out of a hat.

Magic FinServ helps achieve all the objectives mentioned earlier in a timely manner. This begins with tracking corporate action events, automatically accessing relevant notification sites, reading, and extracting the data to identify key value pairs, and transforming it to the investing company’s data standards. Rules are then applied, and the final outcome is fetched into the investment table and various other reporting forms.

If you would like to learn more about how we can help, please connect with us today at mail@magicfinserv.com

As an investment compliance team or an Asset Manager, one of the chief responsibilities is to monitor and administer the position holding of high-value institutional investors in a manner that is beneficial to the investor while meeting regulatory obligations. When it comes to investment monitoring, asset managers must ensure high levels of transparency. This is necessary as unethical practices such as short selling, account takeovers, disproportionate flow through, etc., not only harm the stakeholders’ interests but also result in massive fines and build a bad reputation. For example, an asset management company had been fined £7.2 million in 2013 for not heeding investment protection compliance regulations.

For private market investment, the buy-side asset manager (which acts as investor/LP) also needs to maintain transparency and identify or control the risk associated with their investment cash flow. To do this, the investment monitoring team gathers and monitors all the investment records and distribution received from the General Partner (GP) in a timely manner and relates this with the fund market value.

(A) What is Investment Monitoring in terms of Beneficial Disclosure and Position Limit Monitoring?

For asset managers and institutional investors who hold multiple securities (listed and traded) in a regulated market governed by different jurisdictions, shareholding disclosures continue to be a mammoth task. The challenge is further compounded by the fact that firms must also ensure compliance/make specific disclosure for:

• Investing in a sensitive industry
• Involvement in a takeover bid.
• Accumulating substantial shareholding in a security
• Engaging in short selling

1. Monitoring Shareholder Information and Calculated % of Disclosure/Threshold
   • Shareholder information pertaining to the company’s share capital data and voting rights
   • Used for the calculation of the holding % ownership (threshold). When the value exceeds the threshold (depending on the jurisdiction) monitoring and reporting must be carried out accordingly.

Beneficial Ownership Reporting

“A beneficial owner is any individual who, directly or indirectly, owns or controls at least 25 percent of the ownership interest of the reporting company.”

Beneficial ownership reporting (against violation as per law defined by the jurisdiction) to the NCA (National Competent Authority). For example, Schedule 13/Form 13 filling to SEC in case the jurisdiction is in the US.

2. Position Limit Monitoring

Position Limits represent the maximum number of holdings of the future/option contract corresponding to a given security.

The position limit or threshold is defined by regulatory bodies like CFTC, ESMA, etc., and the exchanges (CME, ICE, etc.) differently.

The investment manager must monitor the thresholds mentioned herewith and inform the respective bodies in case there is a violation.

1. Exchange Position Limit: This limit is defined by exchanges like CME, ICE, etc.
2. Regulatory Body: The regulatory body, for example, ESMA defines the position Limit in MiFID 2 Article 58/58

What does the typical investment monitoring workflow look like and why are asset managers not in control?

This is what a typical investment monitoring workflow looks like for Shareholder & Position Limit Monitoring:

When it comes to shareholding disclosures, here are some of the challenges that asset managers face:

1. Data Consolidation from Multiple Sources system (IMS, OMS, 3rd Party Data Provider, Exchange)
2. New Customer Onboarding Challenges
3. Data Transformation, Tagging, Data Validation or Completeness.
4. Netting/Aggregation of Position
5. Monitoring the % Disclosure value on Timely manner due to dynamic effect of Corporate Action event.

Role of RegTechs!

When it comes to investment monitoring, it would be difficult to envision how to get things done without Regtech’s involvement. Regtech is the management of regulatory monitoring, reporting, and compliance within the financial industry through technology. Regtech systems can not only monitor the current state of compliance against upcoming regulations but ensure real-time compliance as well.

How Regtech Support the Business?

Challenges for RegTech?

Magic FinServ’s Operational Model paves the Way for Change for both Reg-Tech Partner and Asset Management Firms:

Before embarking on a new journey with automation and analytics, firms must ensure that the mapping of data is accurate and complete. And herein lies the biggest challenge. You can onboard a platform or system, but if the system does not recognize the data or information, automation is pointless and real-time updates are skewed or not verifiable.

Biggest Obstacle to Automation is Data: Resolving the challenge the Magic Way with DeepSight^TM

Unsurprisingly, despite the advancements in technology, what remains the biggest challenge for Asset Managers, Portfolio Managers, and Investment Managers is data, or rather the state of data. No prizes for guessing that correctly, for data is always at the center of controversy. If it is in good shape, organizations reap rich dividends by being on top of the game, but poor data is no good. When it comes to investment monitoring and the data conundrum, some of the chief concerns that asset managers and hedge funds face are:

1. Data onboarding and transformation: client data is not in the required format and is scattered in silos: When you have heavy unstructured data, data ingestion takes longer than required.
2. Data incompleteness or missing data points – Another concern is data lineage or finding the source of data which is critical for data transformation.
3. Data validation – Checking the quality of source data before processing data.
4. Collaboration among diverse teams and appropriate knowledge sharing is another key challenge.

At Magic FinServ, we believe that the Investment monitoring mechanism can be simplified by understanding the client’s compliance requirements first. We need to thoroughly analyze the client’s data files and understand what is it that they really need support with before – is it the lack of data, the incompleteness of data, the lack of understanding of the regulatory mechanism, or quite simply process simplification, before integrating the system or aligning the product to requirements.

This would also imply supporting the client in data transformation and reconciliation. This means cleaning the data, loading it, and validating it.

For example, let us consider a scenario wherein the senior leadership of a company “X” who are also shareholders of the company decides to short-sell to a bank or Venture Capital fund, which has also invested in the company and thereby are shareholders of the company. Now depending on the Regulatory policies as per corresponding jurisdiction, this is a clear violation of Threshold and must be reported to the regulatory bodies accordingly.

Now for alerts or triggers to be generated for action, there must be a clear-cut definition for raising an alert. However, this is not possible in a vacuum.

Processes must be streamlined, a rule-based system must choose accurately from the fields and columns of the data provided, and quickly raise alerts in case there is a discrepancy (or a cause for an alarm) and update it on the compliance system.

DeepSight^TM AI/ML automation solution has the capability to extract relevant information from multiple sources and reconcile it based on any applicable business rules. Provided below are some use cases where automation can transform processes completely.

Use Case 1: Maintaining & Monitoring dynamic values of shareholder data and voting rights due to Corporate Action event in Timely manner

Firms must keep up to date with real-time values of company shareholder data and voting rights because any corporate action change can cause a material change to a company and affect its stakeholders. Information about corporate action is published in the form of news alerts or web links which are unstructured data sources. With DeepSight^TM firms can automate shareholder-managed services and support the compliance monitoring team.

Speedier Migration and Quicker Transformation of Data with Magic FinServ

Systems do not understand data and its sources. Hence, implementation remains a challenge. Even the most perfect tools and platforms lack the comprehensive (and comprehending) power of humans. The biggest misconception that organizations fall prey to is getting an expensive tool and hoping it will automatically run one fine day. It simply does not work that way. The system does not understand the rules of the game (investment monitoring). It must be taught. It must be provided directions.

Helping the system understand.

And how does the system understand? It is possible only when both files are understood, and a one-on-one mapping is done. Thereafter, the rules are applied as per the defined jurisdiction or client requirement. And here’s how we can help.

So, for example, there is a new client that desires to use a tool/platform for investment monitoring of shareholding business. The cornerstone for setting up the tool is understanding the set of procedures required for running the data on the system daily. The workflow must be onboarded to the automation tool – the system.

However, before that, some files such as the security and position files are shared as a sample. Thereafter the mapping is done – map all the information in it (files shared) with the automation tool’s data scheme. When the schema is completed mapped, then only can the desired impact of automation for investment monitoring be perceived.

Use Case 2: Client Onboarding made easy with DeepSight^TM

Generally, client onboarding on a system is a laborious affair if it is done manually. It is also highly expensive and error prone. With our Agile Project Management approach, we ensure speed and transparency even under the most excruciating of circumstances. Migration and transformation of data that was unusually long and laborious is streamlined. The results are evident more quickly as we ensure support to analysts and SMEs during all the critical milestones.

DeepSight^TM simplifies new customer onboarding. It aggregates position values (based on regulatory rules) easily. It can facilitate the setup of an exception and alert mechanism when threshold limits are breached. Overall, our solution saves unnecessary costs and efforts, and by eliminating challenges related to data profiling, data completeness, and data lineage, ensures compliance with established standards.

By integrating and configuring the customer source system using DeepSight^TM automation tool and including steps such as data profiling, data completeness, transformation, and mapping data, the process is made smoother without any manual intervention.

The biggest benefit that you get with Magic FinServ is a less irksome and less time-consuming client onboarding (on the compliance system for investment monitoring). With analysts spending less time monitoring the tools, your teams can engage in more productive tasks and leave us to take care of how real-time data will be integrated in the system.

(B) Investment Monitoring: Private Equity (PE) Investment by Buy-Side Asset Manager (Acts a Limited Partner (LP)

Now let us take the specific case of Investment monitoring by the Endowment Investment Institute, which is a Limited Partner in private equity, venture capital, and private market investment funds.

DeepSight^TM helps customers manage all requests and documents in a digital library. The strategy for managing documents is based on the company’s investment fund strategy, making tracking, monitoring, and auditing processes easier.

It also helps customers manage and reconcile private equity fund cash flow information, along with other calculated values such as total commitment, funded commitment, recallable capital, and unfunded commitment for each private equity fund.

DeepSight’s AI/ML-enabled automation solution for Private Equity Fund can create Delta or Comparison reports based on internal data reconciliation and generate reports related to the Private Investment’s cash flow in a timely manner for each fund investment. It also creates alerts in case of any violations. It can also export information through an API or any other mechanism and generate reports using standard metrics.

Use case 3: Extract and reconcile data (from multiple sources) and carry out reporting for all the private equity investment cash flows and market value/fund performance:

With DeepSight^TM ‘s automated solution, compliance, and investment performance teams can easily extract and reconcile all the cash flows and investment performance information from the structured and unstructured sources. Investment performance teams can also identify the delta and create an alert if the fund administrator fails to execute the order on time.

DeepSight^TM can make things easier for you. For more on how we can be of help, write to us mail@magicfinserv.com

In this world, headwinds are far more prevalent than winds from the astern (that is, if you never violate the Pythagorean maxim). – Author: Herman Melville

In our earlier blogs on investment monitoring and transaction regulatory monitoring, we provided a detailed description of the challenges that institutional investors, hedge funds, and asset managers face with respect to filing and monitoring of reports. And along with the challenges, the panacea – an automated rules-based solution that speeds up the data extraction process by a zillion times, enriches and transforms data with tags and maps, while integrating easily with the required workflow and facilitating last-mile process integration. So that regulatory filings no longer remain the nagging pain for business heads and analysts that arises every time it is filing time. And that is every quarter!

Here in this blog, we will be discussing another monumental legacy of entrepreneurship across the world -private equity funds. Along with it, the obstacles, or the headwinds that financial advisors to hedge funds, and hedge funds and asset managers themselves face while filing their reports such as form PF, and alternative asset management funds.

Considering that volatility of the markets, the inglorious end of the Credit Suisse chapter (plagued by constant reprimands from the regulators in the last couple of years for financial irregularities) and Silicon Valley Bank closure that is creating a ripple effect that reverberates throughout the financial and capital markets, and increasing pressure to conform to the regulatory requirements, this blog will be on how Magic FinServ and DeepSight^TM purports to be the “wind beneath the wings.”

What are the key filings?

We begin with a definition of the key filings and the historical relevance of these funds. In the global business eco-system, private equity funds hold an elevated place as these have not only resurrected or reinvigorated companies but have provided them with the much-needed capital leverage during their start-up or fledgling phase. You need to look no further than what is considered the most valuable company in the world today – Apple – which too received funds from private equity during the initial phases.

Because the funds in question are huge, hedge funds and asset managers, and financial advisors that manage them are required to ensure that risks are mitigated, and there is transparency. Some of the key regulatory filings that are applicable to funds include:

Form PF: A registered investment adviser with at least US$150 million of ‘private fund’ is required to file Form PF with the SEC, which requires disclosure pertaining to

• gross and net performance,
• gross and net asset value,
• the aggregate value of derivatives,
• a breakdown of the fund’s investors by category (e.g., individuals, pension funds, governmental entities, sovereign wealth funds),
• a breakdown of the fund’s equity held by the five largest investors.
• summary of fund assets and liabilities
• including Sections 2a (Aggregate Positions) for $1.5 billion in hedge fund assets under management, 2b (Risk Measure),

Form CPO-PQ: As per CFTC regulations most derivatives are included as ‘commodity interests’ that cause a private equity fund holding such instruments to be deemed a ‘commodity pool’ and its operator to be subject to CFTC jurisdiction as a CPO or its adviser (typically the investment adviser) to be subject to CFTC jurisdiction as a CTA, and, unless an exemption is available, to become a member of the National Futures Association (NFA), the self-regulatory organization for the commodities and derivatives market. Source: Regulation of private equity funds in USA.

Alternative Investment Fund Manager Directive (EU AIFMD): Any manager that operates a fund in the EU is subject to AIFMD regulation. The Alternative Investment Fund Managers Directive (AIFMD) is a European Union (EU) regulation that applies to alternative investments, many of which were left largely unchecked prior to the 2008-09 global financial crisis. The directive sets standards for marketing around raising private capital, remuneration policies, risk monitoring and reporting, as well as overall accountability.

Where does the challenge lie?

Finding the needle in the haystack: As apparent, the regulatory filing is a massive exercise involving humongous amounts of data from which relevant field items or data points must be picked. The entire process can be likened to finding a needle from a haystack. Manually filing and reporting is an extremely time-consuming exercise. It disrupts normal business as additional effort is required to process it in time. And to make matters worse, the manual approach is also massively error-prone

Lack of process standardization results in duplication of effort: When filing and reporting is being conducted manually, firms due to time constraints are not focusing on information generation, rather they try to meet the deadlines. Whether it is Form PF or Form CPO-PQR filings, the processes are different, and with no efforts made to standardize the information, firms end up going through the same set of information again and again. The absence of a centralized repository complicates results in rework. Creation of a compliance data repository for all the relevant and necessary data, as well as the creation of business values for calculating measures and risk metrics.

Different systems complicate processes: Another headwind is the task of compiling, netting, aggregating, and validating data from the different business ecosystems as each functions differently. Each ecosystem could rely on processes, approaches and workflows that are different from the others making it tough to validate and reconcile data.

Testing and creating a sample for automation. Ensuring last-mile process optimization and coordinating with the regulator

Lack of collaboration and process standardization are the headwinds: Siloziation culture, and lack of process standardization come in the way of timely and accurate filings. Working out a sync between internal and external parties – exchanges, data vendors, compliance teams, and third-party vendors so that important action items are not missed and reported in a timely manner constitutes another operational challenge.

Navigating the challenge with an automated and rules-based data-driven tool

In order to meet the Form PF and Form CPO-PQR filing requirements in a manner that is accurate, transparent, and up-to-date while ensuring that it is in consonance with the regulatory and compliance guidelines of SEC, CFTC, and European Union’s AIFMD among others, hedge funds and asset managers must adopt a clear-sighted and streamlined approach that funnels the power of cutting-edge technologies such as artificial intelligence and machine learning while concentrating on data-centricity so that there is a centralized data repository, and streamlined processes that can be can be leveraged for optimal utilization of resources. In case there are additional filings for regulators in other jurisdictions as per need, streamlined processes can easily meet the need. It also requires a standardized data gathering and compilation process, and consistent data usage across business units.

An automated and rules-based approach tool is ideal for cutting the slack and for ensuring timeliness and accuracy, and we combine that with our knowledge in the financial services domain and our team of experts who are well-versed in the nitty-gritty of regulatory compliance practices to make fund regulatory filings a pain no more.

Here’s how we can make monitoring and reporting streamlined and hassle-free.

The Roadmap

Assessing Needs and Gaps: Begin by assessing and analyzing the requirements.

1. Find out what it is that the firm requires.
2. What are the reports that are to be filed (Form PF, and Form CPO-PQ, and in addition additional investment)

Identify the sources of data, extract relevant data & transform data using DeepSight^TM

Identify where it is that you get the data, the websites or external sources, and the internal systems such as the portfolio management system(IMS, etc.) What are the gaps that exist? What could have been an extremely complicated exercise, is simplified with DeepSight^TM

Using a rules-based approach, and leveraging its AI and ML capabilities, DeepSight^TM intelligently captures data from different sources – websites and internal systems and transforms it in a manner so that data is accurate, complete, and validate it.

Further, in case gaps exist, liaise with the data providers and exchange where requisite information can be available. Ensure that a golden copy of data is in a centralized data repository for further aggregation and analysis as per need.

Validating data and calculating key business values using DeepSight^TM

Our powerful AI and Machine learning enabled DeepSight^TM to analyze and validate data for completeness and accuracy. Data is enriched and categorized as well. Lastly, when it comes to the analysis of certain key elements required by Form PF, such as portfolio duration, turnover, liquidity, and market risk metric, DeepSight^TM can be an invaluable ally.

Another key functionality of DeepSight^TM is related to the calculation of key business values or metrices.

For more on what how we can make fund regulatory reporting less painful, reach out to us, at mail@magicfinserv.com

Transaction monitoring is “the process of reviewing, analyzing and administering the transactions processed on a business application or information system”. It is extremely critical for Asset Managers, Hedge Funds, Banks, and Financial Institutions for downsizing risks in a volatile market and ensuring that the most stringent regulatory requirements are met.

Considering recent fiascos such as Silvergate and Silicon Valley Bank and the Black Monday of 2020 when global stock markets crashed on 16 March, and US stock markets suffered from the biggest single- day fall since the 1987 crisis, there is a lot at stake for Portfolio Managers, Asset Managers, and Financial Institutions as situations such as the above could have far-reaching consequences and create a negative ripple effect.

While Silvergate and Silicon Valley Bank suffered an ignominious ending, the Black Monday of 2020 resulted in banks and reserves globally cutting their interest rates and bank rates and offering unprecedented support to investors so that a repeat of 2008 would not happen.

Decoding the challenges faced by Asset Managers and Financial Institutions

Regulatory compliance: From a regulatory perspective, banks, investment firms, and asset managers must comply with certain transaction-based regulatory standards like the Money Market Statistical Reporting (MMSR) Regulation, the Markets in Financial Instruments Directive II/Regulation (MiFID II/MiFIR), European Market Infrastructure Regulation (EMIR), and the Securities Financing Transactions Regulation (SFTR). For banks and financial institutions, failure to monitor and report in a timely manner could result in massive penalties and further corrode their reputation.

Bogged down by bad data: However, monitoring and reporting in a timely manner is not easy. Asset Managers, Banks, and Financial Institutions are bogged down by many challenges, particularly those related to data. The data collected by old and archaic systems are constrained and rules/scenarios are not applicable or fail to produce the desired results. Banks and Financial Systems must also counter the fact that data is generally of poor quality – that is incomplete and inaccurate. With data emerging as the mainstay of an effective transaction monitoring system, inevitably, there is a lot that must be done to ensure accuracy, consistency, and fewer false positives.

Tackling potential disruptions quickly: Whether a Bank or an Asset Manager, they must make a case for dynamic transaction monitoring for gaining insights quickly so that potential scenarios can be tackled quickly. However, when they are burdened with humongous amounts of false alerts, monitoring becomes a challenge, and banks and financial institutions either need bigger teams or smarter technology and AUTOMATION.

Other challenges: Some of the other micro and macro challenges faced by Asset Managers and financial institutions today when it comes to regulating and streamlining transaction monitoring are:

• Lack of standardization in the labelling of data.
• Incompleteness of regulatory data information as per business need.
• Monitoring and controlling data quality issues.
• Lack of expertise for the implementation of regulatory requirement workflow in the financial system.
• Managing the regulatory database and monitoring streamlined data flow
• Reconciliation and distribution of feedback status from NCA, ARM to the Client.

How Big is the Risk? For Banks and Asset Managers

1. In 2018, the US Bank National Association of Cincinnati, Ohio, (U.S. Bancorp) was fined $598 million. There were deficiencies in its AML program. To quote the experts, “systemic deficiencies in its transaction monitoring systems, which resulted in monitoring gaps…” It had among many deficiencies “outdated systems to conduct appropriate monitoring and due diligence.”
2. Similarly, we can also consider the example of UBS which was fined $15 million for weaknesses in its automated monitoring system that resulted in poor monitoring or less than thorough monitoring of wire transfers by FinCEN in 2018.
3. The worst single-day dip in the stock market happened on 16 March 2020, when the Dow Jones plunged by 2,997 points (earlier, on 9 March, there was a dramatic 2,014-point drop in the Dow Jones Index was followed by two more drops of 2,353 points on 12 March). This could have easily led to a seismic shock in the stock market, but a repeat of 2008 did not happen through the bullish phase of the stock market came to a halt.

In all the stories that have been mentioned above, we can observe a common thread, the regulators coming down heavy on banks and financial institutions for failing to meet the regulatory standards- and the chief culprit – an outdated and archaic mechanism that is unable to cope up the fluctuations in the market. When it comes to trading and stock market fluxes due to unforeseen circumstances, handling the spike in guideline violations, or emails can be tricky but with automation and a post-trade monitoring workflows that incorporate multiple levels of alerts, we can be

Today, as risk management teams are spending more than 10 % of the revenue on compliance adherence and regulatory announcements associated with fraud and Anti-Money Laundering (AML) have increased by more than 500% globally, there is increasing pressure to de-risk with automated and Artificial Intelligence and Rules-based solutions. And this is where a tool like Magic DeepSight TM comes in. A highly proficient rules-based data extraction platform that leverages technologies like artificial intelligence, and machine learning to provide massive (70% cost savings), exceptionally higher data accuracy, while streamlining your internal and regulatory transaction monitoring workflows and navigating the complex world of transaction monitoring with ease.

Automation, Rule-based, Process Standardization, and Data-Centricity – The Key Levers of Smarter Transaction Reporting

Automation is the key to keeping up to date and ensuring timely resolution of the alerts and triggers thereby saving time, money, and manpower and ensuring quality and standardization. Here’s how processes can be streamlined.

Magic FinServ raising the bar with DeepSight^TM

1. For comprehensive data transformation (and delivery), firms can count on Magic DeepSight™ for the delivery of results within a shorter span of time and from the widest range of data sources. DeepSight^TM aggregates data from different sources (websites). It trawls different websites and identifies the data (for example corporate actions) and downloads it. DeepSight TM extracts only the relevant information from the massive amount of information available, saving considerable time in comparison to manual work. Thereafter, data is reconciled with a static database. In the process, data is transformed – and a Golden Copy dataset for all static data related to the customer account and securities is created.
2. When it comes to process optimization, the capability of Magic DeepSight TM in bringing the required changes is immense. Process standardization, wherein a standard workflow is defined in sync with the business solution. The approach also involves defining a standard template and creating artifacts and documents for tracking and monitoring the regulatory workflow.
3. DeepSight^TM adopts a rules-based approach which makes the extraction of data more relevant. Business Rule engine implementation is another critical lever or pillar for streamlining transaction monitoring and reporting and ensuring transparency in pre- and post-trade and email reporting. For defining and implementing the business rules, the reference comes from the Regulatory Technical Standard (RTS), XML schema released by Regulatory Authority bodies such as the ESMA.
4. DeepSight^TM can be easily integrated with custom and industry platforms, so firms do not have to waste time figuring out how to do it. Lastly, a standard workflow for the Audit and Status report incorporation based on the feedback/acknowledgment received from the NCA enables another critical milestone – last-mile process optimization – without which the actual benefits of automation cannot be reaped.
5. Below is a pictorial depiction of how Magic FinServ enables compliance and transparency of post-trade and email transactional regulatory reporting business MiFD II, SFTR – data as per ESMA with a data- centric, automated, and rules-driven solution for one of our clients.

Regulatory Reporting Business Process

Case Study: Ensuring System Integration for Back Office Automation Rollout for our Client

One of our clients is involved in all the post-trade transaction regulatory reporting business (MiFID II, SFTR, email, etc.). All the post-trade transaction data must be per the regulatory body ESMA. ESMA provides guidelines on how an asset manager must send all post-trade information to regulatory bodies, for ensuring transparency of business in terms of email reporting, MiFID II reporting, SFTR, etc. We implemented a solution where we got the information (data) from the customer and mapped the data to the XML schema, which is provided by ESMA. Thereafter, all the information defined in XML schema is shared with the NCA, the regulatory body for validation. The body decides whether it is correct or not. If data is missing, they revert to asking for more information to ensure that the regulatory needs are met.

Conclusion: What is in it for you?

Magic FinServ is an apt partner in your automation journey. We can help firms leverage their automation plans related to transaction monitoring with our incisive approach to data and process optimization. Here is how we do it:

1. Understand the problem statement for filing transaction regulatory reporting
2. Comprehend why is it that the organizations are not able to file
   • Is it a data problem – incompleteness of data, or,
   • lack a standard process or,
   • firm lacks the ability to understand the regulatory process
3. Based on the inputs, we define a roadmap
4. Then either use automation tools or develop internal automation tools on one’s own for streamlining the transaction regulatory monitoring. The biggest advantage is that Magic FinServ brings the technology to automate some of the processes that are extremely time consuming. Our bespoke tool takes away the pain navigating complex transaction monitoring (internal and regulatory). DeepSight TM is purpose-built for the financial domain and can meet the strictest standards to ensure streamlined operations (monitoring and reporting).
   • As it integrates seamlessly with platforms both custom-made and industry-leading, it obliterates needless work and ensures smooth workflow across business applications; with the capability to scale up or down as per the need.
   • Magic Deepsight™ pre-configured exception-handling rules weeds out errors more proficiently than before.

For more information on how we can add more value to your transaction monitoring, with our solutions you can write to us mail@magicfinserv.com.