Trade Reconstruction Requirements: What are they?

Trade Reconstruction Requirements: What are they?

With regulation requirements mounting across the capital market landscape, it is easy to get confused as to what is relevant to your firm. When it comes to trade reconstruction requirements, the SEC’s Dodd-Frank Act of 2010 and the European Union’s MiFiD II of 2018 constitute the two leading regulatory mandates for firms trading in swaps – the agreement between two parties to exchange sequences of cash flows for a set period of time 

Here at VoxSmart we have broken down these requirements in simple English, no frills just facts! Don’t get left behind when it comes to safeguarding against hefty penalties. 

AMAR – Dodd-Frank Act 

The Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010, brought in under the Obama administration dictates that firms dealing in swap products must, within 72 hours of request, produce a time sequenced reconstruction of swap trades. This spans the pre-trade communications to the swap expiration stages.  

As mentioned, this requirement impacts all swap products, and requires records of the trade to be store for the duration of the swap plus five additional years thereafter. Furthermore, non-transactional records including oral and written communication must be stored for five years.  

This act was brought in to enhance the CFTC’s regulatory authority to oversee the more than $400 trillion swaps market, putting an end to the institutions deemed “too-big-to-fail” and prevent another financial crisis.  

Some of the key components of the Dodd Frank Act include the Financial Stability Oversight Council (FSOC), the Volker Rule to restrict certain investment strategies, the Consumer Financial Protection Bureau to prevent predatory mortgage lending, the SEC Office of credit ratings and a whistleblowing scheme. Arguably one of the most resource intensive rules was Title VII, which imposed new registration requirements and increased reporting requirements, granting the CFTC authority over swaps, apart from security-based swaps, which are regulated by the SEC. 

EMEA – MiFiD II 

MiFID II entered into force on 3 January 2018 and was established to strengthen investor protection and improve the functioning of financial markets making them more efficient, resilient and transparent. 

In a similar vein to the Dodd-Frank Act, MiFiD II requires firms to accurately reconstruct the lifecycle of a trade including all services, activities and transactions. This regulation encompasses all OTC products in addition to exchange traded products. Communication records must be stored for five years, and in some cases as long as seven years, on a tamperproof storage medium that is searchable.  

Although there is no given timeframe for submission of audit request, however, records should be readily accessible based on the type of transaction involved.  

APAC  

Currently there is no specific regulation for APAC regions that requires the reconstruction of trades however, if a firm has a US/EU nexus then this will automatically bring a firm under the regulatory requirements of these regions. Therefore, should an audit be called by the CFTC or ESMA firms within the region must be able to provide trade reconstructions or risk financial penalty and reputational damage.  

With regulation requirements within the region edging towards alignment with US or European standards, firms adopting to an automated trade reconstruction system are better positioned for future regulatory requirements in addition to safeguarding against potential audits under Dodd-Frank Act or MiFiD II.  

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VoxSmart’s award-winning Trade Reconstruction solution not only provides firms with the security of being regulator ready but also equips them with a powerful analysis resource, bespoke and tailored to their specific needs.  

Get in touch with a member of our team today to learn how our Automate Trade Reconstruction solution can help your firm today!

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    How can Natural Language Processing be used in Capital Markets [with examples]

    How can Natural Language Processing be used in Capital Markets [with examples]

    Natural Language Processing (NLP), although not a new concept, is increasingly being discussed within Financial Markets. Despite its tenure in everyday services such as chat boxes, Alexa and Hey Google amongst others, the way in which it is being utilised in financial markets is changing for the better with firms set to reap valuable rewards from its early adoption.  

    In this blog we take a look at how different sectors within capital markets are utilising NLP technology having established in our previous blog – What is Natural Language Processing and how does it work?

    Why is NLP needed in capital markets?  

    Trading floors are a noisy environment, even on today’s evermore technologically advanced trading desks. Traders and sales teams have to manually decipher information through many different communication channels in both text and audio formats however, with the vast quantity of data in circulation and the volatility of this information, opportunities are being missed.  

    Furthermore, financial and trading conversations are awash with industry specific jargon. Traditional speech recognition devices without in-depth and thorough training have a difficult time in making sense of such language and often fails to adequately interpret the true meaning of such speech. This can be seen cause further delays with manual input and review necessary, with traders missing crucial insights from their data. 

    Here are just some of the examples of where NLP is used in the financial sector: 

    Big Banks – Deal Opportunity Detection 

    Big banks in an effort to leverage the data collected need to be engaging an NLP platform as to detect deal opportunities, and flag missed opportunities, through speech analytics. Furthermore, NLP enables the front office to identify profit and loss spikes increases revenue opportunities and other insights into how traders are selling with reports gleamed from communication data.  

    As CEO and ex-fixed income trader, Oliver Blower in an interview with RegTech 100 stated; “On an average trading floor and an average day, a trader or salesperson is missing more opportunities than they capture”. In order to combat this issue an intuitive NLP platform is needed to bring order to the chaos. 

    By utilising NLP to better understand the nature and quality of trading relationships, not only will this help analysts to understand the pricing efficiency of market makers but also assess which relationships add the most value to a market. This serves to reduce operational costs as well as optimise and focus sales relationships at different levels.    

    Trading desks – A source of Indicative Pricing 

     With the volatility and speed of such markets, failing to capture real-time prices automatically puts dealers on the back foot when it comes to securing the best price for customers.  

    In tackling this issue NLP serves to automate pricing, by feeding pricing engines with real-time pricing information taken from live communications. Through this indicative pricing feature, traders are ensuring the best prices for clients whilst boosting revenue through increased speed of trade.  

    What’s more, NLP enhances overall trading floor efficiency by streamlining the order entry process for traders. Currently this is a manual task and falls to the responsibility of each trader to input within a limited timeframe under regulation (MiFID II).  In this was do we see NLP to provide traders with additional trading time, subsequently optimizing profits.   

    Asset Managers – Sentiment and Intent Analysis 

    Many Buy Side firms are increasingly coming up against a vast amount of research to be undertaken in order to glean insights from analysts’ documents regarding earnings estimates. While it may take some time for analysts to update numerical forecasts, parsing text reports using NLP to reveal sentiments and intent enables managers to capture a picture of firms’ overall position in the absence of standard numerical estimates.   

    Additionally in terms of due diligence, NLP provides firms with the opportunity to streamline client screening processes by scanning a profile to identify whether a client meets the pre-defined criteria. 

     

    NLP is diverse and adaptable to specific industry needs, tailored to solve industry needs from universal to niche. The benefits to be ascertained make its adoption a no brainer with incalculable possibilities.  

    Interesting in finding out how NLP can help your business? Get in touch with a member of our team today here! 

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      What is Natural Language Processing and how does it work?

      What is Natural Language Processing and how does it work?

      With the global Natural Language Processing (NLP) market expected to reach USD 44.96 Billion by 2028, according to a report by Reports and Data, there has never been a better time to understand how such a technology works in accurately comprehending human speech.  

      The commercial and operational benefits of adopting NLP technology are increasingly apparent as businesses have more and more access and visibility across their unstructured data streams. Firms who adopt early are positioning themselves as market leaders, with the benefits gleaned from trading insights pivotal in gaining a competitive advantage.  

      Here we break down how NLP works to uncover these invaluable market insights.  

      What is NLP?   

      Put simply, NLP is a technology used to help computers understand human language. The technology is a branch of Artificial Intelligence (AI) and focuses on making sense of unstructured data such as audio files or electronic communications. Meaning is extracted by breaking the language into words, deriving context from the relationship between words and structuring this data to convert to usable insights for a business.   

      How NLP works. 

      In our everyday lives we may use NLP technology unknowingly - Siri, Alexa and Hey Google are all examples in addition to chatbots which filter our requests. In this way we can interpret the technology as the bridge between computers and humans in real time, streamlining business operations and processes to increase overall productivity.  

      NLP techniques rely on Deep Learning and algorithms to interpret and understand human languages and, in some cases, predict a human’s intention and purpose. Deep Learning models ingest unstructured data such as voice and text and convert this information to structured and useable data insights. The technology extracts meaning by breaking the language into words and deriving context from the relationship between these words. In this way do we use NLP to index data and segment data into a specific group or class with a high degree of accuracy. These segments can include sentiment, intent, and pricing information among others. 

      NLP Algorithms Index and Segment data 

      The indexing process can be further broken down into stages.  

      1) Tokenization – whereby the text is broken down into semantic units or single clauses,  

      2) Stop word removal – removing words that add no unique information, e.g., prepositions and articles,  

      3) Stemming/lemmatization - transforming words to their root form and assess context of word use. 

      4) Part of Speech Tagging - words are tagged according to grammatical case.  

      NLP models identify sentiment, intent, and entities. 

      Algorithms can be formed in two ways to drive the NLP training model. Following a rule-based approach, algorithms are created by linguistic engineers and follow manually crafted grammatical rules. However, a faster and more powerful approach is in Machine Learning (ML) algorithms whereby learning models are based on analytical and statistical methods and require a degree of training which concurrently learns from the examples introduced.     

      From this training, associations between words are recognised, which feeds into the machine knowledge bank in order to ascertain the motive of the text, providing firms with key data insights which enhances business opportunity. Furthermore, the greater the training, the vaster the knowledge bank which generates more accurate and intuitive prediction reducing the number of false positives presented.  

      With VoxSmart’s NLP solution, firms are fully in control of the training of these models, ensuring the outputs are tailored and specific to the needs of the organisations with the technology rolled out on-premise. This not only puts the firm in the driving seat but also reduces concerns regarding data ownership, with the firm having full authority over their data. 

       

      Although few may work directly with the inner workings of NLP, the benefits across a firm are testament to its ingenuity and innovation throughout capital markets and regulated industries. VoxSmart’s scalable NLP solution is attuned to the specific needs of our clients, with training models tailored to a firm’s requirements.  

      Interested in learning more on VoxSmart’s NLP solution can help your business? Get in touch with us today here! 

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        Graduate Blog Series: Global Operations Assistant Edition.

        Graduate Blog Series: Global Operations Assistant Edition.

        Part three of our Graduate Blog Series shines the spotlight on Holly Anderson our Global Operations Assistant. Having started her career with VoxSmart in London, the kiwi native, has in recent months return to New Zealand to continue her role as part of the team in our recently established Queenstown office.  

        Having graduated in 2019 with a degree in Business Management from University of Queensland Australia, Holly joined the VoxSmart team.

        Hear what she has to say about her experience below! 

        Name: Holly Anderson 

        Age: 23 

        Degree: Marketing – Business Management  

        Role: Global Operations Assistant  

        Tell us about your role as part of the team at VoxSmart:  

        In October of last year I relocated back to New Zealand and was lucky enough to become a member of the VoxSmart NZ office. I assist the operations and HR duties of the APAC and Americas region, as well as office management and recruitment for the area. Working within the People and Performance team, we help to ensure a smooth onboarding for all new employees, so they’re fully equipped with everything they need to know on their first day. 

        What do you enjoy most about working at VoxSmart? 

        My favourite thing about VoxSmart is the culture. Each department in the company works closely together which means you feel well supported. The fact we now have offices dotted around the globe does not make contacting one another more challenging – everyone is just a Teams message away and more than happy to help.  

        What did you find the most challenging on entry into your role? 

        Because we are a communication surveillance company, the most challenging thing for me was wrapping my head around the basics; what our products are and how they work. I didn’t have any background in the financial services industry, so it was slightly daunting starting with such little knowledge. Over time you begin to understand and slowly things fall into place.  

        How has VoxSmart supported your personal development so far? 

        VoxSmart has given me so many unexpected opportunities which I do not believe would have been possible in other jobs. These experiences have given me freedom to navigate and develop my skillset through a range of different avenues. Being supported by the senior management team as well as your line manager is massively reassuring too. 

        Why did you choose to start your career with VoxSmart and what would be your advice to someone considering applying for a role? 

        In some ways you make your own luck, but I was fortunate enough to be offered a role which I didn’t have the skillset for initially. I began in the Client Services team in a support role. I found it fairly intimidating to begin with but being thrown in the deep end meant I was forced to work hard and looking back, meant I grew a quicker understanding of the products and how they work. 

        My advice would be to research the industry, expect to be involved with a very collaborative and involved team and know that someone is always willing to lend a hand or answer any question. 

        What do you most look forward to as part of the role? 

        Everything is fast paced, and the target is constantly moving so it’s pretty exciting. One day to the next could be totally different, especially now because we are expanding quickly and globally. It will be really interesting to see what this next year brings. 

        What is life like at VoxSmart? 

        Even though it is always busy, there is a relaxed and easy going feel – we all seem to be on the same page. Everyone is enthusiastic, dedicated and have the most positive can-do attitudes so it keeps you feeling motivated all the time. It is definitely not boring that’s for sure. 

        Sum up your experience so far in three words. 

        Rewarding, exciting and challenging. 

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        At VoxSmart we seek to enable our employees to work in a way that suits their lifestyle, whether from Madrid, New York or any location across the globe. A mobile workforce only makes us stronger!  

        VoxSmart are always looking for new talent to join our team, taking our vision to the next level. Check out our available positions here!  

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        The Fear Index shines light on role of market makers in pricing efficiency.

        The Fear Index shines light on role of market makers in pricing efficiency.

        When it comes to trading floors, Sky/NowTV’s recent addition, The Fear Index, has highlighted the crucial role of market makers in creating pricing efficiency. Yet in recent years trading desks world-wide have started to benefit from electronic market making, bringing with it increased speed and ease for traders to buy and sell. 

        In a recent article published by The Trade, VoxSmart CEO, Oliver Blower shares his thoughts regarding the importance of understanding the pricing efficiency electronic market makers bring to the industry.  

        Despite questions of whether an electronic system presents a level playing field for traders, our CEO highlights the opportunities such a technology extends to traders. He argues computer driven market makers actually make it easier for investors and traders to buy and sell with more granular trade insights gleamed through in-depth reports, derived from communications data.  

        Read the article in full here 

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        Graduate Blog Series: AI Engineer Edition

        Graduate Blog Series: AI Engineer Edition

        Part two of VoxSmart’s Graduate Blog Series and what better way to continue the series than from the perspective of recent female graduate working within the industry! Natalia Madrueño Sierro has been part of the team here at VoxSmart since October 2021, having completed her Master’s Degree in Data Science in September (and currently in the process of completing her 2nd in Decision Intelligence Engineering!).  

        Women, unfortunately, in the field of AI remain sparse on the ground with a 2020 World Economic Forum report finding them to make up only 26 percent of data and AI positions in the workforce. A stark disparity.  

        Find out more about more about Natalia and her VoxSmart journey so far below  

        Name: Natalia Madrueño Sierro 

        Age: 24 

        Degree: Math and Software Engineering 

        Role: AI Engineer 

        Tell us about your role as part of the team at VoxSmart 

        I am currently working in the Speech & AI Team. So there’s a lot of data science projects on the go!  

        What do you enjoy most about working at VoxSmart? 

        It’s great to work with such awesome and friendly teammates. Everyday there’s something new to be learned so it’s rarely boring!  

        What did you find the most challenging on entry into your role? 

        I think with any job getting to know the company and how things are done is a challenge, but it’s normal. Everyone is very friendly and accommodating so it makes the process a lot easier.  

        How has VoxSmart supported your personal development so far? 

        Like I previously mentioned there’s new things to be learned every day at VoxSmart, so in that sense learning and personal development are very much encouraged throughout the company.  

        Why did you choose to start your career with VoxSmart and what would be your advice to someone considering applying for a role? 

        I had heard good things about VoxSmart from a colleague at another company, so it really stood out for me. There’s some really exciting technology and opportunities to explore different areas of data science and AI, so it’s a company very much at the cutting-edge of innovation.  

        My advice, at least from the perspective of my role, I would be that you have to have a thirst for knowledge, from every aspect of Data Science (from pure software engineering to pure mathematics). In that way there’s a lot of diversity in the work that I do daily.  

        What do most look forward to as part of the role? 

        Developing awesome Data Science projects to enhance the overall VoxSmart product offering!  

        What is life like at VoxSmart? 

        The company culture here at VoxSmart is great! Everyone is really friendly and even on the busiest of days you have that support network so there’s that team spirit.  

        Sum up your experience so far in three words. 

        Great work environment. 

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        VoxSmart are proud to be an equal rights employer, who support and encourage employees to grow and develop with the company. It is great to have Natalia onboard the AI team here at VoxSmart and we wish her continued success in the role.  

        VoxSmart are always looking for new talent to join our team, taking our vision to the next level. Check out our available positions here! 

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