Looking for long-term advantages that will take your business ahead of the curve?  Creating growth and improving operations, regardless of current market performance, can be achieved through effective and targeted data analysis.  In our previous article, which you can read here, we introduced the idea that the data collected through compliance processes should be a focal point for analytics.  Today we’re going to look at how this can be achieved within some of the compliance processes for MiFID II and why investing in analytics results in improved ROI.

MiFID II only has a few pages documenting the communications recording and monitoring requirements but it proved controversial for companies to implement.  This was further hampered by GDPR which is expected to heavily scrutinise how companies collect, store and process personal data when it goes live in May.

Under MiFID II all conversations that relate to client orders, or dealing on own account that intend to or result in a transaction, must be recorded and monitored.  These records will need to be stored for a period of 5 years or up to 7 years where requested by the relevant authority.  This means that companies not only had to identify, in advance, all the communications that needed to be recorded, but how they would securely store this data.

This resulted in many smaller companies accepting the FCA directive that conversations can be documented through note-taking rather than call-recording software.  For larger companies, or those with high levels of transactions, call-recording software should be integrated with suitable data storage.  Any other mediums used to accept client orders, such as emails, SMS messaging or face-to-face meetings should also be documented in a central database.  The trick here is to get all of these records stored in one format or have a system capable of translating the different file types so all the data can be easily reviewed in one place.

Secondly, the directive requires companies to regularly monitor these records, but hasn’t specified any sample sizes or the frequency of reviews.  Implementing the monitoring and review portion of these requirements has been vague and ambiguous, leaving companies to figure out for themselves the best processes to meet their obligations.  Again, smaller companies are generally choosing to go down the route of manually reviewing and monitoring their recorded communications as it is seen as a cheaper solution.  However, this is not always the case when smaller companies generally mean less resources with more demand on their time.  On the other hand, we’ve seen that larger companies are more likely to reach for analytical software to fulfil this requirement and this is where we see real benefits achieved past the goal of being compliant.

So why is analytical software able to provide benefits to companies that result in improved growth and efficiencies?  There are multiple reasons, but the first and simplest is that analytical software enables companies to mine high volumes of data that they already hold.  It significantly reduces the number of man hours that are normally required to refine raw data while providing near real-time business insights.

The second reason is that analytical software, through the combination of NLP (Natural Language Processing) and machine learning, can be customised to your specific needs.  If you’re an FX broker and want an early indicator for increased demand of pounds to Russian rupees for example, analytical software can do this for you.  If you’re an investment advisor and want to find out how your clients feel about your services without resorting to surveys or requests for feedback, analytical software can produce the information you need.

NLP and machine learning technologies are a branch of AI (artificial intelligence) that can be taught to understand natural languages which in turn can be used to analyse all types of stored communication.  This technology can identify patterns across multiple files, or interpret emotional nuances within a communication record to determine whether a positive, negative or neutral interaction occurred.  Using these insights can help you realise an improved ROI on your compliance processes, by analysing the very data that is collected through these enforced initiatives.

Of course, it’s not as straight-forward as simply building or purchasing a piece of software.  You need to understand how to effectively analyse data for what’s important to the business, without drowning in a wave of useless information.  The different components of NLP such as topic, behaviour and sentiment identification can enable you to do this, and we’ll be talking about each of these in this series.  Stay tuned for our next post to learn all about topic identification and how to correctly target the data you need!


Synetec is an Agile solutions provider with expertise in diverse development technologies, such as Angular, the .Net Framework, SQL Server and other cloud friendly data stores. We are certified and have successfully delivered projects across different cloud technology stacks such as Microsoft Azure and AWS, delivering integration and development solutions since 2000.

We work with a number of the UK’s most respected financial institutions to deliver a range of innovative solutions. We have expertise in working with both established businesses as well as start-ups and extreme growth businesses.

Written by Natasha Walters

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