MiFID II’s unnatural data acts explained

We were pleased to speak at the Asset Control User Conference on Tuesday about the challenges of using RegTech in the context of comprehensive MiFID II data requirements.  JWG’s CEO, PJ Di Giammarino, presented a helicopter view of the regulatory landscape ahead of us, an approach to getting the cost of the data under control.

MiFID II is just one of a plethora of regulations engulfing the financial ecosystem right now.  We are well into the implementation wave of the post-crisis reform agenda, with MAD/MAR going live in July and the PRIIPs KID, GDPR and US Volcker rule all reaching implementation dates next year.  Despite the recently announced delay, MiFID II is a beast in and of itself, and requires preparation now for its January 2018 start.

Some of the MiFID II requirements will be particularly onerous in their demand for data because of their increased scope, limited exemptions and greater focus on quantitative criteria to prove compliance.  The revamped best execution requirements, for example, require a firm to go far beyond just having a best execution policy in place (as required under MiFID 1) and specific data must now be reported to clients about how the obligations were met – a big challenge for many legacy infrastructures.

Using our RegDelta modelling, we reviewed another MiFID II data requirement for algorithmic trading, which is also comprehensive and more invasive than ever before.  Algorithms will need to be tested before their use and then continually monitored to prevent market manipulation.  This obligation builds on MAD/MAR, which require policies to detect market manipulation at the earliest stage possible.  The real-time monitoring infrastructure and underlying data framework used to meet these obligations could also be used to comply with the best execution policies mentioned above.

Rising demand from the regulators will inevitably lead to new challenges in unifying a view across legacy systems – data privacy concerns being one example.  It is important to develop a data strategy that keeps compliance costs under control and minimises the change efforts – both internally and for third party vendors.  Being able to spot your regulatory deltas early is critical and data managers are advised to actively engage in the gap identification and help develop a holistic view of the data challenges.

As one speaker pointed out, regulation is an emotive subject.  Authorities are demanding so much change to the way business is conducted that firms, regulators and their supply chain will be funding the development of a new RegTherapy industry.  Stay tuned as we commission some research on what that is likely to entail …

Regardless of how many sofas are filled in 2017, it is clear that many new relationships – to be formed via the unnatural act of collaboration – will be crucial if the market is to get itself in line, in time and at a reasonable price point.

We advocate using the wisdom of the crowd to source expert interpretations of what the obligation is asking for.  As our MiFID Implementation Group (MIG) has proven, facing the challenges as a herd is far safer than going it alone.  Whatever your sector or niche, you need to find like-minded individuals that speak your language.

Of course, finding a common industry method for spotting the upcoming changes, noting the interdependencies with other regulations and mapping the requirements onto the business operating model, is not easy.  Established standard languages, such as FIBO (Financial Industry Business Ontology), will play a role in facilitating the development of a regulatory dictionary for the financial services industry and translators will be needed for local and regional language differences in regulatory terminology.  If rule changes can be aggregated to a semantic level that everyone can access and understand, this ‘one version of the truth’ could save vital time and resources for all those under pressure.  As we referred to in an earlier article, breaking through the stalemate of inaction is the first step in bringing RegTech to market.

Standards and regulatory engagement will also be imperative in facilitating this change and, here, work is already underway.  In our recent RegTech roundtable with the FCA, which 18 banks attended, there was a lot of progressive discussion about how to prioritise an industrial approach to RegTech development, and the answer was a unanimous consensus – data (or the increasing demand of it) is causing the biggest headache.  The solution called for was, just as has been described above, a common reference model for regulation that regulators, firms and technologists alike could use to identify the obligations in an understandable, universal language.  We call this a robo-rulebook.

On this subject, PJ has been quoted recently by Thomson Reuters as saying “the one big thing that’s on everyone’s mind is how to alleviate the reporting pain.  The answer lies in linking the data standards back to an electronic rulebook.  A smart rulebook would integrate the many regulatory obligations into a single source which could be accessed by regulators and the industry at large.

Smart means far more than a collection of static pdfs.  To enable access to the right rules, meta-data – the data about the rules – is required so that basic questions can be answered in a commonly understood way.  For example, the market could answer questions like ‘what goes in that currency field for a Euro/Dollar swap and how is it formatted?’ in a better, faster, cheaper manner with a ‘robo-rulebook’,” he added.

At the end of the day, the industry and its regulators are going to need to swim together to sort it out.

To keep up to date with all of the latest MiFID II developments, join our MiFID II LinkedIn discussion group here.

mifidiidataimpacts

 

NO COMMENTS

LEAVE A REPLY