UK-based financial institutions have been subjected to increased regulatory scrutiny as the FSA now requires them to record and archive all SMS and voice communications. Paul Metcalfe explains how this requirement has exacerbated firms' Big Data challenges.
With the recent introduction of recording for voice and SMS on mobile phones for trading activities in the UK, introduced by the Financial Services Authority on November 14 last year, technologists have raised the issue of Big Data, as additional voice recording requirements contribute to the growing repository of data being held by their firms to meet regulatory requirements. Although regulators around the globe are driving for greater visibility and a more comprehensive record of past trading activities, this additional data can also serve a purpose in other areas such as dispute resolution.
With Big Data, technologists share the concern that they appear to be facing a rapidly increasing need to hold more data. This is not only a challenge in respect to volume, but also diversity. Trading communication now takes many forms ─ voice, IM and SMS as well as factoring in social networks, email and other systems related data (i.e. electronic payments or transaction messaging). This could be further impacted by the possibility of holding additional data sources such as video from video conferencing along with information that may have influenced or could contextualize the communication being recorded (i.e. news feeds or streaming).
The expectation is that regulators will push for this broader range of data types to be held for far longer periods than before, with current averages in the range of three to six months moving closer to three to five years (as seen in Dodd-Frank and Mifid II proposals). Planning ahead for storage requirements is also a challenge, as volume and diversity of data is often affected by increased activity in the markets, which is hard to foresee, along with the seasonality of specific market activities. The main concern is that existing data technologies and infrastructures could soon reach their limits of scalability and performance.
Outside of volume and diversity, the subsequent challenge of processing the required analysis and interrogation of the data is a worry. Obviously, the turnaround of requests (speed of processing) will be key, as well as being transparent to the geographic locations of data and the requesting user. In this area, we are now starting to see the inclusion of voice, along with a wider set of communication data, in the deployment of data analytics engines. The most advanced of these engines are being required to provide the ability to slice and dice this diverse and generally unstructured data by specific search criteria (i.e. all activities of a trader or desk within a time window) or key values (i.e. specific counterparty, particular word or trigger event).
So how can these data and analytics hurdles be approached? In today's cloud-based technology "as-a-service" world, we are seeing institutions seriously considering specialist service suppliers to provide flexible data storage solutions that are fully scalable. Although this was not a strategy that was immediately accepted for critical applications, due to uncertainty on the risks in security and reliability, the general concept of outsourcing key infrastructure (data storage) along with highly proprietary and confidential data is now gaining acceptance. With a growing base of customers building a track record in the market, this acceptance can only gain momentum. Additionally, at least for the larger firms, the option also exists to deploy their own private clouds as an alternative.
With Big Data, technologists share the concern that they appear to be facing a rapidly increasing need to hold more data. This is not only a challenge in respect to volume, but also diversity.
Most of the larger firms already have programs and proof-of-concepts for the advanced data analytics tools in place. However, many of these will need to be expanded to a wider selection of compliance data (i.e. voice, SMS) which in turn needs further investment. For most of the remaining medium-small sized firms, there is the cost of entry and subsequent understanding of the tangible benefits to justify such a move. This is particularly difficult when the need for these firms to conduct such analysis is not a regular requirement and could probably be dealt with manually on a case-by-case basis, but with a rapidly growing data repository it is not sure how long this would be feasible with a quick enough turnaround.
Once again the concept of analytics "as-a-service" could be a way forward and some of the tools are available on this basis today. Although we have not reached a point where a firm can easily buy analytics over their data for specific investigations or analysis on demand (i.e. pay-as-you-go), this concept is reasonably easy to understand and appears more accessible to a wider range of budgets. An infrequent need to perform such analysis, however, means format and availability of data would need to follow some general standards, which may not be as straight forward, especially with legacy data.
Overall, this is a situation that is still developing, where the larger the firm the quicker the issue of Big Data could become a reality. As alternatives to internal technology infrastructure reviews and potential investment, there appears to be potential outsourcing and as-a-service options. However, timing could be an issue here as these solutions are still relatively new and need to allay concerns, especially with the cautious and risk adverse solution teams within firms. As a trader, voice challenges around recording requirement for compliance go beyond the previous areas of expertise of the telecommunication specialists, and clearly demonstrates the impact technology convergence already has in this sector, where lines are far more blurred between technologies deployed and managed across the trade floors.
Paul Metcalfe is head of voice trading solutions at Orange Business Services - Trading Solutions.
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