Compliance in financial services shouldn’t just be about buying technology in order to tick a box for the FCA and ‘be’ compliant.
The focus for many firms that we work with is to ensure that they fully understand their business and the market they operate in and put in place the correct policies and levels of assurance that are required to be proactively compliant and supplement with the best of breed technology.
The most forward-thinking businesses are those that are focusing their efforts on improving the use of ‘business intelligence’ and ‘big data’ and how these can enable better compliance. At the same time, this increased focus on intelligence can lead to improved business performance as well as compliance, the two do not need to be mutually exclusive.
Compliance, as has been seen in many industries, often drives innovation, and MiFID II is no exception. Many technology company’s products that have been designed to enable a firm to be compliant, such as call recording, are expanding their reach in order to supply accessible and readable data that firms can utilise, analyse and make work for them.
Business units are now becoming more aware of the volumes of data they generate and the value that is potentially stored within it and have the opportunity to put that data to use. Tools are available to interrogate data sets to understand trends and patterns in order to set the correct policies and procedures for better compliance. This interrogation, or analysis, can help to reduce organisational risk and exposure in certain markets.
In the current climate, financial service companies are required to capture and retain all communications data generated during a financial transaction and be able to reconstruct the transaction across all channels, be it a commodity trade, a mortgage application or FOREX transaction.
Under MiFID II firms will be required to monitor and examine this data for market abuse and product governance and understand the sentiment of client interaction. This increased engagement with communications data gives firms the power to improve business performance by understanding their client interactions better and look to improve client engagement.
Through transcription services voice calls can now be turned into text files and combined with meta data from all unified comms channels to form a single communications data set across a business.
Synetec is working with organisations to understand how this meta data can be turned into business intelligence. Through the creation of APIs, Synetec are able to ingest this data into a proprietary analytics engine called…(sorry, still TOP SECRET)…and through the use of Natural Language Processing and Machine Learning protocols can analyse it in accordance to each individual organisations specific assurance processes and risk parameters to provide real-time intelligence.
This BI will ensure that compliance is not just a tick-box exercise for the regulator, but also a way to proactively manage compliance and generate real time data that can be utilised by the business to drive smart decisions.
Specifically, clients will be able to use the base line functionality of the engine to monitor and analyse client interactions to understand the presence or absence of key words and phrases, such as disclaimers linked to a sale that has been made. This data will be generated in near real-time and procedures can be amended if it is deemed that there is a current compliance risk
In the upper levels of the engine the client will have the capability to program the system to map and report on the frequency over time of certain words/phrases in accordance with business critical incidents. For example, an FX trader may see higher than average usage of the words ‘yen’ and ‘dollar’ without an obvious external reason then the organisation is able to undertake high level investigations to ensure that there is no untoward activity. At the same time, the investigation may well uncover the fact that the business would need to increase their spread to account for the most probable requirement to increase margin as the spike in communications may signal a future increase in transactions.
At the top level of the engine clients will be able to run sentiment analysis, specifically the correlation of content, sentiment and sequence of critical incidents. For example, insurance claims can be analysed in order to ensure that product governance had been adhered too during the sale of a product and also able to detect irregularities that may indicate fraudulent claim activity.