Dr Nathalie Aubry-Stacey - Head of Regulatory Affairs and Compliance
Many financial institutions are finding themselves in an ‘arms race for AI’ as financial companies recognise that further digital transformation can lead to significant compliance, and business, advantages. The pandemic shone a light on just how fast technology can evolve, as many employees shifted to remote work almost overnight. Organisations have witnessed a massive increase in their digital footprint, leading to data growth, and potential fragmentation, across a multitude of applications, devices, and locations. The insights AI can provide are highly dependent on the quality of the data ingested as well as its normalisation - key steps to the creation of a unique data lake. Custodia services are focused on the recording of all forms of communication including video and voice, as well as operational data, to provide a comprehensive view for compliance, that can be leveraged to deliver meaningful analytics.
A more unified view of data
One of the most consistent challenges to compliance remains: are we capturing all conversational data points in a compliant manner, from turret, fixed line and mobile to social media applications? Audit and compliance investigations require near real-time access to data. The challenge posed by remote working is set to stay. As far as the regulators are concerned, hybrid workers should not risk or compromise their organisation’s ability to follow rules, obligations, and auditable standards.
Regardless of the modality traders use, their basic regulatory obligations have not changed. For this reason, firms need to look beyond addressing compliance recording in a piecemeal approach and move toward solutions that facilitate holistic capture. By deploying Custodia CC1 service, organisations enable digital transformation through the ingestion of communication recordings from legacy recording platforms as well as cloud capture services. Financial institutions can adhere to compliance obligations according to Recital 144 in MiFID II, which summarises the regulatory need for communication recording.
‘Existing recordings of telephone conversations and data traffic records from investment firms and documenting the executions of transactions, as well as existing telephone and data traffic records from telecommunications operators constitute crucial, and sometimes the only, evidence to detect and prove the existence of market abuse as well as verify compliance by firms with investor protection’ (MiFID II, Recital 144).
Financial organisations need the ability to bring together larger volumes of data from ever more sources because of regulatory obligations, but also ensure return on investment to business heads. The need to form a unified data capture, ready for further analytics, for compliance as well as risk management needs.
The rise of data lakes
The regulatory obligation, to effectively ingest and store raw data has led to the emergence of data lakes as a viable way to pool data and get better visibility of what is happening across a company. A decade after the financial crisis, businesses are more aware of the value of a holistic perspective on risk. Having a more complete view of all the data, available in various company systems, could be the difference between being aware of market abuse issues and being blindsided by them. A clean data lake, kept as a source for AI, allows an organisation to leverage raw data and turn it into actionable tasks. The focus has shifted from discrete compliance solutions to how we can capture and mine audio files in storage – effectively transforming any video, voice or text interaction into a source of valuable data.
The financial industry produces enormous amounts of data, and is increasingly becoming a data-driven industry. In 2022, the amount invested by banks and large financial institutions into their data architecture has never been higher. Data and analytics budgets continue to increase, with Deloitte’s annual capital markets report indicating that 84% of surveyed institutions plan to make further investments into artificial intelligence, and 62% plan to spend more on advanced analytics. Data is key to building robust applications and software – creating opportunities for innovation, and unlocking competitive advantage within a business environment that’s becoming increasingly dependent on technology. Yet dark data, which organisations pay to store, but goes underutilised in decision-making, is now growing at a rate of 62% per year.
A data lake is a centralised place that allows an organisation to hold large quantities of raw data in its native format, structure and unstructured, at any scale. It is a source for creating and enabling reporting dashboards and visualisations, real-time analytics, and machine learning. Early ingestion of data is key to the data quality, and its raw state of the data means it can be repurposed into many diverse data sets, as needed by unanticipated analytics questions.
The importance of data integrity
Data lakes provide new options for self-service reporting, satisfying regulatory requirements, gathering a single source of reference data, and opening up data for new purposes. Data lakes are a useful repository for a whole range of data from different sources, which can be used to provide more accurate risk reporting, enhance compliance capabilities and insights. By combining data previously held in various silos using CC1 service, companies can get a more unified view of interactions and operations.
Financial services organisations are grappling with legacy technology and scalability challenges in their transition to the cloud and can often feel restricted what they can do with the data they have. It can be a challenge to replace critical legacy systems, which is why they persist. According to a recent survey, commissioned by InterSystems, 86% of business leaders at financial services companies aren’t confident that their data can be used for decision-making. The problem may stem from disconnected systems and data sources, with almost (98%) respondents saying that there are data and application silos within their organisation.
Yet financial organisations would like to have business intelligence, AI and machine learning from a unique platform, where their data already resides. This requires best-of-breed data storage capabilities that can run directly to their data lake. Capturing more and more information across every part of the organisation has led to a sprawl of data. AI is enabling financial businesses to rethink their business models, minimise and manage risks, improve operational efficiency, and reformulate their workplace strategies, and other tasks by leveraging global systems and data-driven insights.
Organisations should democratise data beyond technology departments and enable the wider compliance, and business, to glean insights directly. Data fragmentation should no longer be accepted in financial services, with businesses increasingly using analytics to inform decision-making on anything from compliance to customer experience. It is imperative that every business unit realises the value of a unified view of data.
Cloud-native solutions like data lakes take on great importance by providing a centralised repository for businesses to collect and store data of any scale and format. When managed correctly, such data stores promise to help create a consolidated, single source of data truth, making it easier to govern, manage and transform into an analytics-ready state.
Custodia aims to simplify compliance efforts in this new environment by providing a transversal visibility and control sitting directly above any existing and new technology systems organisations employees use, on premises or at home. CC1 service provides tamper-resistant and permanent digital records to ensure conformity with financial regulatory obligations.
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