A-Team Insight Blogs

This year’s London Data Management Summit was a resounding success, answering the questions of hundreds of market participants working to transform, digitalise and innovate their approach to data management and drive value out of data. It touched on technologies from knowledge graphs to data standards that can help users achieve these goals, and provided actionable insight on cultural issues including data ethics and diversity in the workplace.

Andrew Delaney, chief content officer at A-Team Group hosted the Summit, which started with an inspirational practitioner innovation keynote from Peter Jackson, director, group data sciences at Legal & General.

Practitioner innovation keynote

Jackson discussed how to drive insight, value and disruption out of data, describing the data driven business transformation he is leading at Legal & General. This includes a data strategy and a story that appeals to 80-100% of each business in the wider organisation. The aim is to provide better, leaner and faster operations to increase the speed of decision making; focus on customer experience; take a left-turn towards disruption; implement innovation; and ensure high quality data for regulatory compliance.

He acknowledged the need to deliver value quickly to keep everybody listening and provided tips on how to achieve a dynamic data driven transformation. These included starting with a data maturity assessment, deciding on how to scale transformation, implementing metrics around issues such as cost reduction and customer churn, setting up for success by making sure of board buy-in, and creating a vision of the end state of the transformation – that will only be met by winning hearts and minds across the organisation.

Buy-side keynote

The Summit’s second keynote was presented by Giles Nelson, chief technology officer at MarkLogic. He considered the challenges buy-side firms face, particularly a rise in investment fund flows into passive funds, the need to change how alpha is generated, and an increase in regulation including not only Markets in Financial Instruments Directive II (MiFID II), but also a further 500-plus pieces of new or adapted regulation that must be dealt with by the end of 2021.

These challenges, he said, can be tackled by taking a data-driven approach to transforming products, operations and the firms themselves. Expanding this view, he outlined case studies of buy-side firms taking a data-first approach to transformation and the outcomes they are achieving, including a 360 degree customer view, improved decision making, extended market reach and more agile operations.

Data management keynote

Peter Moss, CEO of the SmartStream RDU, presented a third keynote questioning why data management is so difficult. He said the financial industry spends $28.5 billion on externally sourced market data and a further $2-3 billion cleaning it up so that it can be used internally.

He suggested that in a market where products are defined by data and traded using data mechanisms, the data should be standardised – but this is not the case due to factors such as differences in securities identifiers, data attributes represented differently across data sources, problems with classification, and a mix of identifiers for market participants. Considering the difficulty of maintaining data that is required across an organisation and that data standards are not precise enough in an environment where data comes from a huge number of sources, Moss called for industry cooperation to improve and implement more effective data standards.

Data ethics keynote

Lorraine Waters, chief data officer, financial crime risk at HSBC, presented the final keynote of the Summit, discussing the emergence of data ethics at financial firms following the focus on data privacy required by General Data Protection Regulation (GDPR) compliance and the arrival of artificial intelligence (AI) applications in the workplace.

She explained how HSBC has built a framework for data ethics that draws on her experience in data governance and data strategy, and commented on the importance of buy-in from the board. The framework is built on seven practical and applicable, useful and reusable principles that are shared with data management practitioners. The principles cover consistency with HSBC values, data privacy, clearly defined purposes of data use, unfair bias and decision making, responsibility for AI, adaptable data governance and ongoing development of best practice.

Panel discussions

The Summit included a number of interactive and thought provoking panel sessions moderated by industry experts and joined by data management practitioners and selected vendors.

An opening user panel discussed the ‘new world of data’, noting the huge potential of data gathered by financial firms, but the need to implement controls, engage stakeholders, hire data scientists, and ensure a strong data foundation before attempting to build value. Backing up these sentiments, a panel on preparing data for business benefits and another on building smart analytics agreed that getting the data foundation right is a critical first step.

A lively panel on data lineage discussed how to make the business case, where to draw the line between business and technical lineage, regulatory requirements for data lineage, the challenges of automation, and best practice implementation. While data lineage is a hot topic and complex task, the panel agreed that the best approach is to keep it simple, start small and ensure data ownership.

Moving in to the afternoon, the Summit diverged to address both ends of the spectrum of capital markets technology – the necessities of managing regulation, reporting and risk, and the mechanics of building data science capability.

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