TECHNOLOGY: DATA ANALYTICS A


ccording to European Commission statistics, the value of the data economy in its 27 EU countries,


together with that of the UK, will exceed €550bn by 2025.1


The European Commission


defines the data economy as representing the overall impacts of the data market on the economy as a whole. It involves the generation, collection, storage, processing, distribution, analysis, elaboration, delivery and exploitation of data enabled by digital technologies.


What does this mean for corporate and business financial services provision? In short, the winners will be those with the best analytic competencies backed by strong data quality. Organisations are becoming more data-centric, rather than application- or process-centric, as they increasingly rely on data for decision-making.


Four years ago, McKinsey noted that the majority of the world’s largest banks were employing advanced analytics. According to McKinsey, “more than 90% of the top 50 banks around the world are using advanced analytics. Most are having one-off successes but can’t scale up. Nonetheless, some leaders are emerging”.2


This article


charts Deutsche Bank’s progress. Regulatory drivers


Inefficient technology architecture, multiple sources of data, inconsistent taxonomies, numerous data formats, disparate processes, lack of golden source reference data adoption and insufficient data ownership are common root causes of data quality issues.


Fines from regulators will often have their origins in incorrect and inaccurate reporting – successive acquisitions bring with them incoming data sets that create difficulties when the acquired business becomes part of a larger enterprise. Problems have typically arisen from data truncations, lack of completeness, mapping issues and varying data quality.


The other driving force behind improved data frameworks comes from regulatory requirements such as Payment Services Directive 2 (PSD2),3


information. The other issue is that while good data sets can be used to drive strategic insights for clients, they must be used with awareness and controls for public and private side separation, and for potential conflicts of interest. Artificial intelligence applications and ethical implications must also be controlled.


From a prudential regulatory perspective, the Basel Committee on Banking Supervision’s 14 ‘Principles for effective risk data aggregation and risk reporting’ (BCBS 239)5


the analytics and value that help customers – is not easy, but it is something that is shaping the new competitive landscape (see Figure 1 on page 86).


is a framework that is actively


used to assess firms’ approach to data quality. Regulators review firms’ approach with an eye on accuracy, completeness and timeliness. These are considered to be ‘hard’ checks, in that they can be defined by metrics.


Rethinking data management As the flow article ‘Tomorrow’s technology today’6


explains, Deutsche Bank created


a new Technology, Data and Innovation division in October 2019 to get the technology transformation process under way, with the aim of reducing administration overheads, taking further ownership of processes previously outsourced, and building in-house engineering expertise. Its mission is to “provide and use the right common data, skills and tools for everyone to make decisions and enable innovative solutions that create value for clients and the bank”.


What does this look like when done well? Finding the balance between security and stability – coupled with the agility to deliver


The Chief Data Office works closely with Deutsche Bank Corporate Bank’s data office (Deutsche Bank Investment Bank and Deutsche Bank Private Bank also have their own data offices) to ensure that everything touching a client (data, cash, digital platforms and reporting) is secure, intuitive and sustainable. But by having a remit across the bank, the Chief Data Office ensures consistency between the offices in key areas, including establishing principles, policies and standards that need to apply across the enterprise.


which stipulates that


payment service providers must have a robust framework and structure within the data that satisfies new use cases. And to comply with the General Data Protection Regulation,4


financial services providers


have needed a much more granular grasp of specific sets of personal and private


Visit us at flow.db.com


Data is a living, breathing thing and never perfect, but when it stops someone from doing something, it becomes an issue


David Gleason, Chief Data Officer, Deutsche Bank Corporate Bank


Rethinking data In 2017, the Chief Data Office set about developing a data management strategy, investing in improved data governance and quality management. It sought to transform its data management function from a defensive tool that prevented financial crime and ensured client privacy, to a dynamic development tool that brings new insights and capabilities to clients. This included the following areas of focus: • Data-focused talent and culture. This involved: improving the group-wide understanding of the critical need for investment; enhancing the visibility and understanding of the bank’s data assets; providing a core pool of data analytics, modelling and engineering skills; and developing continuous learning programmes.


• Data architecture and tools. An interim and target schema (as you can’t get to where you need to be overnight) that represents the future streamlined data landscape,


85


Clients are asking for increased transparency on financial and non- financial metrics and data-driven insights and recommendations, not to mention harmonised information flows across banks. But corporate treasurers from large commercial clients are now looking to their banking partners to be data and technology innovation partners, in addition to providing traditional banking services.


Banking partners including Deutsche Bank are investing in analytics to examine where and how businesses can make efficiencies and run a more streamlined operation. They can highlight, for example, where cost is leaking from a business and where more value can be squeezed from.


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