By Andy Mott, EMEA Head of Partner Solutions Architecture and Data Mesh Lead
The financial services sector is experiencing a major transformational cycle as the effects of COVID-19, increase in regulations, and cybersecurity risks take their toll. To embrace these challenges, accelerate innovation, and compete in a crowded marketplace, financial services must move rapidly, ensuring they are gathering the right insights from their data. A recent survey from IDC found that 55% of financial service institutions want better data efforts in identifying customer-centric objectives, and they certainly have a lot of it, with more data on customers than any other sector. This trend towards data as the key to success was recently outlined by the UK Government’s AI strategy, who emphasised a need to treat ‘data as a strategic asset second only to people’.
Personal financial data is amongst the most valuable currencies in the digital economy, and to navigate this, you need a data management and analytics strategy that simplifies offerings and drives sustainable, responsible growth.
Data challenges in financial services
A hyper, important pain point in the financial services is cybersecurity and safety, as fraud becomes smarter, and more commonplace. The UK experienced in the first six months of 2021 a 71% jump in fraud cases, sparking warning of a national security threat due to the sensitive information involved in financial services. Financial services must be more efficient and smarter with their data; cybersecurity is incredibly vital. Choosing a data architecture model that supports these ambitions and safely stores data is imperative to keep up with competitors and modernise your business.
McKinsey recently reported that just 30% of financial service firms align their data and analytics strategy with their overall business goals. Now is the time to update your scalability and agility of data, beyond simply storing it. Financial services need to be driven by data not only to offer hyper personalisation for consumers but to gather greater insights into how and where customer is spending. As society draws further away from cash, digital payments can result in engagement and insightful findings which can help drive areas such as investment trends. Competition is tight, as big tech giants such as Google, Microsoft and Facebook move to take on financial services, although hindered by regulations and intricate financial know-how.
Data Mesh: the solution for financial services woes?
The Data Mesh approach, which focuses in on decentralising data and removing bottlenecks, can answer many of these challenges. Financial services domain teams can own their data closest to them, treating it as they would a high-quality product. When data is clearly owned, data owners can delegate this to an expert to oversee the development, management and serving of data, to ensure the data strategies align with organisational goals . Creating a self-service data platform supports workflows and removes friction in creating and connecting different sets of architecture to ensure efficient and organised analytics; both incredibly important assets to have in financial services. The data mesh strategy requires implementing a set of rules that applies to all data products within an organisation and makes them interoperable, for flexible decision making.
Benefits of data mesh
A data mesh approach can help financial services better serve its customers and showcase how innovation and success is enabled via a data-driven strategy. Data Mesh decentralises data management and diminishes the impacts of silos and bottlenecks by giving teams ownership, control, and access to their own data. End users can query and access data where it lives without having to transport it anywhere, gaining better management and serving abilities. This speedier access directly translates into time to value and greater discoverable insights. By empowering data and product teams, companies can adapt faster to keep up with the market and regulatory changes by removing inefficient blockers of central IT. For financial services, this is critical to keep up to date with the changing regulation market and privacy guidelines. Data mesh reduces organisational bottlenecks, simplifying access and removing unnecessary movement of data across organisational borders, enabling organisations to remain compliant with every changing national regulatory requirements.
With the decline of cash, global data volumes in the financial services continues to increase as more and more tracked transactions occur. Data Mesh architecture closes the gap between these transactions and the process of analysis with data ownership granted to individual teams, allowing them to make quick, real-time decisions without the need for data transfer.
COVID-19 accelerated the financial services industry and showcased how fast the industry can, and must, adapt and change. Moving forward with this quick agility to choose data architectures that grant independence and quick access, like Data Mesh, will enable further innovation and success. Financial services can overcome challenges concerning regulation, safety, and fraud with the use of data management that bypasses organisational bottlenecks and stores data in user-friendly and transparent means. Big tech has their sights set on financial services, and not always in the traditional ways. Data mesh will ensure financial services remain competitive and innovative.