Strategy, Data, Jul 02, 2021

Innovating payment processing using data-driven insights

Antonio Peneda

The payments industry has long been heavily influenced by technological disruption.

Increasing market disintermediation led by innovative digital service offerings, coupled with the COVID-19 pandemic, is driving cashless payments to new highs. This reinforces the need for fast, error-free, low cost, and compliant payments that will increasingly differentiate market leaders and drive growth. However, a capability gap is emerging between the financial powerhouses and early payments innovators versus the businesses founded within the digital economy.

The challenge

Whilst a number of organisations have embarked on data transformation efforts, many are failing to achieve their data strategy. Data quality remains a major challenge for banks and payment organisations who face internal organisational barriers and governance issues, as well as outdated systems and processes. This often results in data, which is rich in potential, not being used as actionable insight to generate results. Compounding this issue are the varying payment data standards held globally, resulting in separated instances of banking systems for processing. In our experience, we have encountered a range of issues in working with clients:

  • Lack of a clear group-wide data strategy and sub-optimal data architectures for effective data exploitation, including complex payment integrations limiting the ability to change. ​

  • Lack of transactional data insight that could otherwise be used to understand payment issues and drive operational efficiency across the end-to-end payment lifecycle as well as generate new customer insights to enable personalisation.

  • An increase in digital transactions means an increase in fraud and error, a higher number of declined transactions, and an impact to customer experience and cost of processing.

  • Bureaucratic governance and management that are disconnected from the business value and required data use cases resulting in delays to effective data exploitation when these processes should in fact be enablers of safe and effective use.

Read next: Leveraging operational excellence to optimise payments processing

Embedding a data-centric culture to enable transformation

From delivering operational insights to forming the bedrock of quality and compliance programmes, and from understanding customer behaviour to assessing the efficiencies of current processes and systems, putting data at the heart of your change agenda will provide the insight you need to make not only the right operational decisions, but inform the direction of required transformational investments too.

Payments innovation remains a key priority for banking institutions, particularly given the disruption taking place. There are a number of transformative opportunities to generate revenue and manage risk that can be realised by embedding data management and curation as well as data-centric decision making as a core part of culture. Current opportunities include:

  • Exploiting plug-in analytics: Open banking integrations enable transactions across platforms and customer spend analytics across products and institutions.

  • Improving fraud risk management: Advanced anti-money laundering capabilities enabled by AI technologies are improving fraud risk capabilities whilst also being offered to B2B and B2C customers to add value to services.

  • Rich data structures, such as those introduced by ISO20022, allows frictionless payments across borders and platforms and presents great opportunities for insights of payment data, customers, and preferences.

In order to leverage these opportunities, organisations must move towards a data-centric culture. Transformation efforts need to be directed at changing the traditional attitudes and ways of working towards putting data at the core of the payment services. Understanding the value that data can bring when seen from an enterprise-wide perspective is important to drive that culture and breakdown silo’d barriers, be this across organisation departments, processes, or technologies. An enterprise-wide data strategy focuses the organisation towards single objectives and aims to align all areas in solving the common problem.

Key data strategy considerations

A data strategy should redefine the organisations capabilities to deliver agile and federated models that embrace data and analytics and enable continuous change. Responding to the constantly evolving payments market and exploiting the available industry and technological innovation requires an enterprise-wide view of data and a strong understanding of available data capabilities and achievable benefits. Key considerations for defining and delivering on your data strategy include:

  • Enterprise-wide or domain specific: Delivering a data strategy across the organisation is a major undertaking that could halt any efforts before they even start. Iterating the strategy starting with a single domain has benefits to course correct and show value earlier on, whilst gaining support from each business area.

  • Senior sponsorship: Development of strong senior sponsorship for planned investments and a clear definition of the value that this will bring. Mapping your data strategy to KPIs and objectives and across processes and capabilities will focus your investment priorities and act as a guide for payments teams.

  • Modern data architecture management: Aligning the enterprise’s data architecture with an effective data architecture management capability focused on a service-oriented approach. Simplifying data architectures that enable agility and speed of data processing help to support analytics capabilities in strategic and operational decision making.

  • Leveraging the benefits of ISO20022: Implementation of the standard promises and a comprehensive interoperability across platforms enables organisations to develop banking products faster and adds value to services through rich data structures. This helps to ensure that your organisation is ISO ready to capitalise on the wealth of payment data.

  • Advanced analytics capabilities: Development of analytics capabilities, supported by a strong foundation of data architecture management, enabling a feedback loop to improve services and products.

In a nutshell

Greater operational insight will open the door to new innovation paths, whilst identifying opportunities for cost savings from better payment efficiency and more effective management of risk. At the same time, greater customer insight can lead to enhanced payment facilitation, improved service offerings, user-centric innovations, and ultimately a more satisfied customer.

Your data is likely to be the catalyst to further growth. Through a better understanding of your customers and operations, you can map a route to lower costs, targeted process optimisation, and enhanced customer experiences.

Learn more about data strategy

Read more:
Understanding data and analytics maturity: A focus on Strategy and Alignment
Understanding data and analytics maturity: A focus on Data Services and Compliance
How can retail banking adapt to the new normal to keep up with customer demand?
How wealth managers can use data to keep focused on what really matters: Achieving digitisation success
How banks can achieve the promise of open banking with a data mesh architecture

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