Data-driven approach: knock over your bank’s IT architecture!
Improved work efficiency is one of the results of the “overturning” of IT architecture in a bank: from vertical silos to horizontal data fabric. In exchange, you get boosted efficiency, better customer data analysis, data driven decision making, and employee satisfaction, all powered by big data.
The last decade has been a turbulent period for banks all over the world. Difficult market conditions, regulatory changes and the growing success of hi-tech in financial institutions have brought about many transformations. This is especially true in jobs related to sales and handling of FICC transactions. In light of poor performance, the new regulations have triggered a spate of layoffs in many organizations. Financial institutions of all colors have been forced to do more with less and expectations have increased with regard to customer satisfaction.
Data analysis in financial institutions: silos vs. fabric
An independent survey of 260 US traders conducted by JP Morgan in 2021 (The e-Trading Edit: Insights from the inside, 2021) found that nearly a quarter of respondents cited labor productivity as their main challenge on the job. In comparison, 12% indicated remote work as the main challenge. In turn, Gartner research (Top Strategic Technology Trends for 2022) shows that among the most important technological trends for 2022, employee efficiency has been recognized as one of the three priorities for the CEO. Interestingly, the second most important was business growth and digitization.
As the authors of the report state, the value of data is visible like never before. Yet relevant data is often trapped in individual applications (silos). This means that company data cannot be used effectively for building competitive advantage. To fully integrate data across platforms and users you need data fabric IT architecture. We wrote about how to effectively and efficiently combine data from different applications in our article on bank complaint management.
You need a data driven culture bringing in a horizontal approach to data, supported by built-in analytical solutions. It allows determining what information is put to use. The real added value lies in recommendations on what other data to use, which to exchange, and how to improve data quality. This streamlines business intelligence. Building a strong data culture is essential for leveraging the full potential of data and analytics in financial institutions. As Gartner notes, this approach will optimize data management by up to 70%. By 2024, implementing data fabric solutions will quadruple the efficiency of data use while halving the number of human data management tasks, making it a best practice for ensuring financial stability.
The Horizon Bank: data sources combined
As a medium-sized American personal current account provider, the Horizon Bank wanted to solve the problem of customer relationship management that had been a challenge for years. The data infrastructure in the bank’s CRM systems did not improve efficiency in managing customer relations when handling personal current accounts. First of all, there were no data integration features. The data was stored in many databases, data warehouses and other repositories. This limited business intelligence capability was reflected in lower sales, poorer marketing campaigns and efforts and customer service, and thus decreased financial performance. It was far from a data-driven culture.
Horizon decided to create a custom CRM solution, focusing on organizing data so that employees would be able to work more efficiently. The bank merged various repositories and reorganized data, focusing on convenience for employees and hassle-free data entering. Automation and simplification of the IT infrastructure have significantly improved the company’s IT environment and subsequent management of personal current accounts.
Today, technology-powered data improves efficiency by providing a 360-degree view of customer information, including behavioral data. The bank’s data sources are powered by machine learning algorithms. Where technology has replaced spreadsheets, latest insights come in the form of daily reports from multiple sources. The bank can now obtain granular data and take action based on clear, accurate information, which was not possible before. Horizon managers have access to the system data of all business units, and some of the reports created by the new system are automatically sent to senior management, including the CEO. Structured data heralds better competition as covered in our article on ISO 20022 enhanced data.
As the example of Horizon bank shows, the key to a new, super-efficient business model is to provide a data-driven work environment. It turns out that genuine customer centricity starts with improving the work efficiency of each employee. In digital banking, employees must have at their disposal data and tools that increase efficiency and support data-driven decision making. Staff are not data scientists. They should simply have tools to focus on decision making, act as an accountability partner, and prepare the bank for future challenges.
Digital banking… without breaking the piggy bank
Banks are getting leaner and more agile as they try to keep up with technology and bolster data collection opportunities. However, increased work efficiency and better understanding of the consumer is not possible without the collection and processing of volume data. Only well-oiled data-driven processes can make employees more effective. It is not only about reducing the number of repetitive tasks, but also increasing job satisfaction. Tools that streamline data analysis allow employees to truly care for customers and cater to their needs. Motivated in such a way, the employee can become a real bank ambassador!
For many banks, the process of transforming into a data-driven organization is very difficult. Fortunately, innovative and user-friendly technologies are now available, offering the same functionalities more efficiently and at a fraction of the cost. They enable banks not only to increase operational efficiency, but also to improve customer experience. Our proprietary system Payres is based on this idea. Our solution activates and leverages volume data in real time. Payres also works as an MT/MX message converter, supporting the implementation of changes required in ISO 20022. Find out more in this ebook: ISO 20022: a new standard for a complex environment.