Data-driven work efficiency: knock over your IT banking architecture!
Improved work efficiency is one of the results of the “overturning” of IT banking architecture from vertical silos to horizontal data fabric. In exchange, you can count on increased efficiency and better customer experience and employee satisfaction.
The last decade has been a turbulent period for the banking industry all over the world. Difficult market conditions, regulatory changes and the growing success of hi-tech in financial institutions have brought about changes. 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 colours have been forced to do more with less and expectations have increased with regard to customer satisfaction.
Silos vs. fabric in financial institutions
An independent survey of 260 US traders conducted by JP Morgan in 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 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, but it is often trapped in individual applications (silos). This means that they are not used effectively, for building competitive advantage. What allows data to be fully integrated across platforms and users, making it available where you need it, is the data fabric IT architecture. Such a horizontal approach to data, supported by built-in analytical solutions, 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. 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 to ensure financial stability.
The Horizon Bank: banking data at hand
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 the use of the full scope and depth of banks’ own information resources, which was reflected in lower sales, poorer marketing and customer service, and thus decreased financial performance.
Horizon decided to create a custom CRM solution, focusing on organizing data for work efficiency. 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 has significantly improved the company’s IT environment and subsequent management of personal current accounts.
Today, technology-powered data improve 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.
As the example of Horizon bank shows, the key to the new, super-efficient business models is to provide a data-driven work environment. It turns out that genuine customer centricity starts with improving work efficiency of each employee. In digital banking, employees must have at their disposal data and tools that increase efficiency, so that they can focus on decision making, act as an accountability partner, and offer the customer financial services they actually need.
Digital banking… without breaking the piggy bank
Banks are getting leaner and more agile as they try to keep up with technology. 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 banking 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 thus 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, to allow 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.