Actually, everything could be so beautiful. Higher interest rates are leading to rising revenues in the local financial industry, especially due to the flourishing interest and commission surpluses. Nevertheless, banks are facing a major challenge: exploding costs are weighing on the expense side of the balance sheet and increasing the much-noted cost-income-ratio in a very tangible way. According to a recent Bundesbank statistic, for example, the administrative expenses of banks and savings banks have risen by EUR 5 billion compared with 2022, with an equal increase in non-personnel and personnel expenses.
This current situation allows only one conclusion: There is urgent pressure for action on the cost side for banks. This challenge should be approached holistically by systematically addressing the structural problems.
These include three major areas in particular:
1) Still too many manual processes
2) Widespread use of stand-alone solutions instead of user-friendly self-services and end-to-end automations
3) Poor data management in customer advisory services and therefore still insufficient basis for decision-making, e.g. for fully automated credit decisions
Due to the low level of automation, the above-mentioned points lead on the one hand to inevitably high personnel costs, while on the other hand the processes are slow, inflexible, complicated, inefficient and therefore expensive. Overall, therefore, there are plenty of starting points for addressing the structural challenges and making processes more efficient and flexible.
Process optimization before automation
In the past, manual (partial) processes were often automated without a thorough analysis of the end-to-end (E2E) process, for example via Robotic Process Automation (RPA). However, if the quality of the process is not right, even the automated process will not be efficient in the long term. Instead, a thorough process analysis and derivation of optimization potentials should be carried out at the beginning in order to create efficient E2E processes.
For this purpose, typical E2E workflows, such as an account opening or a credit application, can be checked for any breaks, loops and connections to other workflows. Only if such a process is coherent from start to finish should it be automated in order to ultimately realize cost savings.
Integrated workflow systems are the first proven means of optimally automating processes. Low-code platforms go one step further, if necessary supported by the use of artificial intelligence (AI). With the help of these tools, applications can not only be developed and configured more quickly and flexibly, they also promote the agile collaboration between business departments and in-house IT that is so common today. This means that no IT tickets need to be placed for every small innovation in the application – IT no longer acts as a bottleneck.
Another major advantage of this form of development is the reusability of the solutions. This frequently described “Lego principle” further reduces development costs and thus provides further cost relief.
Fast and flexible development through low-code platforms
Low-code platforms provide an agile way to develop and optimize an E2E workflow system quickly and efficiently. By using low-code development platforms, subject matter experts without an IT background can be directly involved in the development of applications, allowing expertise to flow into workflow optimization faster and in a more targeted manner. The result is faster implementation of requirements and higher quality of developed applications. The platforms’ repository also stores generated solution building blocks that are available to all stakeholders for future applications. In a highly competitive environment, low-code platforms thus offer a decisive advantage.
The importance of AI in low-code platforms
The integration of AI in low-code applications is becoming increasingly important for banks – not only to optimize processes, but also to create a unique customer experience. For example, fintus’ low-code banking platform uses AI to read and categorize incoming documents in a fully automated way using intelligent Optical Character Recognition (OCR) and Natural Language Processing (NLP), and to further process the recognized user data in the platform. In this way, depending on the complexity of the document type, entire processes can be automated without the help of a bank employee.
Another approach for AI is the analysis of transaction data, e.g., using open banking technologies. This involves analyzing the customer’s account transactions, including those at third-party institutions, in order to generate personalized sales approaches for the company’s own products. For example, the analysis of an installment payment for a consumer loan at a third-party bank can be used to good effect in the current interest rate environment to offer the customer a personalized debt rescheduling option. The same logic can also be used to address savings or investment products in order to generate personalized recommendations.
Rules engine and business logics as key
When using AI, bots and similar solutions, it is important to integrate them into a higher- level platform with a corresponding set of rules and business logics. For example, the fintus platform already comes with a preconfigured set of rules – tailored to the requirements of European banks – and thus enables smooth integration, as data can be exchanged and evaluated more quickly and effectively. In addition, end-to-end integration of processes contributes to a faster response to changes and adaptation to new circumstances.
Optimize processes and reduce costs with fintus
By using low-code platforms, banks and financial institutions can accelerate the development of applications and processes and thus shorten time-to-market. At the same time, they can reduce costs by foregoing extensive programming work and instead relying on prefabricated building blocks.
fintus is the optimal solution provider for the use of low-code platforms in banking. The low- code banking solution from fintus enables banks to make their processes agile and efficient and to implement innovations faster. With AI-based low-code platforms, banks can optimize and accelerate their processes through intelligent automation without relying on IT support. The center-out architecture and intuitive user interface ensure that the platform can be quickly and efficiently adapted to banks’ needs at any time, and processes can also be created and adapted by an employee without programming skills. All these features make fintus an optimal solution provider for banks to quickly and cost-effectively address the highly competitive environment and rapid change in banking.