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Date: 20/10/2018

Title: More Reach in Process Optimization with Robotic Process Automation

Teaser: Every day, banks are faced with the challenge of achieving a high level of customer satisfaction while at the same time keeping resource consumption as low as possible. Traditional IT limits this. Thanks to new technologies and approaches, decisive optimization in this area can be achieved.

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More Reach in Process Optimization with Robotic Process Automation

Every day, banks are faced with the challenge of achieving a high level of customer satisfaction while at the same time keeping resource consumption as low as possible. Traditional IT limits this. Thanks to new technologies and approaches, decisive optimization in this area can be achieved.

Authors: Andrea Frauchiger | Pascal Wagenhofer

Since the financial crisis in 2008, it has been observed that Swiss banks have on average suffered significant losses on the earnings side. Since then, financial institutions have been looking for ways to increase their revenue again. Due to falling margins, opportunities for growth on the sales side often arise only through increased product sales (e.g. the mortgage market), which are, however, purchased at a higher risk (e.g. default risk). At the same time, cost reduction plans, especially for staff, have only marginally reduced costs. Indeed, in the area of compliance there has even been an increase in staff due to the increase in regulation. Modern process optimization approaches help to sustainably reduce costs on the one hand and enhance the customer experience on the other. This also improves the cost/income ratio.

Continuous process optimization fails due to IT and internal control procedures

Processes are becoming increasingly complex for various reasons, such as:

  • external regulatory requirements and internal documentation and monitoring obligations;
  • constantly increasing customer demand for a shortened reaction time.

Regulatory and internal compliance requirements are designed to ensure that there are no formal errors or inappropriate business practices, in order to protect shareholders, customers, and other stakeholders such as taxpayers. On the other hand, the bank must actively adapt its products to the market on an ongoing basis and deliver them quickly in order to meet the rapidly changing customer requirements. The yearly goals at the front-desk of a bank are not always compatible with the safety requirements of the monitoring functions.

Another limiting factor in process optimization is the IT landscape, which is typically very heterogeneous. On the one hand, this is due to internal changes in IT («historical growth») and on the other hand to M&A activities. Old «legacy» systems are often in use, and cannot be replaced quickly due to dependencies. It is scarcely possible to estimate the risks and costs associated with the changeover to a modern or «unified» IT platform. Non-integrated and old systems thus limit the possibility of making business processes more efficient and adapting them to the current requirements of the banking business.

Process optimization in the field of various forces created by a rapidly changing regulatory system and increased customer requirements is a great challenge in itself. Together with the boundaries of today’s IT landscape, these challenges resemble a Gordian knot. Resolving them requires an innovative approach.

Process optimization as a catalyst for sustainable cost savings

In order to reduce costs in the long term, process optimization should be introduced holistically as a guiding principle (see   1). In the first step, the actual state of a process is determined. This requires accurate documentation, which must be prepared through detailed analysis. The effective costs of the analyzed processes can be determined with various tools. In order to determine them, statistically necessary data (e.g. volume ratios, tickets, etc.) is consulted. This data is verified by means of cross-comparisons within the department or assigned to individual processes. In the subsequent workshops, the process problems identified in the analysis are defined, quantified and validated with the relevant experts («subject matter experts» or «SMEs»). Problems are referred to as «waste» (see below). «Waste» that fragments the value chain and makes processes inefficient can be the following:

graphic graphic
Fig. 1: Process optimization
  • Transport: e.g. the inadequate transfer of information from system A to B,
  • Inventory/Task jam: e.g. for uncompleted tasks that have been in the queue for more than the normal processing time,
  • Movement: e.g. calls and other communication that is necessary to close or process a case/request, but that stops the process,
  • Rework: for example, cases that are opened, processed, or closed incorrectly,
  • Overproduction: e.g. processing requests outside office hours, although a service level agreement has been defined with the customer for the «next working day»,
  • Over processing: e.g. enriching information that will not be used later,
  • Waiting: E.g. if a system is not operational or slow,
  • Skills: e.g. the wrong skills in the wrong place, preventing a task from being processed correctly.

Process optimization represents an optimization problem with the three dimensions of cost, time and quality. Maximizing all three at the same time is not possible. For each process, it must be defined whether the bank customer’s willingness to pay is more likely to lie in an «inexpensive», «fast» or «secure» solution. This results in a pattern of how to deal with identified «waste». Depending on the paradigm of «inexpensive», «fast» or «secure», process parts in various combinations are eliminated, simplified or automated («Eliminate-Simplify-Automate», also known as the «ESA principle»). The process costs and key figures are available after the initial analysis. Based on this result, performance can also be observed in the future and improvements or deteriorations can be made immediately transparent compared to the initial situation.

The measures derived to eliminate «waste» must now be implemented. In practice, there are inefficiencies at the process level that cannot be avoided, e.g. due to IT limitations. Support from robotic process automation is helpful in addressing these remaining inefficiencies.

Robotic Process Automation as the key to integrated process optimization

Automation is nothing new in banking. The sector is already familiar with advantages such as precision, speed, 24/7 availability and auditability. The automation of high-volume front-to-back processes in the sense of straight-through processing (STP) is already well advanced, and a lot of investment is still being made to get the last percentages out of it. 

However, traditional IT has often turned out to be too expensive for the automation of small-volume activities, which means that there are still no business cases today. The potential has therefore not yet been tapped.

With robotic process automation (RPA), the scope of process optimization and automation can be extended by lower cost thresholds and shorter implementation cycles (see also   2). The robots follow a rule-based logic and use the graphical user interfaces (GUIs) to execute processes. Existing validations, security controls and data are used, which massively reduce risks and development efforts. No validations, security, data models or interfaces in the conventional sense have to be touched.

A typical use case for RPA is the integration of two systems to avoid «media breaks» (e.g. manually typing the clients information from a form into an IT-System), which otherwise negatively influence business processes and cause «waste». With RPA, «media bridges» can be built between existing systems using the normal user interfaces. RPA’s ability to quickly integrate with applications is particularly useful in cases involving undocumented legacy systems. This allows processes to be continuously optimized.

graphic graphic
Fig. 2: Robotic Process Automation

Through the use of robots, it is thus possible to significantly advance process optimization and thus eliminate IT-induced «waste».

In the sense of continuous process optimization, the robots should work «hand in hand» with the employees. In order to simplify the interaction between humans and robots and at the same time ensure that a process is controlled efficiently, business process management (BPM) and case management tools can be used for support. Within these tools, business cases from A to Z are displayed and assigned. These tools can be integrated with RPA (e.g. via web services). Robots can then exchange process results with employees and vice versa. The robot systematically processes the rule-based parts of the process. With the help of a BPM tool, cases to be processed by humans or requiring cognitive knowledge can automatically be assigned to the respective teams. Some BPM tools even allow «live» collaboration between employees and robots – for example if a robot’s procedure requires support from the employee to make a decision due to a complex context. This integrated «human-in-the-loop» approach allows targeted and effective support for process optimization initiatives.

Some BPM tools even allow «live» collaboration between employee and robot – for example if the robot’s procedure requires support from the employee to make a decision due to a complex context. This integrated «human-in-the-loop» approach allows targeted and effective support for process optimization initiatives.

RPA can also be supplemented by intelligent components that enable the processing of unstructured data (e.g. documents or e-mails).

In the context of an integrated process optimization initiative, RPA – with additional elements such as BPM tools or intelligent components – can cover functional deficits in IT in the shortest possible time and with smaller financial and operational risks compared to conventional automation methods.

Process optimization and Robotic Process Automation in a volatile and complex environment

External regulatory and macroeconomic trends which cannot be influenced are including opportunities and risks. As such, a bank’s operational efficiency and agility have the highest priority. 70% of the Swiss banks surveyed in a representative study conducted in 2018 cite innovation, earnings growth and efficiency improvements as their most important strategic focus for the next six to twelve months. Process optimization helps by prioritizing revenue. Efficiency gains are used as a means to achieve them.

The combined and parallel use of RPA not only allows the efficiency gains to be achieved to the full extent, but is, in fact, a factor that promotes innovation. RPA makes it easier to combine and integrate the potentially outdated IT landscape with new technologies. It is, therefore, not surprising that 75% of respondents are positive about RPA, especially in the middle- and back-office areas.



David Steiger

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