Thought Leadership
The market for traditional financial services is still dominated by a few large players within the universal banking system that prevails in Germany.
A distinction must be made between three main groups of universal banks: Private banks, public-sector banks and cooperative banks. However, all these traditional credit institutions have one thing in common – not least due to the greatly accelerated digitalization of banking in the wake of the Covid-19 pandemic: they are facing growing competition from new market players – such as fintech start-ups or digital banks – that are increasingly using technology to offer consumers innovative and convenient banking solutions that cater to changing user behavior. This is because more and more customers increasingly prefer contactless online banking solutions. In order to remain competitive, traditional banks are investing in digital transformation and technologies such as artificial intelligence (AI) and machine learning (ML) to improve customer service and increase efficiency, while smaller retail banks need to become active themselves, particularly through the use of robotic process automation (RPA).
Optimization opportunities in retail banking through RPA
The potential applications of RPA in retail banking are diverse. From customer service and recurring operational processes to marketing and sales, robotic process automation offers immense benefits. Some of these are listed below:
Onboarding: If smaller banks, especially local branch banks, want to set themselves apart from the competition and offer additional services – such as regional shopping vouchers, additional online services or welcome gifts – they have to take action themselves with regard to the necessary processes. By using RPA, such special services are then made available automatically:
Account maintenance: The processes in the area of account maintenance are already largely automated by the higher-level providers. However, if additional services, such as gifts for anniversaries, are to be added, this process can be fully automated with the help of RPA.
Account closure: If the portfolio of a smaller branch bank includes other, self-created offers – such as special online insurance policies – their deregistration can also be automated through the use of additional RPA functionalities.
Customer service: Automated customer support is one of the most popular use cases for RPA in retail banking, as its use significantly reduces the workload of customer service employees. This enables banks to offer their customers a faster and more efficient service and thus improve the customer experience. At the same time, the reduction in manual tasks leads to a noticeable reduction in operating costs.
Data entry and validation: RPA bots are able to extract data from a variety of sources such as emails, PDFs and spreadsheets, enter it into the bank’s system and then validate it by cross-checking data from other sources. This leads to a significant improvement in service quality in the bank’s core processes.
Automated lead generation: Automated lead generation is a crucial aspect of retail banking, as it helps smaller banks in particular to identify potential customers and generate new business opportunities. With the help of RPA, banks can automate the lead generation process by collecting and analyzing customer data from various sources such as social media, online forums and customer feedback.
Personalized marketing: Automated personalized marketing helps smaller banks in particular to engage with their customers in a more targeted and effective way. With the help of RPA, they can analyse customer data and behaviour patterns to create regional, personalized marketing campaigns.
Cross-selling and upselling: Automated cross-selling and upselling is a powerful tool for smaller retail banks to increase sales and customer satisfaction. By using RPA, banks are able to analyze customer data and behavior to identify opportunities for cross-selling and upselling.
In a fiercely competitive environment, smaller branch banks in particular need to position themselves by offering agile and customer-friendly processes and scoring points with regional offerings. RPA creates the necessary technological conditions to achieve all of this. It enables the optimization of processes, increases efficiency while saving time and conserving human resources. In addition, it offers functionalities that higher-level data centers do not provide. RPA is therefore a powerful tool for the business success of such credit institutions – both today and in the future.
(pd/SS&C Blue Prism)
