Over the last few years, the financial sector has been under constant pressure due to the emergence of FinTech and the growth of Virtual Banking, which constitutes a strong threat to traditional banking. Due to this persistent and modern competition, all financial institutions now have a pressing need to face up to this new wave of innovation, to reinvent themselves and continually evolve as a business, in addition to offering a new and exceptional customer experience in the provision of financial services.
Faced with this scenario, it has become essential for both banks and traditional financial institutions to optimize costs as much as possible and, at the same time, to increase the productivity of their operations exponentially, and this is precisely where RPA “fits like a glove”.
Moreover, among the list of growing challenges that RPA can address are the shortage of qualified resources, the need to increase process efficiency, and the costs associated with the human resources that perform them on a daily basis.
You are probably asking yourself: How does RPA work and what are its usual applications in financial services?
The answer is relatively simple because RPA is the automation of business processes through the installation of software robots at the end user’s workstation and at dedicated servers, either on-premise or in the cloud, which, duly programmed, constitute the digital workforce, and may also be a workforce equipped with artificial intelligence services or so-called virtual assistants.
An analogy often used to exemplify the way RPA works, is a “macro” being executed on a spreadsheet, but “with steroids”, due to the immense resources and attributes that confer a greater ability to interact with various applications. However, the road to process automation is long and intense, as it requires solid training of employees, well-structured “inputs” and, mainly, governance.
However, once all this is set up and implemented correctly, RPA technology can take full control of interfaces (mouse and keyboard), including clicking and opening applications, sending emails, and copying / pasting information from one system to another.
Once the basics are understood, from the correct and careful implementation of RPA, financial institutions can enjoy reduced inefficient manual efforts (with full compliance), risk mitigation, and improved overall end customer experience. Furthermore, what makes automation more suitable for financial institutions are the reduced demands on additional infrastructure requirements along with its “low code” approach.
WHAT ARE THE USE CASES?
Since RPA can be applied in several businesses process automation projects, here are some of the most common uses in the financial sector:
Automated Report Generation – Generation of compliance reports, aimed at identifying fraudulent transactions and suspicious activities, is a ‘standard’ requirement in financial institutions. As a rule, compliance officers have the arduous, manual, and repetitive task of reading all the reports and filling in the necessary details in a form, which requires a lot of time and effort. RPA, coupled with artificial intelligence services, with natural language processing (NLP) capabilities, can “ingest” long compliance reports and thus extract the necessary information to later archive them.
Customer Onboarding – This process is usually inefficient and lengthy mainly due to the need for multiple documents that require manual verification. RPA can streamline this process by automatically reading documents using intelligent optical and intelligent character recognition (ICR) technology. Such documents can then be compared with the information previously provided by the customer. Thus, RPA in customer onboarding helps avoid manual errors, as well as saving employees time and effort in performing tasks.
Account opening – With RPA the account opening process, which is usually quite “heavy” and time-consuming, becomes much simpler, faster, and more accurate. Automations eliminate data transcription errors between central systems and new account opening applications, thus improving overall data quality.
Credit Processing – Credit processing/allocation is always by default one of the most critical areas for any financial institution. The fact that this process is extremely long and time-consuming makes it especially suited for automation. RPA can be used to handle, with clearly defined rules and almost effortlessly, the process and its exceptions as well. It also allows easy automation of relevant tasks including credit initiation, document processing, financial comparisons, and quality control. As a result, credits can be approved much more quickly, leading to greater end-customer satisfaction.
WHAT ARE THE OVERALL BENEFITS?
Scalability and Elasticity – Robots are highly scalable, which allows them to manage large volumes during peak times and, if necessary, add more digital workers in order to respond to any anomalous situation in record time.
Increased Productivity – With RPA being well implemented, financial institutions can make their processes much more agile and efficient.
Cost vs. Benefit – Financial institutions can save 25% to 50% of the time and costs associated with manual process execution.
Risk and Compliance Reporting – RPA in the financial sector helps in reporting as well as auditing to both mitigate operational risks and ensure high compliance.
The Window of Availability – Whether the goal is to reduce manual errors or achieve high productivity at low cost, robots work 24×7 to fully execute the tasks assigned to them.
Reduced Infrastructure Costs – Requires few changes in infrastructure due to its automation capability, both at the level of application interfaces, workstations, and servers that will be dedicated to the automated process. The cost of hardware & software, maintenance, and technical support is even lower for RPA implemented in the cloud.
Fast Implementation – RPA tools usually work on a “drag & drop” basis to create workflows that allow automation of processes, thus making everything much easier in terms of the effort needed both for implementation and maintenance of such automated processes, with minimal coding knowledge.
Integration with Legacy Systems – By implementing RPA in their operations, financial institutions can integrate information from legacy systems with that created and managed by newer applications to bridge gaps that exist between two ‘worlds’ that do not communicate directly. This way of integrating and making available all the essential data for automated processes, allows you to create consistent repositories of relevant data and propagate it through various applications, providing the rapid growth of your business.
Implemented in the right way, RPA is truly transformational for the financial sector as well as other industries and can be applied in many business areas such as operations, accounting, human resources, procurement, call centers, etc.