2023 has seen dramatic macroeconomic pressures impacting the banking sector. The response has been for banks to continue their ongoing transition to a true digital transformation in order to better retain customers, streamline operations, and increase productivity. To accomplish these goals, Robotic Process Automation (RPA) solutions are clearly seeing significant adoption by banks around the world. This adoption is a crucial step toward creating a Connected Enterprise where all processes and systems are seamlessly integrated and automated.
In fact, the banking sector is the world’s largest consumer of RPA technology.
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With RPA and AI, 25% of work across banking functions can be automated, freeing up the workforce for strategic tasks while increasing productivity and reducing costs. This is a key aspect of a Connected Enterprise, where automation and AI are leveraged to streamline operations and enhance decision-making.
With dynamic new business models, increased investment in technology, and multiple customer channels, the global financial industry is undergoing a colossal shift. Banks are leveraging the power of RPA not only to automate high-volume manual processes but also to transform customer journeys in ways never imagined before. This transformation is central to the vision of a Connected Enterprise, where customer journeys are seamlessly integrated across different touchpoints and channels.
To maximize the value of a bank’s investment in RPA, a clear set of best practices has emerged that shows how and where RPA can have the most impact on operations. We will look at three broad areas on how banks can leverage automation, RPA, and AI to build a Connected Enterprise. These include customer relationship management, fraud, and risk management, and automating operations.
Customer Relationship ManagementÂ
Maintaining a great customer experience is a critical competitive differentiator for today’s banks, be it commercial or retail. RPA enables a rich customer dashboard by automatically integrating information from multiple sources. It can also aid in customer onboarding with quick, OCR-enabled document verification, KYC authentication, and customer validation processes. In a Connected Enterprise, this seamless integration of customer data across different systems and processes enhances the customer experience and drives customer loyalty.
RPA in banking can also handle repetitive tasks such as data entry and analysis faster than a human can, thus freeing up time for customer service representatives to engage more deeply with customers and solve their problems. Additionally, RPA in banking eliminates the risk of human error in inputting and processing data. This ensures that customer information is always accurate and up-to-date, which is crucial for a great customer experience.
What’s more, RPA-enabled systems can easily handle a majority of customer inquiries via automated solutions. In this way, millions of customer requests can be handled daily, with some banks seeing an average increase of 20% year-on-year in the volume of requests handled. This is in part because RPA bots can work around the clock without breaks or days off. This means that customer requests can be processed at any time, leading to faster response times and greater customer satisfaction.
Fraud and Risk ManagementÂ
One task that AI and automation have consistently proven themselves more efficient is fast and efficient anomaly detection, which makes them ideal for identifying fraud and other risk-related events. In retail banks, RPA aids in real-time risk prevention by consistently scanning a diverse set of databases and other data sets to uncover and identify suspicious activity. This includes checking multiple email systems, external sites, and broker statements to generate reports and highlight anomalies.
RPA even aids in compliance activities by automatically generating detailed reports on automated processes. In a Connected Enterprise, this real-time risk detection and compliance reporting across different systems and processes significantly enhances the bank’s ability to manage risk and ensure compliance.
Automating Operations Using RPA in Banking
RPA also has great promise for automating some of banking’s most tedious processes, resulting in significant savings and immense productivity gains. A good example is streamlining the process of credit card and mortgage applications. RPA can speed up the process of collecting and verifying information for credit card applications or mortgage loan processing. This can improve customer service and allow banks to significantly increase the volume of their applications.
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RPA is also excellent at data validation and reconciliation, as banks often need to compare information across different systems or databases. RPA can automate this process, ensuring that all data is consistent and up-to-date. RPA can also automate the generation of reports on various aspects of banking operations. Even basic banking operations, like transfers, deposits, withdrawals, etc., can be automated to reduce manual effort and error.
In a Connected Enterprise, this automation of operations across different systems and processes significantly enhances operational efficiency and reduces errors.
Examples of savings delivered to banks via automation abound. For example, one multinational banking and financial services institution headquartered in Singapore wanted to undergo large-scale digital transformation to drive up process efficiencies for increased productivity and revenue enablement. Leveraging RPA technologies, the bank automated 16 use cases as part of the initial phase across multiple business processes. As a result, the bank saw a 90-95% increase in the accuracy of transaction verifications, with 16 use cases automated as part of the initial phase – and more being identified on a monthly basis. Part of this implementation saw swift integration with eWFI and Intellistar (complex legacy systems) that are used by a number of banking and insurance companies in Singapore.
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Another large global bank turned to RPA to automate a complex 12-step vendor creation process, which led to 35% cost savings and ROI in 3 months.
As we look to the future, the role of RPA in banking will only continue to grow. With the increasing complexity of banking operations and the relentless drive towards digital transformation, RPA will be a key enabler in connecting different parts of the organization, enhancing overall operational efficiency, and driving business outcomes. In the context of a Connected Enterprise, RPA is not just a tool for automation but a strategic asset that can transform the way banks operate, making them more resilient, agile, and customer-centric. As such, banking CIOs need to consider RPA not just as a technology investment but as a critical component of their strategic roadmap for the future. The journey toward a Connected Enterprise is not just about connecting systems and processes but about creating a seamless, integrated, and automated environment that can adapt to changing business needs and deliver superior customer experiences.
As we move forward, the synergy between RPA and the Connected Enterprise will redefine the banking landscape, creating new opportunities for growth, innovation, and competitive advantage.
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