Robotic process automation in banking industry: a case study on Deutsche Bank Journal of Banking and Financial Technology

In return, the team delivers a family of products or services either to end customers of the bank or to other platforms within the bank. In the target state, the bank could end up with three archetypes of platform teams. Business platforms are customer- or partner-facing teams dedicated to achieving business outcomes in areas such as consumer lending, corporate lending, and transaction banking. Enterprise platforms deliver specialized capabilities and/or shared services to establish standardization throughout the organization in areas such as collections, payment utilities, human resources, and finance. And enabling platforms enable the enterprise and business platforms to deliver cross-cutting technical functionalities such as cybersecurity and cloud architecture. Exhibit 3 illustrates how such a bank could engage a retail customer throughout the day.

Some have installed hundreds of bots—software programs that automate repeated tasks—with very little to show in terms of efficiency and effectiveness. Some have launched numerous tactical pilots without a long-range plan, resulting in confusion and challenges in scaling. Other banks have trained developers but have been unable to move solutions into production. Still more have begun the automation process only to find they lack the capabilities required to move the work forward, much less transform the bank in any comprehensive fashion.

Layer 3: Strengthening the core technology and data infrastructure

Although intelligent automation is enabling banks to redefine how they work, it has also raised challenges regarding protection of both consumer interests and the stability of the financial system. This article presents a case study on Deutsche Bank’s successful implementation of intelligent automation and also discusses the ethical responsibilities and challenges related to automation and employment. We demonstrate how Deutsche Bank successfully automated Adverse Media Screening (AMS), accelerating compliance, increasing adverse media search coverage and drastically reducing false positives. This research contributes to the academic literature on the topic of banking intelligent automation and provides insight into implementation and development. To enable at-scale development of decision models, banks need to make the development process repeatable and thus capable of delivering solutions effectively and on-time. In addition to strong collaboration between business teams and analytics talent, this requires robust tools for model development, efficient processes (e.g., for re-using code across projects), and diffusion of knowledge (e.g., repositories) across teams.

These costs stack up exponentially for large organizations and banks that process millions of invoices, but not if intelligent solutions are leveraged to enhance these processes at scale. Business Process Automation (BPA) provides a unique opportunity to radically transform banking’s administrative burdens for both customers and employees. Repetitive yet critical processes can now be conducted by an ‘always on’ digital workforce at a fraction of the cost, many times the speed and with 100% accuracy. The old legacy banking systems are challenged to support technology that’s not native to the core system.

Best Practices For Leveraging Automation In Banking M&As

For example, banks have conventionally required staff to check KYC documents manually. However, banking automation helps automatically scan and store KYC documents without manual intervention. If you are curious about how you can become an AI-first bank, this guide explains how you can use banking intelligent automation in banking automation to transform and prepare your processes for the future. Financial organisations no longer need to go outside their platform to tack on AI—it’s already there. Integration allows organisations to focus on how technology solves business problems instead of on the technology itself.

• BankLabs & Participate, pioneering the nexus of fintech and banking evolution.Read Matt Johnner’s full executive profile here.
• The technology is rapidly maturing, and domain expertise is developing among both banks and vendors—many of which are moving away from the one-solution-fits-all “hammer and nail” approach toward more specialized solutions.
• He led technology strategy and procurement of a telco while reporting to the CEO.
• Manual invoice processing may involve several steps, such as data entry, approvals, and validation, each requiring significant time.

In addition to real-time support, modern customers also demand fast service. For example, customers should be able to open a bank account fast once they submit the documents. You can achieve this by automating document processing and KYC verification.