Skip to main content

Advertisement

SpringerLink
Log in

Robotic process automation in banking industry: a case study on Deutsche Bank

  • Original Article
  • Published:
Journal of Banking and Financial Technology Aims and scope Submit manuscript

Abstract

Robotic process automation (RPA) is a software robot technology designed to execute rules-based business processes by mimicking human interactions across multiple applications. As a virtual workforce, this software application has proven valuable to organizations looking to automate repetitive, low-added-value work. The combination of RPA and Artificial Intelligence (AI) is called CRPA (Cognitive Robotic Process Automation) or IPA (Intelligent Process Automation) and has led to the next generation of RPA bots. It has been transforming the banking industry by making the core financial operations exponentially more efficient and allowing banks to tailor services to customers while at the same time improving safety and security. 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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Asquith A, Horsman G (2019) Let the robots do it!–Taking a look at Robotic Process Automation and its potential application in digital forensics. Forensic Science International: Reports, 1, 100007

  2. Aggarwal N (2020) Deutsche Bank to prioritize public cloud investments in FY 2020. ETCIO—The Economic Times

  3. Alberth M, Mattern MICHAEL (2017) Understanding robotic process automation (RPA). J Financ Transform 46:54–61

    Google Scholar 

  4. Brener S (2019) Automation and data as a resource. Cash Management

  5. Biscotti F, Tornbohm C, Villa A, Bhullar B (2020) Competitive landscape: robotic process automation software. Gartner. Initiatives: Technology Market Essentials.

  6. BCBS (2013) Principles for effective risk data aggregation and risk reporting. Basel Committee on Banking Supervision—Bank for International Settlements.

  7. Chen IJ, Popovich K (2003) Understanding customer relationship management (CRM): People, process and technology. Bus Process Manag J 9(5):672–688

    Article  Google Scholar 

  8. Chappell D (2016) Understanding enterprise RPA: the blue prism example. Chappell & Associates

    Google Scholar 

  9. Conrad E (2011) Chapter 1—domain 1: information security governance and risk management. Eleventh Hour CISSP. Syngress, pp 1–18

    Google Scholar 

  10. Clarke M (2018) Deutsche bank security services: getting personal. Deutsche Bank Flow Magazine

    Google Scholar 

  11. Cryan J (2016) Deutsche Bank Corporate Responsibility Report.

  12. Deutsche Bank (2016) Banking Cybersecurity - Beyond IT Controls [Whitepaper].

  13. Dann C, Murchu C (2021) Driving Data Quality. Flow Magazine - Insights from Deutsche Bank Corporate Bank

  14. Deckard, M (2017) Robotic process automation. RPA in our own words: managing unstructured data. UiPath. https://www.uipath.com/blog/rpa-in-our-own-words-managing-unstructured-data. Accessed 7 May 2017

  15. Deloitte & Efma (2017) AI and you: Perceptions of Artificial Intelligence from the EMEA financial services industry. Grid by Deloitte

  16. Daly C (2018) Scaling intelligent automation: Pitfalls to avoid. In: Your intelligent automation journey. AI Business e-book series. WorkFusion, Inc. p 20

  17. DISYS (2016) Robotics process automation: optimizing today’s banking workforce. Banking & financial services. Digital Intelligence Systems, LLC (DISYS)

    Google Scholar 

  18. Dilmegani C (2021) Robotic Process Automation Comprehensive Guide [whitepaper] AI Multiple.

  19. Durbin J (2016) A practical approach to cybersecurity management. Flow Magazine - Insights from Deutsche Bank Corporate Bank

  20. Ernst & Young EY (2018) ISACA LA. Robotics Process Automation (RPA) and Artificial Intelligence (AI): a new world order

  21. Everest Group (2017) Robotic process automation (RPA) Evolution | Market Insights. Everest Group—service optimization technologies

  22. Evstifeeva P, Nielsen T, Templeman L, Davis S, Cunningham-Day J, Young C, Ostojitsch C (2019) Regulation driving banking transformation. 2nd edition. Insights into the key regulatory developments shaping the data economy, FinTech and BigTech companies in the financial industry and crypto-assets. Deutsche Bank Corporate Bank

    Google Scholar 

  23. Edwards N (2020) The Digital side of deutsche bank that you have not heard about. Forbes Magazine

    Google Scholar 

  24. European Commission (2017) Building a European data economy. COM(2017) 9 final (hereinafter ‘Data Economy Communication’). https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=COM:2017:9:FIN

  25. FSB (2017) Artificial intelligence and machine learning in financial services: Market developments and financial stability implications. https://www.fsb.org/2017/11/artificial-intelligence-and-machine-learning-in-financialservice/

  26. Farhat II (2019) RPA and the government audit. J Govern Financ Manag 68(1):42

    Google Scholar 

  27. Fast-Berglund Å, Fässberg T, Hellman F, Davidsson A, Stahre J (2013) Relations between complexity, quality and cognitive automation in mixed-model assembly. J Manuf Syst 32(3):449–455

    Article  Google Scholar 

  28. Forest H, Foo E, Rose D, Berenzon D (2014) Big data: how it can become a differentiator. Deutsche Bank [White Paper]

  29. Fitsche, J Jain A (2014. Deutsche Bank Corporate Responsibility Report

  30. Goldenberg B (2000) What is CRM? What is an e-customer? Why you need them now. In: Proceedings of DCI Customer Relationship Management Conference, Boston, MA, pp 27–29

  31. Governance Institute (2020) What is governance ? Governance Institute of Australia

    Google Scholar 

  32. Gutierrez-Garcia JO, Lopez-Neri E (2015) Cognitive computing: a brief survey and open research challenges. In: 3rd International Conference on applied computing and information Technology/2nd International Conference on computational science and intelligence, pp 328–333

  33. Harper J (2018) Transforming RPA into intelligent automation with AI. In: Your intelligent automation journey. AI Business e-book series. WorkFusion, Inc., p 16

  34. Hoback K, Poltrack N, Risolo S (2020) Intelligent automation in banking: 10 Insights from IABFSI 2020. WorkFusion

    Google Scholar 

  35. Horton R, Rollason C, Gordeeva M, Green J, Rollason C, Patel T (2018) The robots are waiting: Are you ready to reap the benefits? Deloitte Consulting, London

    Google Scholar 

  36. Huang K, Madnick S (2020) Cyber securing cross-border financial services: calling for a financial cybersecurity action task force. Available at SSRN 3544325

  37. Haun M (2014) Cognitive Computing-Steigerung des systemischen Intelligenzprofils. Speyer, Deutscheland, Springer Verlag, pp 28–37

    Google Scholar 

  38. IDRBT (2011) Information Security Governance for the Indian Banking Sector. IT Governance Series. Sub-group on Information Security Governance Institute for Development and Research in Banking Technology—Established by Reserve Bank of India

  39. IDRBT (2011) Holistic CRM and Analytics: for Indian Banking Industry. A practical handbook covering conceptual framework, focus areas, implementation approaches & benefits of CRM solutions. CRM series: Holistic CRM and Analytics.

  40. IEEE (2017) Guide for Terms and concepts in intelligent process automation. In: IEEE Std 2755–2017, Vol., no., pp 1–16, 28, https://doi.org/10.1109/IEEESTD.2017.8070671.

  41. IBM (2016) The cognitive bank: decoding data to bolster growth and transform the enterprise. IBM Institute for Business Value. Executive Report Banking and Finance

  42. Kaya O (2019) Artificial intelligence in banking: a lever for profitability with limited implementation to date. EU Monitor Global financial markets. Deutsche Bank Research

    Google Scholar 

  43. Kapoor S (2020) IDC perspective: Six capabilities from leading RPA service providers that advance financial services institutions toward intelligent automation. IDC PERSPECTIVE: analyse the future

  44. Leukert B (2020) Tomorrow’s technology today. In: Flow magazine—insights from Deutsche Bank Corporate Bank. https://flow.db.com/more/technology/tomorrow-s-technology-today

  45. Lacity M, Willcocks LP (2015) Robotic process automation at telefonica O2. MIS Q Exec 15(1):21–35

    Google Scholar 

  46. Lin P (2018) Adapting to the new business environment. CPA J [s. l.] 88(12):60–63

    Google Scholar 

  47. Lindstrom F (2018) The CIO view: Successful banking automation needs a long-term plan. In: Your intelligent automation journey. AI Business e-book series. WorkFusion, Inc., p 12

  48. Modha DS, Ananthanarayanan R, Esser SK, Ndirango A, Sherbondy AJ, Singh R (2011) Cognitive computing. Commun ACM 54(8):62–71

    Article  Google Scholar 

  49. McWaters JR, Galaski R (2018) The New Physics of Financial Services: understanding how artificial intelligence is transforming the financial ecosystem. In: World Economic Forum

  50. Mai H (2018) Card fraud in Germany: few incidents, but high costs. Deutsche Bank Research. Talking point

  51. Manning V (2018) Preparing for real-time liquidity: The need for collaboration around the future of liquidity and collateral management. Deutsche Bank Global Transaction Banking [Whitepaper]

  52. McKinsey (2017) Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages. McKinsey Global Institute

    Google Scholar 

  53. Nirale S (2018) Your ultimate CX destination. Servion Global Solutions

    Google Scholar 

  54. Noonan L (2017) Deutschee boss Cryan warns of ‘big number’ of job losses from tech change. The Financial Times

    Google Scholar 

  55. Orynbayeva A (2019) A governance model for managing Robotics Process Automation (RPA). https://repository.tudelft.nl/islandora/object/uuid%3Ab4609d10-9318-465c-baa4-e945e7de1a96

  56. Overby S (2017) RPA proving its transformational value at Deutsche Bank. CIO

    Google Scholar 

  57. Opher A, Chou A, Onda A, Sounderrajan K (2016) The rise of the data economy: driving value through internet of things data monetization. IBM Corporation, Somers

    Google Scholar 

  58. Patterson K (2017) Governance in the age of automation. N Z Manag [s l.] 31(10):22

    Google Scholar 

  59. Polaris Market Research (2018) Robotic process automation (RPA) market size, share, trends, & industry analysis report. Report ID: PM1010

  60. Romao M, Costa J, Costa CJ (2019) Robotic process automation: A case study in the banking industry. In: 2019 14th Iberian Conference on information systems and technologies (CISTI) (pp. 1–6). IEEE

  61. Syed R, Suriadi S, Adams M, Bandara W, Leemans SJ, Ouyang C, Reijers HA (2020) Robotic process automation: contemporary themes and challenges. Comput Ind 115:103162

    Article  Google Scholar 

  62. Sharma V (2019) Cognitive computing in banking. CAPCO: the future now. https://www.capco.com/Intelligence/Capco-Intelligence/Cognitive-Computing-in-Banking

  63. Sewing C (2020) Annual Report 2019—Deutsche Bank

  64. Sewing C (2020) Deutsche Bank Human Resources Report—2019

  65. Sehr M (2016) Cybersecurity: work together and be vigilant. Financial Intelligence Guide. The Banker. Deutsche Bank Corporate Bank

    Google Scholar 

  66. Suri VK, Elia M, van Hillegersberg J (2017) Software bots-the next frontier for shared services and functional excellence. In: International Workshop on Global Sourcing of Information Technology and Business Processes. Springer, Cham, pp 81–94. https://link.springer.com/chapter/10.1007/978-3-319-70305-3_5. Accessed 7 May 2021

  67. Slaby JR (2012) Robotic automation emerges as a threat to traditional low-cost outsourcing. HfS Res Ltd 1(1):3–3

    Google Scholar 

  68. Spanyi A (2010) Business process management governance. In: Handbook on business process management 2. Springer, Berlin, pp 223–238. https://link.springer.com/chapter/10.1007/978-3-642-01982-1_11. Accessed 7 May 2021

  69. Smith M (2016) Intelligent automation: exploring enterprise opportunities for systems that do, think and learn [whitepaper]. Cognizant

    Google Scholar 

  70. Storey VC, Song IY (2017) Big data technologies and management: what conceptual modeling can do. Data Knowl Eng 108:50–67

    Article  Google Scholar 

  71. Schmitz-Becker C, Manning V, Smeeton J, Madjar B, Genter W, Bremer H, Jendruschewitz B (2018) The road to real-time treasury. [whitepaper] Deutsche Bank Global Transaction Banking.

  72. Spinale L (2019) The Innovators 2019: Innovation Centers. Global Finance, The Magazine

    Google Scholar 

  73. Schmitz M, Dietze C, Czarnecki C (2019) Enabling digital transformation through robotic process automation at Deutsche Telekom. In: Digitalization cases. Springer, Cham, pp 15–33. https://link.springer.com/chapter/10.1007/978-3-319-95273-4_2. Accessed 7 May 2021

  74. Sun G (2017) Roboter sind Produktivitätstreiber - Interview mit Gülabatin Sun, Deutsche Bank. Horváth Directions: Magazin für Wegwensend Unternehmenssteuerung Und Performanceoptimierung, By Horváth & Partners: Management Consultants, pp 15–16

  75. Temeno (2020) Forging new frontiers: advanced technologies will revolutionise banking. The Economist Intelligence Unit

    Google Scholar 

  76. Van Der Aalst WMP, Bichler M, Heinzl A (2018) Robotic process automation. Bus Inf Syst Eng 60:269–272

    Article  Google Scholar 

  77. Van Grembergen W, De Haes S, Amelinckx I (2003) Using COBIT and the balanced scorecard as instruments for service level management. Inf Syst Control J 4:56–62

    Google Scholar 

  78. Vishnu S, Agochiya V, Palkar R (2017) Data-centered dependencies and opportunities for robotics process automation in banking. J Financ Transf Capco Inst 45:68–76

    Google Scholar 

  79. WorkFusion (2017) Automation Quick Start Guide A practical resource for evaluating, prioritizing, and staging the automation of business processes with RPA and cognitive automation.

  80. Willcocks LP, Lacity M, Craig A (2015) The IT function and robotic process automation. The Outsourcing Unit Working Research Paper Series. Paper 15/05

  81. WorkFusion (2020) Intelligent Automation Delivering the Future of AML: reshaping adverse media monitoring—a bedrock anti-money laundering control. Accent Appl Intell

  82. WorkFusion (2019) The Innovators 2019: innovation centers. Global Finance. The Magazine

    Google Scholar 

  83. WorkFusion (2019) Customer success. Deutsche Bank: driving digital transformation around the world. https://www.workfusion.com/customer-stories/deutsche-bank/

Download references

Acknowledgements

The language of the paper have benefited from the academic editing services supplied by Eric Francis to improve the grammar and readability.

Funding

The author received no funding for this work.

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Essex, Colchester, Essex, UK

    Alice Saldanha Villar

  2. College of Management and Technology, Walden University, Minneapolis, Minnesota, USA

    Nawaz Khan

Authors
  1. Alice Saldanha Villar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nawaz Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conception or design of the work: AV and NK. Data collection: AV. Data analysis and interpretation: AV. Drafting the article: AV. Critical revision of the article: NK. Final approval of the version to be published: AV and NK.

Corresponding authors

Correspondence to Alice Saldanha Villar or Nawaz Khan.

Ethics declarations

Conflicts of interest/Competing interests

I declare that I have no significant competing financial, professional, or personal interests that might have influenced the performance or presentation of the work described in this manuscript.

Supplementary Information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Villar, A.S., Khan, N. Robotic process automation in banking industry: a case study on Deutsche Bank. J BANK FINANC TECHNOL 5, 71–86 (2021). https://doi.org/10.1007/s42786-021-00030-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42786-021-00030-9

Keywords

Search

Navigation