{"id":16665,"date":"2022-01-06T19:18:10","date_gmt":"2022-01-06T13:48:10","guid":{"rendered":"https:\/\/cigniti.com\/blog\/?p=16665"},"modified":"2022-07-28T14:16:37","modified_gmt":"2022-07-28T08:46:37","slug":"rpa-bfsi-digital-transformation","status":"publish","type":"post","link":"https:\/\/www.cigniti.com\/blog\/rpa-bfsi-digital-transformation\/","title":{"rendered":"Why is RPA Needed for Transforming the BFSI Industry"},"content":{"rendered":"
Banking Financial Services and Insurance industry continues to house many legacy applications and business processes that involve many repetitive manual processes. Large organizations like JP Morgan Chase, UBS, MetLife insurance, etc., have invested millions of dollars over the years to transform their application landscape to enable end to end straight-through processing. Despite the large investments from major players, the industry has significant pockets of inefficiencies that need to be ironed out. In this mind space, Robotic Process Automation has occupied as an enabler towards the goal of digitally transformed straight-through processing.<\/p>\n
What is RPA in the financial services industry?<\/strong><\/p>\n We define RPA in the BFSI industry as robotic\/programmed applications to augment or eliminate human efforts in the financial sector. RPA helps banks, insurance, operations, and finance departments automate repetitive manual processes, allowing the associates to focus on higher-value tasks and help the organization gain a competitive advantage. A fundamental rule-driven robotic process automation rules to automate tasks without any variation. To further enhance RPA, financial institutions have implemented intelligent automation by adding AI\/ML\/NLP (Artificial Intelligence,\u00a0Machine learning and Natural Language Processing) capabilities. The addition of intelligence enables the RPA software to handle complex processes, understand human language, recognize emotions, and adapt to real-time data.<\/p>\n The global consulting firm, McKinsey, has produced a report<\/a> on RPA in which they have listed a set of potential automation candidates in the Banking and Finance industry.<\/p>\n <\/a><\/p>\n Some of the candidates in the Insurance industry are<\/p>\n How can RPA aid the digital transformation of FIs today?<\/strong><\/p>\n The holy grail of the industry players is to run an organization with fully automated end to end straight through processed services. These processes include rudimentary functions like documentation scanning and checks to significant scale exceptions handling errors.<\/p>\n Most banking and insurance customers initiate their service requests online in North America and other advanced economies. Mobile applications have taken the lead in converting customers to digital services rather than branch-based services. The online initiation of service requests has helped the FIs move towards servicing the customer digitally end to end. Digital technologies have taken significant leaps towards linking customers, banks, and supporting players. However, within the middle and back office, there are still many processes in this ecosystem that are handled manually.<\/p>\n The Financial Institutions (FIs) that have crossed the first hurdle of automating most processes still struggle with handling a mountain of exceptions thrown by their automated solutions. The presence of large-scale false positives as exceptions has significantly reduced the efficiencies gained by digital automation of processes and validations. RPA technologies like AI\/ML\/NLP rescue the FIs by embedding intelligence into these automated processes.<\/p>\n AI\/ML technologies help by understanding the rules and the exceptions that commonly occur, then suggest additions to the rules to eliminate false positives. These applications work on the data over time and reduce false positives up to 90% in many cases. One of the significant examples of RPA technologies is fraud management in the Cards and payments industry. AI-enabled fraud management software like Actimize, Tookitaki, Clari5 help the FIs to reduce or eliminate false positives by continuously learning the data and help to tweak the rules. Other examples are in the areas of Insurance policy fraud and financial reconciliation.<\/p>\n Thus, extensive usage of embedded intelligence is the next step for FIs, who have traversed large parts of the automation journey, to gain full advantage of the automation.<\/p>\n Benefits of RPA in banking and finance<\/strong><\/p>\n According to Gartner, 80% of leaders in the financial sector are already using some form of RPA for various purposes. Some of the benefits of financial process automation:<\/p>\n Conclusion<\/strong><\/p>\n Cigniti has a matured RPA CoE with extensive experience in RPA implementation<\/a>, proven methodologies, processes, and frameworks to establish a centralized RPA function. We help to start your RPA journey by helping you define the strategy. First, we help you to understand and identify processes that need automation. Once we optimize productivity and FTE, we plan the roadmap for automation rollout.<\/p>\n Bot development is at the core of RPA implementation. Based on the shortlisted candidates for automation, we design and develop bots using AI, ML, and cognitive services for process automation. Our RPA experts then orchestrate workflows, governance, and rollout validation. We have highly skilled resources in marquee RPA tools such as Uipath, Automation Anywhere, Leapwork, Jiffy.ai, and Nintex.<\/p>\n As the automation program matures, the number of bots in production periodically rise. As a result, continuous support and monitoring of these bots is required. We help in running large bot floors with L1 and L2 support models to continuously monitor and maintain the bots.<\/p>\n Schedule a discussion with our BFSI Testing<\/a> and RPA Testing<\/a> domain experts to find out more about why RPA is needed to transform the BFSI industry.<\/p>\n","protected":false},"excerpt":{"rendered":" Banking Financial Services and Insurance industry continues to house many legacy applications and business processes that involve many repetitive manual processes. Large organizations like JP Morgan Chase, UBS, MetLife insurance, etc., have invested millions of dollars over the years to transform their application landscape to enable end to end straight-through processing. Despite the large investments […]<\/p>\n","protected":false},"author":53,"featured_media":16666,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[732,2727,2786],"tags":[3954,3953,2749,3949,3950,3955,3366,3951,3952,2747,3178,2992,2750],"ppma_author":[3771],"yoast_head":"\n\n
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