Artificial Intelligence

Cheatsheet: What you need to know about Robotic Process Automation

  • The financial industry sent hundreds of thousands of jobs overseas.
  • Now, with RPA, those activities are coming back home.

Email a Friend

Cheatsheet: What you need to know about Robotic Process Automation
For decades, Wall Street has exported back office jobs overseas. India, China, and the Philippines all benefited from the move offshore. The thinking was banks should focus on what they were good at and outsource everything else. Sending jobs abroad helped shore up bank balance sheets, too, as the back office moved from fixed to variable costs. But technology always catches up. It may not bring those back office jobs back, but Robotic Process Automation, or RPA, has returned many of these activities back onshore and this time, it's computers handling them, not humans. What is Robotic Process Automation? Imagine bots, or computer programs, that can automatically handle the types of reconciliation that happen at the end of every day in a financial institution. Books are balanced, accounts tallied, and transactions matched. Files are shared and filings made to regulatory bodies. That's RPA. It's a catch-all phrase for a series of technologies, including machine learning and artificial intelligence, used to automatically handle mundane, repetitive tasks. While RPA can be used in any industry, its early adopters are financial institutions and as heavy users of offshoring firms, the industry is one of the biggest consumers of RPA technology. Forrester attributes the interest in RPA to the fact that robots can be deployed with minimal process change, ROI is straight-forward to calculate, and it's a "fresh alternative" to big spend business process management (BPM) programs. By the numbers
  • According to a study by Markets and Markets, the robotic process automation market is estimated to reach $2.467 billion by 2022, growing at a CAGR of over 30 percent between 2017 and 2022.
  • 53 percent of top global firms count RPA as their top investment focus, outstripping any other investment priority.
  • It's still early for the technology as hype exceeds real-world value. It's estimated that only half of today's RPA implementations are actually making progress.
How robotic process automation works Financial firms choose to implement RPA differently, ranging from partial to full automation. With attended automation, software bots are installed on employee desktops, assisting human operators by completing repetitive tasks in the background. In unattended automation, bots are deployed on company servers, on premise or in the cloud, and function independently of humans. Firms choose different flavors of RPA depending on the complexity and importance of the tasks it wants automated. Pricing for an RPA deployment can be done as a license fee or per bot or per process automated. The players in RPA As the market is heating up, service firms and consultancies are expectedly fomenting the hype to get their clients primed to buy. When financial firms start looking at technology providers, they'll find a field littered with companies from the U.S. Europe, and Israel. There's an ongoing arms race to get to scale. Some of the notable RPA players include: Workfusion's technology was born in research conducted at MIT during 2012-2013. The company has numerous partnerships with integrators and recently raised a $50 million Series E round. Founded in Bucharest, UiPath's current RPA offering was ranked strongest by Forrester in 2018. Automation Anywhere, BluePrism, Contextor, NICE, Pega, and Redwood Software are some of the names to watch. Kryon Systems, an Israeli firm, is a scrappy RPA vendor with inroads into financial services. The fintech view The financial industry embraced offshoring to lower costs and boost profits. The industry is also one of the largest consumers of technology. So, while RPA isn't financial in nature, it would make sense that the financial industry would be an early adopter of RPA. Expect firms to continue to tweak their RPA offerings for finance.

0 comments on “Cheatsheet: What you need to know about Robotic Process Automation”

Artificial Intelligence, Green Finance, The Green Finance Podcast

The Green Finance Podcast Ep. 15: Why climate AI is essential to reach net zero

  • Today, we're talking about artificial intelligence – a tool uniquely positioned to help manage the complex issues presented by climate change.
  • To help us understand more about how AI can help us solve the climate crisis, I've invited BCG's leading sustainability expert Mike Lyons to expand upon the study findings and explore real-world, practical applications for climate AI.
Iulia Ciutina | December 09, 2022
Artificial Intelligence, Member Exclusive

Deep Dive: What’s in the black box? The challenges of explainable AI in digital finance

  • In the wake of reports of discrimination and negative impacts on consumer wellbeing, regulatory scrutiny is increasing on FIs that use AI models.
  • AI is central to digital finance – but do we understand how it truly works?
Rabab Ahsan | November 14, 2022
Artificial Intelligence, Sponsored

How financial institutions can get the most out of artificial intelligence

  • Artificial intelligence is a complex technology with a variety of applications. For best results, financial institutions should implement AI with a specific need, plan, and strategy in mind.
  • AI can help financial institutions move beyond a transactional, generalized digital banking experience, and deliver branch-like banking on digital channels at scale.
Finalytics | November 07, 2022
Artificial Intelligence, Data

‘This year, banks will strive to balance two opposing forces’: The state of AI in banking 2022

  • AI developments in banking have so far been restricted mostly to back-end uses. This year, there is a desire among service providers to focus on innovating more for the front-end.
  • As AI becomes smarter and banks begin holding increasingly intimate data about their customers, the industry is expected to progress slowly and responsibly.
Subboh Jaffery | January 31, 2022
Artificial Intelligence, Sponsored

Four ways we can ensure AI lending works for everyone

  • Real competition in credit scoring and rigorous fair lending testing for all players will help expand credit access
  • Built correctly and with care, AI models can be even more transparent than legacy scores, which have yet to undergo real public scrutiny of their disparate impact
Zest AI | December 14, 2021
More Articles