RPA & AI in the financial sector: key functions, technologies, future decade trends

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Explore how RPA & AI are transforming the financial sector—boosting efficiency, compliance, and risk management. Learn key technologies, trends, and future insights.

 

Yury Rapatsevich, FinTech Expert & Division Deputy Director at IBA Group, explores the transformative role of RPA & AI in the financial sector, highlighting key technologies, industry trends, and the future of automation in banking and finance.

 


 

Instant payments, 24/7 available bank offices, and no queues are not a dream anymore: more than 30% of financial institutions can offer to their clients such experience, which happens thanks to Robotics Process Automation (RPA) and AI adoption within the BFSI industry. In 12 months of implementing RPA solutions, companies see 3x-10x ROI returns, Deloitte highlights, setting for a significant 25% CAGR growth.

Automation sounds like a universal solution, but it brings challenges. Tasks with large data sets or irregular workflows often need advanced AI solutions.

 

However, successful implementation requires more than just adopting technology - it demands a calculated approach. It's vital to ensure automation efforts yield results. So, we must evaluate ROI for each use case, develop a strategy, and create a roadmap. 

Deloitte suggests a formula. If it's done right, companies can achieve a seamless end-to-end automation process for more than 75% of operations through RPA platforms, Business Process Models, and Notation (BPMN) with AI elements. RPA will be key in any automation. It will ensure compliance, reduce risks, and drive innovation.

 


 

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Compliance & risk management: facilitation through RPA

Compliance and risk management are time-consuming and require accuracy. As regulations evolve and become complex, the possibility to process the amounts of data and propose informed decisions is crucial.  

A recent global RPA survey shows that automation reduces such errors by 90%. It also cuts compliance task time by half. EY's case studies reported a 92% compliance boost. This was due to automated audit trails created by RPA bots. 

Fraud detection, one of the most critical areas of risk management, also changes. Instead of relying on manual processes, Accenture reveals that AI-powered RPA enables real-time monitoring and prevention of fraudulent activities, leading to up to 32% operational cost reduction.

 

How to build smarter operations with RPA and AI?

Beyond cost savings, RPA proves its value in strategic risk management and the digital transformation of financial services.

Similarly, AI-driven credit scoring systems have increased profitability for lending divisions by as much as 34%. These success stories illustrate the immense potential of combining RPA with AI, creating opportunities for financial institutions to build smarter, more responsive operations.

 

The Future of RPA & AI in the financial sector

Looking ahead, the future of RPA lies in its integration with AI and finally in replacing robotics processes with artificial intelligence. This next generation of automation will focus on processing unstructured data, predictive analytics, and real-time decision-making. 

We are stepping into the era of a BFSI (Banking, Financial Services, and Insurance) infrastructure reorganization. Financial institutions will invest in robust IT infrastructures, including data lakes and advanced analytics platforms, to fully leverage their potential.

Based on IBA Group clients, including banks, fintech startups, and insurance companies, the most attractive trends I can name are AI for risk management, smart offers, compliance control, customer onboarding, and fraud detection. 

Companies that utilize RPA and AI today enhance their operational efficiency and secure their place as leaders in the market for the future. Start with analyzing existing processes to eliminate inefficiencies.

Some activities aren't suitable for automation, instead look at rule-based, repetitive, and time-consuming tasks. Comprehensive testing, from functional checks to integration validation, ensures smooth deployment while minimizing risks.  

The automation journey may be complex, but the rewards, cost savings, customer trust, and market leadership make it worth every effort. The question is not whether to adopt these technologies, but how quickly and effectively you can do so.

 

 

 

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