In recent years, financial institutions have faced significant pressure to enhance customer experience, all while managing risk and maintaining regulatory compliance. As we move into 2025, these challenges are further intensified by the rapid pace of technological advancements, increasing cybersecurity threats, and evolving regulatory landscapes.
There’s a sense of urgency to modernize legacy systems, comply with regulatory demands, and manage resource constraints while maximizing the value of tech investments, such as automation, AI, ML, and RPA technologies. This highlights the need to adapt to constant change and future-proof IT investment.
Companies with a high level of digital maturity are already employing end-to-end process orchestration as the foundation required for this change. In this blog post, we discuss the current state of process orchestration, drawing insights from a survey of over 300 participants from the banking, financial services, and insurance industries, and over 800 total participants from multiple industries.
The growing divide in finance: automation and AI are on the rise, yet inefficiencies and legacy technology are still prevalent
A study from Deloitte shows that 92% of advanced automation adopters use end-to-end automation as a part of their strategy now, or plan to within the next three years. To stay competitive and meet growing customer expectations, financial institutions must leverage orchestration, automation, and AI, as reflected by our survey results.
AI and automation technologies in financial services
AI and automation technologies are on the rise in financial services, banking, and insurance. Use cases include leveraging generative AI for creating personalized financial advice and reports, advanced AI-powered customer service chatbots, predictive analytics for risk management and fraud detection, AI in underwriting and claims processing, and AI-driven cybersecurity for real-time threat detection and response.
These advancements are significantly boosting efficiency across these industries. Yet, many—if not most—banks and financial organizations still struggle to successfully integrate them, due to their reliance on legacy technology.
Banks and financial services providers continue to face challenges with legacy systems
79% of respondents from banking and insurance said that legacy tech is keeping them from achieving hyperautomation. Transitioning away from legacy systems isn’t easy, either: 55% of respondents stated the shift from deeply entrenched monolithic platforms is a challenge at their organization.
This complication is due to several factors. First, these systems are deeply entrenched and integral to daily operations—they can’t simply be shut off without risking significant disruption to the business. Additionally, these legacy platforms often contain vast amounts of critical data and have been customized over many years to meet specific business needs, making modernization or migration projects highly complex and time-consuming.
Moreover, employees are accustomed to these systems. Transitioning to new platforms requires training to ensure they can effectively and efficiently use the new technology. There’s also the challenge of integrating new systems with existing ones, which can be technically demanding and costly.
Survey results: companies fear that increasing complexity leads to digital chaos
The widespread use of automation and AI technologies, such as machine learning, natural language processing, and RPA, leads to rapid technological advancements that introduce new complexities.
83% of respondents from banking and insurance expressed concern that a lack of control over automated systems may result in digital chaos or “automation Armageddon.” This apprehension is not unfounded, as 80% report that this lack of control has already led to an increased risk of core business processes failing to function properly.
Endpoints and components are exponentially increasing
One key driver of digital transformation is the complexity of the growing ecosystem. This leads to more connected applications, which significantly enhance functionality and user experience but also increase overall process complexity.
92% of respondents from insurance and 84% from banking said that the volume and diversity of components and endpoints across their company are increasing exponentially. Organizations in banking average about 51 components/endpoints (the highest from all industries), representing an 18% increase over the past five years.
This growth is driven by several factors. For example, nearly 70% of organizations in banking and insurance use enterprise applications, from enterprise resource planning systems such as Oracle to CRM tools like Salesforce. 67% of insurers and 65% of banks use task automation technologies, such as RPA or iPaaS.
This complexity makes it challenging to streamline and gain visibility over operations. 85% agreed that as multiple automated tasks are combined, managing the overall end-to-end process becomes more complex.
AI and automation lead to challenges with regulatory compliance and risk management
89% of respondents (both from banking and insurance) stated that tightening regulations have increased process complexity. Managing compliance and risk becomes increasingly challenging as business processes grow more complex, digital, interconnected, and automated.
Typically, compliance teams inform lines of business about upcoming regulations and necessary changes. Business teams then collaborate with compliance and IT to implement these changes. This leads to delays and miscommunication, which can result in incorrect modifications.
Moreover, many organizations find scaling and operationalizing AI challenging:
- 84% of the insurance industry said that a lack of transparency into how AI applications and services are used within business processes leads to regulatory compliance problems.
- 94% agreed that AI applications and services must be orchestrated like any other endpoint within automated business processes to ensure compliance with regulations.
One example of such regulations is the EU AI Act, a comprehensive regulatory framework, that aims to ensure the safe and ethical use of AI across industries. It introduces stringent requirements for transparency, accountability, and risk management, adding to the complexity of compliance challenges.
An additional challenge of AI is the increasing technical debt. According to Accenture’s report, “Build your tech and balance your debt,” AI plays a significant role in this rise. Generative AI and enterprise applications have become the leading contributors to technical debt.
Misalignment between business and IT teams needs to be addressed
81% of respondents believe that having business processes locked up in “black box” legacy applications hinders their organization from achieving efficient end-to-end automation.
This also impacts communication between different departments. When business and IT teams aren’t aligned, it can significantly slow down automation projects.
- 62% of survey participants noted that business users and IT struggle to collaborate on individual processes or projects.
- 77% of respondents indicated that the lengthy process of designing and approving changes is a major bottleneck in their organization.
- 82% reported that miscommunication between teams often results in incorrect implementations or products being delivered to customers.
Companies can enhance the developer experience through effective process orchestration. Adopting open standards like BPMN and DMN helps teams visualize and simulate processes, improving collaboration and alignment. Standardization plays a crucial role in maintaining and protecting the intellectual property of processes, especially against talent turnover.
Another crucial element is composability: 94% of organizations have highlighted the importance of a composable architecture for the flexible integration of best-of-breed solutions. By reusing proven process components and safely sharing them with other lines of business and teams, organizations can customize these components to their needs, fostering a trust foundation that speeds time-to-market and enhances standardization.
Process orchestration provides companies with the intelligent, composable, scalable solution they need to tackle complexity
The increasing adoption of automation and AI technologies, alongside existing legacy systems, highlights the critical role of process orchestration in financial services. This orchestration encompasses operations, finance, and organizational culture, with a strong emphasis on business automation. The majority of survey respondents agreed that effective process orchestration is necessary to manage these complexities successfully.
- 85% of respondents agree that process orchestration is essential for digital transformation.
- 88% claim that hyperautomation cannot be achieved without process orchestration.
- 79% agree that reaching an autonomous enterprise is nearly impossible without process orchestration.
The future of process orchestration in financial services and insurance
Process orchestration is the necessary foundation for integrating automation, AI, and legacy systems. It enhances operational efficiency and ensures regulatory compliance and risk management. By adopting a robust orchestration platform, financial organizations can future-proof their operations, meet evolving customer expectations, and maintain a competitive edge in an increasingly challenging landscape.
Embracing process orchestration is no longer optional—it’s essential for thriving in the modern financial ecosystem. Institutions like Goldman Sachs, NatWest, and the National Bank of Canada have already adopted Camunda’s process orchestration to coordinate complex processes across people, systems, and devices, enhancing efficiency. These leading financial institutions recognize that digital transformation and end-to-end process orchestration go hand in hand to streamline workflows, eliminate redundancies, and leverage technology for operational excellence.
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