We are in an era of unprecedented technological advancement, the banking, financial services, and insurance (BFSI) sector stands at the crossroads of a revolutionary shift. Intelligent automation (IA), supercharged by the breakthrough capabilities of Generative AI (Gen AI), is not merely transforming these industries—it's redefining the very foundation. Consultancy firm McKinsey has found in a report that just 63 Gen AI use cases could contribute between $2.6 trillion and $4.4 trillion additionally to the sector annually, driven by increased productivity. Leveraging IA in the BFSI sector promises substantial economic benefits across all segments and functions. While initial Gen AI pilots in banks focus on productivity, this technology has the potential to also transform job functions and customer interactions. However, to unlock the potential of IA, several critical components must be seamlessly integrated.

IA encompasses several advanced technologies such as Robotic Process Automation (RPA), Intelligent Document Processing (IDP), LCNC platforms and Gen AI. By leveraging these technologies, businesses can automate not just repetitive tasks but complex processes as well, extract valuable insights from unstructured data, and utilize AI-driven decision-making capabilities. This enhances productivity by freeing up human resources for more strategic endeavors and improves customer satisfaction by providing better services.

Consider the underwriting process in the insurance sector as an example. From receiving broker submissions and policy documents to reviewing completeness, checking claims history, calculating premiums, and ultimately issuing policies; numerous steps can benefit from intelligent automation. Underwriting support staff can be augmented by automating the tasks, thus streamlining the process, reducing overall cycle time and improving efficiency.

Deriving Productivity from Automation

However, the true power of IA lies in its ability to transcend mere task automation and facilitate process reengineering or whole process redesign. By holistically examining end-to-end workflows covering the entire value chain, organizations can identify opportunities for optimization, streamlining, and value creation that would have been impossible through traditional means.

It is important to have a clear road map of the IT landscape for the next 4-6 years when planning automation strategies. There are multiple aspects to consider when selecting an RPA tool from the range available in the market. A single tool at the enterprise level can help reduce infrastructure setup and maintenance costs. Factors such as current infrastructure, architecture, applications, license costs, and proposed upgrades or changes to the infrastructure are crucial in finalizing the RPA tool and the right use cases. For example, in environments where Pega BPM is a primary application, using Pega Robotics makes sense from both technical and financial perspectives.

A significant example of the transformative impact of IA can be seen in Mphasis’ partnership with a leading global insurer’s Automation Center of Excellence (COE). Collaborating closely, Mphasis has delivered 150+ automations using Pega Robotics across various processes, including claims, underwriting, and credit control, spanning regions including the UK, France, Italy, Spain, Germany, and the Nordics. These automations have encompassed a diverse range of products, such as auto, commercial, property, and professional liability insurance. The initiative has yielded remarkable results, freeing up capacity equivalent to 52 full-time employees and reducing overall turnaround times by a whopping 85%. There are 20+ similar success stories across multiple verticals over the last 15-18 months period. The next phase of transformation includes IDP and Gen AI solutions to tackle more complex processes across all geographies.

Gen AI solutions are enhancing the contact center experience by providing dynamic and personalized responses, leveraging the power of large language models (LLMs) and natural language processing (NLP) to create focused and effective conversations. At Mphasis, we have developed multiple Proof of Concepts (PoCs) across BFSI functions using Gen AI solutions to transform voice processes, enhance customer experience, and improve efficiency.

We have seamlessly integrated these automation solutions with critical applications such as Guidewire CMS, Oracle DMS, and policy administration systems. A robust governance framework for robotics delivery and support has been established using JIRA and DevOps principles. By actively collaborating to identify opportunities and maintain a robust robotics pipeline, Mphasis has enabled the insurer to unlock productivity gains and enhance customer experience.

Addressing Unique Challenges

Compliance and regulatory requirements, however, create unique challenges for the highly regulated financial sector in adoption of IA. Concerns around adherence to strict guidelines and the impact on existing processes can hinder smooth adoption. Nonetheless, the value addition that IA brings is undeniable, particularly in areas such as new client onboarding, KYC, and sanctions screening processes. For instance, solutions such as WorkFusion’s AI Digital Workers, which include specialized bots for sanctions screening, can streamline manual and time-consuming tasks. Similarly, conversational AI capabilities from platforms such as Kore.AI can revolutionize customer interactions by understanding complex queries with multiple intents.

To address certain concerns where a human-in-the-loop approach is preferred, point solutions in the form of attended automations are deployed. For example, attended automations are used in activities such as account closure, money link setup, journal setup, and check setup. These solutions ensure that human oversight is maintained in critical processes, enhancing both accuracy and compliance.

Beginning with PoC and Taking it to Implementation

The journey towards leveraging intelligent automation begins with a proof-of-concept (PoC) approach. This entails identifying suitable use cases, engaging relevant stakeholders, and ensuring a clear understanding of the project’s objectives and expected value addition, both quantitative (such as cost savings) and qualitative (such as improved customer experience). After conducting the PoC and demonstrating tangible outcomes, organizations can proceed with broader implementation, supported by robust measurement frameworks.

Assessing efficiency gains in automation initiatives is relatively straightforward. By capturing end-to-end process timestamps before and after automation, organizations can quantify improvements in productivity and resource utilization metrics, such as handle time reductions. However, measuring qualitative value additions requires a more nuanced approach.

Techniques such as customer surveys, sentiment analysis, and voice-of-the-customer analytics provide valuable insights into the impact on customer experience. Similarly, employee feedback and engagement metrics shed light on how IA influences the workplace environment.

Organizations, however, differ in their approach to IA. While some are advanced in embracing these capabilities, others remain cautious. A key discussion point is building a compelling business case and demonstrating a clear return on investment (ROI). Executives need to understand the costs, expected ROI timeframes, and potential impact on existing processes or systems. The proposed IA initiative must align with the objectives outlined by the leadership team.

Process optimization and efficiency gains, though valuable, are no longer sufficient justifications on their own, as these outcomes can be achieved through alternative approaches such as lean process reengineering or traditional RPA deployments. When proposing a comprehensive intelligent automation transformation, especially involving technologies like Gen AI, organizations must clearly show the specific business key performance indicators (KPIs) that will be positively impacted, quantifying expected efficiency gains. Such robust ROI analysis, coupled with strategic alignment to executive priorities, can empower decision makers to embrace IA.

We have been an automation partner for a prominent global insurance carrier in the non-life segment since 2016. Leveraging BluePrism as the RPA tool and Abbyy Flexicapture for optical character recognition (OCR), Mphasis has automated over 150 processes, resulting in the automation of 350,000 transactions. This automation program has yielded significant benefits, including savings of approximately 300,000 hours and over $6 million in cost reductions. Mphasis provides ongoing support and maintenance services for the 100+ bots deployed in production environments.

The automation initiative has accelerated speed-to-market strategies by reducing cycle times, improved broker satisfaction as reflected in higher Net Promoter Scores (NPS), and increased quote conversion rates and policy retention. Additionally, the automated bots have extended operational capabilities, functioning during out-of-office hours, holidays, and weekends. By leveraging IA, this global insurance carrier has unlocked substantial productivity gains, cost savings, and enhanced customer experiences.

Identifying the Right Use Case is Key

A critical consideration when implementing intelligent automation is avoiding piecemeal solutions. Instead, organizations must adopt a holistic, end-to-end approach that examines and optimizes the entire workflow. This comprehensive perspective is especially crucial in customer-facing industries such as banking. It should be ensured that all feasible levers are considered while designing the solution. For example, using appropriate combinations of RPA along with OCR, ICR, ML, AI, Gen AI, etc., can enhance the effectiveness and efficiency of the automation process.

For instance, while virtual assistants and automated call handling may resonate well with certain customer segments, others may still prefer human interactions at brick-and-mortar branches. The industry recognizes these nuances and actively explores ways to cater to diverse customer profiles and preferences. By leveraging advanced customer profiling and segmentation techniques powered by data and AI, organizations can gain deeper insights into their customer base.

Leveraging Partnerships to Realize Value

Mphasis’ partnerships with companies such as Kore.ai and WorkFusion have created significant value. Mphasis has acquired the professional services arms of both these firms, bringing their expertise in-house. This strategic move allows Kore.ai and WorkFusion to focus solely on enhancing their product offerings and R&D efforts, while Mphasis leverages its newly acquired talent to deliver implementation and deployment services. When an opportunity arises that aligns with Kore.ai’s or WorkFusion’s solutions, Mphasis involves their respective teams, tapping into their deep product knowledge. Simultaneously, Mphasis contributes its own domain and technology experts, forming cross-functional teams that collectively drive successful implementations.

For the BFSI sector, such partnerships offer substantial advantages. With Mphasis as the implementation partner, pricing and commercial agreements can be streamlined, fostering cost efficiencies. Moreover, the collaboration ensures that BFSI clients gain access to cutting-edge intelligent automation solutions backed by the domain proficiency of Mphasis’ teams and the product expertise of Kore.ai and WorkFusion. This symbiotic relationship creates a win-win scenario, benefiting all parties.

As organizations embark on their intelligent automation journey, measuring and demonstrating tangible outcomes becomes crucial. Key metrics span productivity improvements, such as increased transaction volumes handled by automated solutions, efficiency gains reflected in reduced handling times, and ultimately, positive revenue impacts. However, delivering such transformation requires an enterprise-wide approach, leveraging collective strengths.

At Mphasis, we follow a Village Delivery Model, assembling experts from our diverse tribes and practices to form dedicated teams for each large-scale, complex transformative program. These multidisciplinary teams & squads seamlessly integrate capabilities such as RPA, IDP, BPM platforms, low-code/no-code solutions, and Gen AI to craft tailored solutions. Once the program objectives are achieved, team members transition back to their respective tribes and practices, fostering continuous knowledge sharing and skill enhancement.

As we look ahead, IA emerges a game-changer, unlocking new possibilities. Its impact is particularly profound in customer-facing domains such as contact center modernization, where conversational AI can elevate customer experiences by delivering seamless and personalized interactions. By harnessing the power of Gen AI in harmony with IA, organizations can simultaneously drive operational efficiencies and superior customer experience – the twin pillars of sustainable growth and competitive advantage in the contemporary experience economy.