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RPA – Rocket Fuel for Insurance

Insurance companies have leveraged various technologies to manage complexities relating to products, processes and customer interfaces. One technology stands out for ushering in unimagined transformations in the sector. Hear firsthand from 4 such companies:

RPA Case Study 1

Driving RPA with multi-vendor benefits

Interview with KV Dipu, Senior President & Head-Operations & Customer Service, Bajaj Allianz General Insurance:

Driving RPA with multi-vendor benefits

Ravi Lalwani: In which products and processes is RPA making the biggest impact at BAGIC?

KV Dipu: At Bajaj Allianz General Insurance, Robotic Process Automation (RPA) has made a significant impact across various products and processes, revolutionizing the way we operate and serve our customers. RPA has been a game-changer in streamlining operations, enhancing customer service, improving claims processing, optimizing financial tasks, and facilitating distribution. Here are some of the key areas where RPA has had the most substantial impact:

1. Policy Issuance and Endorsement Issuance: RPA has transformed our policy issuance and endorsement issuance processes. Mundane, rule-based tasks that used to require manual intervention and hours of effort are now automated. This has not only accelerated the issuance process but has also reduced the margin for error, ensuring that policies and endorsements are accurate and compliant with regulations.

2. Reconciliation: The reconciliation of financial data is a critical function in the insurance industry. RPA has been instrumental in automating this process, enabling our teams to reconcile vast amounts of data quickly and accurately. This has led to more efficient financial reporting and compliance

3. Bulk Processing: One of the standout achievements of RPA implementation in our organization is the handling of bulk processes, such as the issuance of government policies in mass. These tasks involve processing large volumes of data and documentation, which can be overwhelming if done manually. RPA robots excel in handling such tasks efficiently, ensuring that government policies are issued promptly and accurately.

4. Tracking and Ticketing: RPA has improved our ability to track and manage tasks and tickets across departments. It automates the creation, assignment, and tracking of tickets, ensuring that customer inquiries and service requests are handled promptly and with full visibility.

5. Allocation: In the realm of allocation, RPA has simplified and optimized resource allocation. It helps in assigning tasks and responsibilities to the right teams or individuals based on predefined rules and priorities. This ensures that work is distributed evenly and efficiently among our teams.

6. Downloads: Handling the downloading of documents and data is another area where RPA has made a substantial impact. RPA robots are capable of swiftly and accurately retrieving and storing important documents, ensuring easy access and compliance with data retention policies.

The impact of RPA in our organization is not limited to process efficiency alone. By automating routine, rule-based tasks, our employees have been freed from mundane work, allowing them to focus on more value-added activities that require human judgment and creativity. This has boosted employee morale and productivity. Furthermore, RPA has enhanced our customer service by reducing response times and minimizing errors, leading to higher customer satisfaction. Claim processing has become faster and more accurate, ensuring that our customers receive timely support when they need it most. In the finance department, RPA has improved accuracy in financial reporting, reducing the risk of costly errors.

Which ones were easiest to implement, and which ones were toughest?

Easiest to Implement:

1. Single Platform Processes: Processes that are confined to a single platform or application were typically the easiest to implement with RPA. These processes involve straightforward tasks within a single software environment. RPA robots can easily navigate and manipulate data within such environments, making automation relatively straightforward. For example, tasks like data entry into a single platform database or extracting information from a uniform system were seamlessly automated with RPA. The robots could mimic human actions and perform these tasks accurately and efficiently.

Toughest to Implement:

1. Multi-Platform Processes with OCR (Optical Character Recognition): Processes that required automation across multiple platforms, especially when OCR technology was involved, posed a greater challenge. These processes often involve extracting data from unstructured documents, such as scanned images or PDFs, and then integrating this data into various systems. Implementing RPA for these processes required more sophisticated workflows. OCR technology was necessary to extract text from scanned documents, and the RPA robots needed to be programmed to interpret and process this data correctly. Additionally, the integration of multiple platforms and systems added complexity to the automation.

2. Business Rules Engines (BRE) Integration: Processes that relied on Business Rules Engines (BRE) for decision-making also presented challenges. BREs are used to define complex business logic and decision rules and integrating them with RPA required careful coordination. Automating processes involving BREs often necessitated close collaboration between the RPA development team and domain experts who understood the intricacies of the business rules. Ensuring that RPA robots could accurately apply these rules and make informed decisions required thorough testing and validation.

3. Multi-Platform Data Transfers: Processes that involved transferring data between multiple platforms, each with its unique data format and protocols, were among the toughest to implement. These processes required the development of intricate data transformation and mapping logic to ensure that data could be seamlessly exchanged between systems. RPA bots had to be programmed to handle data conversions, error handling, and exception handling across platforms, which demanded a high degree of customization and rigorous testing.

In conclusion, in our organization, single platform processes were the easiest to implement with RPA due to their simplicity and the ability to automate tasks within a controlled environment. On the other hand, multi-platform processes involving OCR, BRE integration, and complex data transfers presented greater challenges. These processes required a higher level of technical sophistication, close collaboration between RPA developers and domain experts, and extensive testing to ensure accuracy and reliability.

For RPA, is BAGIC partnering with a single IT vendor or with multiple IT vendors?

In our organization, we have opted for a multi-partner arrangement to implement hyper-automation processes that encompass a wide array of technologies, including Robotic Process Automation (RPA), Artificial Intelligence (AI) and Machine Learning (ML), Business Rules Engines (BRE), Internet of Things (IoT), and more. This strategic choice aligns with our commitment to harness the full spectrum of digital transformation tools and expertise available in the market.

We get 4 key advantages of a multi-partner approach: (i) Access to specialized expertise, (ii) Leveraging best-of-breed solutions, (iii) Innovation and competition, (iv) Risk mitigation.

Has BAGIC won any awards for RPA implementation? If yes, please give details.

(i) UiPath Automation Excellence Award for Crises Management & Business Continuity Award 2020, (ii) UiPath Automation Excellence Award 2021, (iii) TechOps 2022 Award for Robotic Process Automation, (iv) Award for RPA (Robotic Process Automation) – Digital Technology Senate Awards 2021.

[email protected]

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RPA Case Study 2

RPA handles complex cases like pricing & discounting

Interview with Vishal Shah, Head – Data Science, Go Digit General Insurance:

RPA handles complex cases like pricing & discounting

Ravi Lalwani: In which products and processes is RPA making the biggest impact at Go Digit General Insurance?

Vishal Shah: The daily workload that exists in insurance companies is very high and quick turnaround times are sacrosanct in this industry. Automation has seen rapid adoption in the insurance industry over the past few years. This is helping insurers process insurance claims at a much faster pace, thereby reducing expenses, and improving the delight factor among customers. Robotic Process Automation (RPA) is being used to create an auto scaling bot, which is helping optimize system performance based on real-time data. Pre-built RPAs are also being used to implement automated claims processing workflows and facilitating real-time and compliant onboarding processes for various teams. This is helping insurers dedicate more time to providing a more personalized experience to customers.

RPA is also being used to keep a check on potential fraud by implementing the same to verify and validate essential documents and claims. We are also observing the use of RPAs for quote generation, policy issuance and customer service support. RPA is not only helping in automating repetitive tasks, but also helping insurance companies maintain a consistent level of service quality and reduce the scope for error in data-intensive tasks. All this together has led to significant improvement in the overall operations efficiency of the insurance companies.

Which ones were easiest to implement, and which ones were toughest?

Claiming any RPA deployment as easy would be an understatement. However, some deployments have shown a better effort-to-impact ratio in relative terms. For instance, the pin code update bot plays a crucial role in ensuring accurate pin codes for policy issuance by proactively identifying pin codes which are not available in the system. This is important to ensure there aren’t any anomalies. While this had its own set of challenges, this RPA deployment was implemented without many complications.

On the other hand, more challenging implementations involve complex decision-making processes such as pricing and discounting using services like rule engine. Integrating multiple decision models and translating them into meaningful outputs for underwriting and actuary teams can be complex. However, specialized bots like the rule engine bot helped successfully streamline this process, reducing the time required for data upload and download. While implementing this was more challenging, it turned out to be a more impactful deployment.

For RPA, is Go Digit partnering with a single IT vendor or with multiple IT vendors?

Digit Insurance is one of the leading digital full stack insurance companies of India. Our entirely in-house integrated technology stack is a key enabler of our strategy and business model. The RPA development and implementation is completely undertaken by Digit’s in-house team, and we do not work with external IT vendors for the same.

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RPA Case Study 3

Single vendor approach drives consistency & efficiency

Interview with Nilesh Parmar, Chief Operating Officer & Chief Technology Officer, Future Generali India Life Insurance:

Ravi Lalwani: In which products and processes is RPA making the biggest impact at Future Generali India Life?

Nilesh Parmar: At Future Generali India Life Insurance, we have harnessed the power of Robotic Process Automation (RPA) across a spectrum of functions, leading to substantial improvements in operational efficiency and customer service. There are 4 products and processes where RPA has made the most significant impact.

(i) Operational Efficiency: RPA has been primarily deployed in our high frequency low impact operational activities, wherein approximately 90% of activities are RPA enabled. These activities encompass a wide range of tasks, including data extraction, managing back end daily operations, generating and disseminating frequent communications, modifications, and more. The introduction of automation in these repetitive tasks has not only elevated accuracy but has also slashed the processing time by an impressive 40%.

(ii) Customer Experience: RPA ensures timely fund application and correct documentation and generation of comprehensive reports. This has drastically reduced the manual workload and ensured enhancing customer experience. Secondly, RPA has been actively employed to facilitate the training of AI models for various customer facing automations, thereby contributing to our advanced analytics Natural Language Processing (NLP) initiatives.

(iii) Processing Enablement: RPA has enabled significant automation of backend processing thus enabling timely customer payouts. These enablement’s have resulted in timely error free payout processing at the same time enhancing employee experience.

(iv) Risk Management: RPA has helped us accomplish end-to-end automation of the customer verification process. This has enhanced reconciliation precision and ensured the utmost accuracy in follow-up activities related to pre-issuance and post-issuance verifications.

Which ones were easiest to implement, and which ones were toughest?

Initiatives related to operational efficiency were the easiest to implement. With these processes being well-established, our implementation of RPA seamlessly automated repetitive tasks through bots. This not only improved efficiency but also resulted in significant time savings, a key benefit for our stakeholders and investors.

Initiatives related to risk management were the toughest to implement. We had to construct workflows from the ground up, relying on provided logic without the luxury of detailed process maps. However, despite these challenges, the outcomes have been exceptionally rewarding, delivering substantial time savings and a remarkable boost in accuracy. This innovative approach underscores our commitment to staying at the forefront of modernization.

For RPA, are you partnering with a single IT vendor or with multiple IT vendors?

We have chosen to partner exclusively with a single IT vendor. This strategic decision to collaborate with a single vendor has enabled us to maintain a coherent and integrated approach to RPA implementation. It ensures consistency and efficiency in the deployment of RPA tools across our organization.

Has FGIL won any awards for RPA implementation? If yes, please give details.

As of now, our organization has not submitted entries for awards related to our RPA implementations. Our primary focus has been on achieving operational excellence and enhancing efficiency through RPA, with a strong commitment to delivering exceptional service to our customers. While we have not actively pursued external recognition, we remain dedicated to further optimizing our processes and consistently delivering value to our stakeholders.

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RPA Case Study 4
Claims bot the most challenging to implement

Interview with Sharad Mathur, Managing Director & Chief Executive Officer, Universal Sompo General Insurance Company:

Ravi Lalwani: In which products and processes is RPA making the biggest impact at Universal Sompo General Insurance?

Sharad Mathur: The insurance industry is leveraging RPA to modernize its operations, streamline processes, enhance customer engagement, and boost sales. RPA brings various benefits to insurance, such as scalability, innovation, and improved customer experiences. In our organization, we’ve implemented multiple use cases that have significantly improved our turnaround time (TAT) and operational efficiency. Some notable use cases include deploying a chatbot on our website and mobile app for customer queries, introducing the bot for claims notification, and automating end-to-end policy issuance for IPA products. We are also in the process of introducing self-service options on our WhatsApp bot. These implementations have collectively resulted in saving multiple man-month costs.

Which ones were easiest to implement, and which ones were toughest?

The easiest bot use case we implemented was related to auto onboarding of employees. On the other hand, the most challenging implementation was the claims bot, primarily due to its complex technological integrations with Natural Language Processing (NLP) and multilingual capabilities.

For RPA, are you partnering with a single IT vendor or with multiple IT vendors?

We have engaged with multiple IT vendors for our RPA initiatives.

Has USGI won any awards for RPA implementation? If yes, please give details and describe the project briefly.

Yes, our organization has received recognition for our RPA implementation. We were awarded the ‘Best Use Case of AI/ML Implementation in BFSI Industry’ for our crop bot project. This implementation addressed a critical challenge in the insurance industry: handling claims intake efficiently. During the lockdown and post-covid era, ensuring that we never miss a customer call was a top priority. To achieve this, we introduced AI-powered virtual agents using conversational AI to automate routine conversations traditionally handled by live agents.

The First Notice of Loss (FNOL), the initial step in claims processing, often involved long wait times for customers, causing frustration. Our AI Assistant, powered by conversational AI and a Digital AI Platform, provided Automatic Speech Recognition (ASR), Natural Language Processing (NLP), Dialog Management, and Voice Analytics. This technology allowed for deep neural network training, bringing the AI’s capabilities closer to human conversations, even with multilingual support.

By offloading claim calls from human service representatives to AI-powered virtual agents, we significantly improved operational efficiency. The USGIC Intelligent Virtual Assistant (IVA) operates 24×7, handling tasks such as initiating claim requests and generating claim request numbers. Within just one month of its launch, it successfully registered 94% of claims without any human intervention. This reduced the overall claim intimation time from 16 minutes to just 4 minutes, greatly enhancing customer satisfaction and operational efficiency.

Customer delight has always been a crucial focus in our technological improvements, and the Crop Bot played a pivotal role in achieving this.


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