Insurance with Intelligent Process Automation

Discover how Intelligent Process Automation powers insurance operations, efficiency, accuracy and customer experience.

In insurance, automation is the name of the game for the past few years. 77% of insurance companies are in some stage of adopting AI in their value chain, up from 61% in the 2023. 67% of insurance companies are already piloting large language models (LLMs), a strong indicator of future adoption.

92% of respondents expect to maintain or increase their automation efforts in the future, viewing it as a critical ongoing capability rather than a temporary trend.

But in the insurance industry, a highly regulated market, concerning tons of sensitive data, any automation has to be not only quick, but also precise. There is no room for error, especially in the compliance department.

Enter Intelligent Process Automation. A technology combining unique, useful elements to serve one purpose – to serve the customer.

This new technology is simplifying operations and changing the way insurance companies operate, interact with customers and manage risk.

What is Intelligent Process Automation in Insurance Sector 

Intelligent Process Automation (IPA) is a combination of technologies working together to transform insurance processes. It goes beyond traditional automation by incorporating:

1. Artificial Intelligence (AI): The base of IPA, AI allows systems to mimic human intelligence, make complex decisions and learn from experience.
2. Machine Learning (ML): A part of AI, ML algorithms allow systems to get better over time without explicit programming.
3. Robotic Process Automation (RPA): The foundation of automation, RPA is great at handling repetitive, rule-based tasks quickly and accurately.
4. Optical Character Recognition (OCR): This technology converts different types of documents, scanned paper documents, PDF files or images into editable and searchable data.
5. Business Rules Engines, or BREs: These systems manage and execute business rules allowing complex decision-making based on criteria that are determined in advance.Intelligent Document Processing, or IDP: OCR is combined with AI and ML to help understand, extract, and process information from different types of documents.

This combination of technologies allows insurance companies to simplify business processes, speed up claims, handle unstructured data and make data driven decisions with unprecedented accuracy and speed. IPA can understand, learn and adapt to complex insurance processes, from claims to underwriting and customer service.

Business Rules Engines in Intelligent Process Automation

Business rules engines have been the foundation of decision automation in insurance for years and with IPA they present both opportunities and challenges.

BREs allow insurers to codify complex decision-making processes based on pre-defined rules and conditions. They have been particularly useful in areas such as underwriting, claims processing and policy administration.

The combination of BREs and IPA offers:

1. Better Decision Making: When combined with IPA, business rules engines provide a framework for decision-making, while AI and machine learning components can handle more subtle, data driven decisions.
2. Flexibility: Contemporary BREs are becoming flexible and easy to maintain. This coupled with IPA’s learning capabilities allows systems to respond much faster to changes in regulations or market conditions.
3. Transparency and Explainability: At a time when “black boxes” in AI decisioning have made everyone want either to understand or distrust, business rules engines can provide a layer of explainability, important to get a regulatory compliance tick.
4. Handing exceptions: Though IPA excels in the normal cases, the business rules are very important in handling exceptions and complex situations requiring human defined logic.

IPA in Insurance

According to PwC, businesses that implement IPA can reduce compliance costs by 10% while experiencing a 15% increase in automation.

Fraud Detection

Subex has a hybrid rule engine as part of its Insurance Fraud Management solution. This combines machine learning with a business rules engine to detect and prevent fraud.

The hybrid rule engine allows insurers to catch at least 80% of fraud by allowing analysts to review only 20% of the alarms generated.

Anthem, one of the largest health insurance providers in the US, has implemented intelligent automation and machine learning to boost fraud detection.

Their automated systems have detected over $750 million in fraudulent claims per annum.

Faster Insurance Claims processing

Nothing affects customer experience like claims processing. And it takes some time.

A typical motor insurance claims process takes from two to for weeks. Some simple claims are processed within a few days. Claims involving medical injuries or disputes may extend beyond this timeframe.

McKinsey reported that AI automation can cut the cost of insurance claims processing by up to 30%.

Lemonade achieved a record-breaking 3-seconds from claim filing to payout.

Benefits of IPA in Insurance Industry

Cost Savings

In a business with $1billion revenue, even 1% is a lot.

Automating manual processes and reducing errors saves operational costs.

Better Customer Experience

Faster processing and more personalized services means better customer satisfaction. 87% of policyholders believe claims experience impacts their decision to stay with insurers, speed of settlement and process transparency are the top contributors to customer experience.

Accuracy

Eliminating human error in repetitive tasks reduces errors in insurance processes.

MetLife used intelligent process automation (IPA) to find $100M in savings by automating unstructured data processing.

Risk Assessment

Advanced analytics powered by IPA means more accurate risk profiling and better pricing and reduced losses.

Challenges and Considerations

While the benefits are clear, implementation is not without its issues.

And data security and privacy concerns need to be taken very seriously to maintain customer trust and compliance.

Employee training and upskilling is also a challenge as the workforce needs to be trained to work alongside these new technologies.

How Intelligent Automation Will Look Like in the Future

As IPA grows we will see even more advanced applications in insurance.

Some of the emerging trends are:

• IoT devices and telematics for real time risk assessment and pricing
• Blockchain for secure and transparent transactions and smart contracts
• Advanced predictive analytics for proactive risk management and fraud detection.

According to Grand View Research, the global intelligent automation market is expected to reach $15.8 billion by 2025, growing at a CAGR of 40.6% from 2020 to 2025. It is projected to reach $50.7 billion by 2032, indicating a significant growth trajectory.

This is a huge growth, and IPA is adopted across industries, and insurance is one of the key drivers of this growth.

Insurance Intelligent Automation – Summary

As you consider how IPA might transform your insurance operations, do consider where each component might play. Business Rules Engines do have a significant role to play in decision automation and policy management. If there’s a particular solution you might have an interest in seeing how it integrates with your automation strategy – perhaps even something like the Higson Business Rules Engine – why not look at a tailored use case?

That may just give you some leading insight into how processes can be streamlined and how you can improve your ability to make decisions.