In the last few years, technology has become very important in the insurance business. In some way, 77% of insurance businesses are using AI in their value chain. This is up from 61% in 2023. 67% of insurance companies are already testing large language models (LLMs), which is a good sign that they will be widely used in the future.
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, or IPA, is a group of tools that work together to change the way insurance works. It’s more than just regular programming because it has:
- Artificial Intelligence (AI): The base of Intelligent Process Automation, AI allows systems to mimic human intelligence, make complex decisions and learn from experience.
- Machine Learning (ML): A part of AI, ML algorithms allow systems to get better over time without explicit programming.
- Robotic Process Automation (RPA): The foundation of automation, RPA is great at handling repetitive, rule-based tasks quickly and accurately.
- Optical Character Recognition (OCR): This technology converts different types of documents, scanned paper documents, PDF files or images into editable and searchable data.
- Business Rules Engines (BREs): These systems manage and execute business rules allowing for complex decision making based on pre-defined criteria.
- Intelligent Document Processing (IDP): Combining OCR with AI and ML, IDP can understand, extract and process information from various document types.
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. Intelligent Process Automation or 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:
- 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.
- Flexibility: Modern BREs are becoming more flexible and easier to update. When combined with the learning capabilities of IPA, insurance systems can adapt faster to changing regulations or market conditions.
- Transparency and Explainability: In an age where AI decisions are often seen as “black boxes”, business rules engines can provide a layer of transparency, essential for regulatory compliance.
- Handling Exceptions: While IPA is great at processing standard cases, business rules engines are crucial for handling exceptions and complex scenarios that require 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 being adopted across industries and insurance is one of the key drivers of this growth.
Insurance Intelligent Automation – Summary
When you think about how IPA could change the way your insurance business works, you should look at how each part might affect things. Business Rules Engines help people decide what to do and remember the rules. Look at a specific use case to get an idea of how the Higson Business Rules Engine might fit into your plan to automate things.
You could learn something useful from it about how to get things done faster and decide what to do better.
By integrating the BRE with IPA, your organization can create a more agile, efficient system that adapts quickly to changing regulations and customer needs, ultimately improving both operational efficiency and profitability.