How hyperautomation is underwriting the future of risk streamlining in insurance

The actuarial science of underwriting has evolved remarkably since its birthplace in Edward Lloyd’s coffeehouse in London in the early 17^th century. Risks associated with shipping evolved the place into the birthplace of Lloyd’s of London, which then evolved into a premier insurance market. Over the next two centuries, global regulatory standardizations were introduced, transforming insurance into a significant economic sector in the 20th century. Statistical data analysis methods are further refined underwriting, making it more accessible and ensuring adequate coverage.

However, new risks due to technological advancements and socio-economic changes challenge traditional models that rely on historical data. Cyber risks, climate change, and heightened data protection demands require underwriters to consider new variables.

In the 21st century, we are at yet another evolutionary inflection point. This is where the integration of bleeding-edge technologies such as artificial intelligence (AI), machine learning (ML), and hyper-automation enables human underwriters to focus on complex problems, pushing the envelope of what the industry could achieve in the future.

Key challenges impacting underwriting departments

Today, capital is not as low-cost as it used to be.

Factors including geopolitical headwinds, rising interest rates, economic uncertainties, and shifts in investment preferences reflect a broader trend of financial market adjustments to balance economic stability and growth.

This increases capital costs, forcing underwriters to adjust premium rates so that higher borrowing costs for insurers don’t lead to higher operational expenses. For example, higher interest rates might lead to better bonds and fixed-income securities returns, but also increase the cost of financing claims reserves. Underwriting teams must consider these factors when structuring policies and pricing risks​[1]. Failing to meet investor expectations can result in lost business and decreased customer satisfaction. The hurdles don’t stop there:

• The manual data collection and analysis process from various sources and systems, including customer applications, medical records, financial documents, etc., is time-consuming and prone to human error, leading to delays and inconsistencies in underwriting decisions.
• They must also navigate new regulations to ensure that policies comply with legal standards while managing the cost implications of such compliance.
• The larger the data pool, the better the analysis of data risks. With the data explosion in the digital world, managing vast datasets requires infusing AI, ML, and big data analytics into traditional underwriting processes – within tight budgets
• Accurately assessing risk and pricing policies is a perennial challenge. Emerging risks such as cyber threats, climate change, and pandemics complicate this task.

Addressing these challenges requires a combination of advanced technology, skilled personnel, and strategic management. This is why, according to a 2024 report by the World Economic Forum, the insurance industry must rewrite the underwriting story using advanced tools, expanded roles, and innovative approaches to address these inefficiencies​[1]. Deloitte’s insights indicate that insurers relying on traditional underwriting methods face a difficult-to-reverse negative spiral, including adverse risk selection and difficulties recruiting and retaining skilled professionals[2].

Essentially, instead of dealing with cost implications after the fact, they must now see risks coming miles away. In this underwriter’s need to move from the hindsight to foresight mindset, hyperautomation is proving to be the crystal ball that provides clear vision and early warnings, enabling proactive and strategic decision-making.

How Hyperautomation is ushering a new revolution in underwriting

As these technologies continue to evolve, the insurance sector will increasingly benefit from the enhanced capabilities and competitive advantages of hyperautomation. Embracing these innovations is crucial for insurers aiming to stay ahead in a rapidly changing digital landscape.

AI-powered risk assessment tools

Hyperautomation leverages AI-powered risk assessment tools to enhance the speed and accuracy of underwriting evaluations significantly. AI-driven tools can automate error-prone, manual processes, using machine learning algorithms to analyze vast amounts of data from various sources more efficiently than human underwriters. For instance, AI can process data from medical records, credit reports, geospatial information, and IoT sensors to identify risk factors and predict potential outcomes. AI techniques can analyze data faster for human underwriters to run potential risk scenarios, leading to better risk assessment, pricing accuracy, and quicker informed decisions. AI-based risk assessments could lower loss ratios significantly by better predicting risks.

Automated data collection and verification

Hyperautomation also revolutionizes underwriting by automating data collection and verification processes from disparate sources and systems. Hyperautomation uses technologies like Robotic Process Automation (RPA) and Intelligent Document Processing (IDP) to streamline these tasks. RPA bots can automatically retrieve and process data from various sources, such as online databases and scanned documents. If mere hundreds of RPA bots can handle millions of transactions annually, that would save tens of thousands of underwriter hours.

Streamlined customer onboarding experience

The integration of hyperautomation significantly improves the customer onboarding experience by making the process faster and more efficient. Traditional underwriting often involves lengthy procedures and multiple customer interactions, leading to frustration and dissatisfaction. Hyperautomation addresses these issues by providing a seamless, end-to-end, automated onboarding process.

Furthermore, AI-powered chatbots and virtual assistants can guide customers through the application process, answer queries, and collect necessary information. These tools can provide real-time updates and feedback, enhancing customer engagement and satisfaction. Moreover, hyperautomation allows for real-time customer data integration across various platforms, ensuring that all relevant information is instantly available to underwriters. This real-time data synchronization helps reduce delays and errors, providing customers faster policy approvals and a more transparent experience.

Resilience against future risks – ‘hyperautomatically’

Hyperautomation is not just a technological advancement; it’s a revolution in the underwriting process. It paves the way for underwriters to achieve unprecedented efficiency, accuracy, and customer satisfaction.

As we move forward, embracing hyperautomation is essential for those aiming to stay ahead in the dynamic landscape of insurance underwriting. The future of underwriting is here, and it is ‘hyperautomated’.

• Hyperautomation
• Risk Management in Insurance