Modern Underwriting: Using Technology to Assess Risk Better

Łukasz Niedośpiał
July 1, 2024
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Modern Underwriting: Using Technology to Assess Risk Better

The insurance industry has always used underwriting to assess and price risk. For years, it was a manual, paper based process where underwriters would sift through piles of documents and use their experience and gut feel. 

While it worked for decades it was full of inherent problems, which is why automating routine tasks has become essential for improving efficiency and accuracy.

Historical & Pain Points in Risk Assessment

The traditional underwriting process was slow and prone to human error. Traditional data collection methods were limited in scope and often outdated, leading to inefficiencies. Decisions could take days or even weeks and frustrate the customer and slow down the insurance workflow. And relying on limited historical data and manual calculations meant risk assessment was inconsistent.

Loss ratio, which is heavily influenced by underwriting, has a significant impact on overall financial performance, varying by up to 28 percentage points between top and bottom performers

The Digital Shift & Modernization

Basic technology like spreadsheets and databases brought incremental improvements but it wasn’t until digital technology that the underwriting world really started to change. The growing demand for faster, more accurate and personalized insurance products meant a fundamental shift in how insurers assessed risk. Integrating technology with human judgment and experience is crucial in this modernization process, as it streamlines and improves risk assessments.

An Accenture study found 82% of insurance executives believe digital will disrupt the industry in the next 5 years. To stay ahead of the curve insurers are turning to advanced technology to modernize their underwriting.

Technologies Changing Underwriting

The digital revolution has brought in a host of new technologies that are changing the underwriting world. Advanced data analytics plays a crucial role in modern underwriting by improving loss ratios, increasing new business premiums, and enhancing retention in profitable segments. These technologies speed up the process and also enable underwriters to make more informed data driven decisions.

Artificial Intelligence (AI)

Artificial Intelligence is seen as the foundation of modern underwriting and can analyze vast amounts of structured and unstructured data to find patterns and correlations that human underwriters might miss. AI powered tools can automate routine tasks like data entry, preliminary risk assessment, and process repetitive tasks so underwriters can focus on complex cases.

Allianz, a global insurer, has implemented an AI powered fraud detection solution called Incognito and have seen a significant reduction in fraudulent claims and savings of millions of dollars a year.

  • Since its development, Incognito has helped save £1.7 million to date, with an additional £3.4 million held in claim reserves pending the conclusion of investigations.
  • Application fraud savings have increased by 150% compared to year-to-date expectations.
  • Specific examples of savings include a contrived accident claim that saved £21,000 after being identified by Incognito.

AI is also being used for automated underwriting of simple life insurance policies to speed up the application process and improve customer satisfaction.

Machine Learning (ML)

Machine learning is a subset of AI and focuses on algorithms that learn and improve from experience without being explicitly programmed. 

Machine learning also enhances underwriting and pricing accuracy by analyzing vast amounts of data to identify risk factors more precisely. In underwriting, ML models can analyze historical data to find predictive factors for risk assessment. These models get more accurate as they are exposed to more data so insurers can make more precise underwriting decisions.

JPMorgan Chase, a major financial institution, uses machine learning algorithms to assess credit risk and predict loan defaults and has improved their lending and risk management practices as a result. In 2017, JPMorgan Chase introduced a contract intelligence platform that leverages machine learning for financial credit risk assessment. This platform has improved the accuracy of credit risk scoring and reduced default losses.

Internet of Things (IoT)

The Internet of Things (IoT) refers to a network of devices embedded with sensors and software that collect and exchange data. IoT devices can help predict and manage future risks by analyzing data to foresee potential challenges and create risk-mitigating strategies. In underwriting, IoT devices can provide valuable insights into individual behavior and risk profiles. For example, wearable fitness trackers can monitor health data, and telematics devices in vehicles can track driving habits.

Progressive Insurance, a pioneer in usage-based insurance, offers its Snapshot program which uses telematics data to reward safe driving with lower premiums. By analyzing data on braking, acceleration and mileage, Progressive can personalize premiums based on actual risk rather than just traditional factors. This benefits safe drivers but also encourages safer driving overall.

Big Data & Advanced Data Analytics

The insurance industry generates vast amounts of data from various sources including customer applications, claims history, social media and external databases. Big data analytics combined with advanced statistical modelling can extract meaningful patterns and correlations from this data flood.

This information can be used to refine risk assessment models, detect fraud and identify emerging trends. Big data and advanced analytics also contribute to effective risk assessment by centralizing data management, automating assessments, and providing actionable results to inform risk management strategies.

A study published in McKinsey found that leading insurers who built advanced data and analytics underwriting solutions saw business premiums increase by 10 to 15 percent, loss ratios improve by three to five points, and retention in profitable segments surge up to 10 percent.

Business Rules Engine in Modern Underwriting

In the pursuit of efficiency and accuracy business rules engines (BREs) have become a powerful tool for automating underwriting. Business rules engines contribute to risk mitigation by facilitating real-time monitoring of work environments and equipment, enabling prompt hazard identification and risk assessment. 

A BRE is a software system that executes pre-defined business rules to make automated decisions based on specific criteria. These rules can be easily changed and adapted to changing market conditions or regulatory requirements.

Key Applications in the Underwriting Process

  • Risk Assessment: BREs can automatically assess an applicant’s risk profile based on factors like age, medical history, occupation, and lifestyle choices. This enables insurers to streamline the underwriting process, manage risk effectively, and quickly identify applicants who are outside their risk appetite.
  • Policy Pricing & Customisation: BREs can dynamically adjust policy premiums based on an individual’s risk profile. This means more personalized pricing where lower risk individuals are rewarded with lower premiums and higher risk individuals are charged accordingly.
  • Regulatory Compliance: The insurance industry is subject to many complex regulations. BREs can automate compliance checks to ensure policies adhere to all applicable rules and reduce the risk of non-compliance penalties.

Real-World Example

Higson Business Rules Engine found application in Notus. Notus Finance is a top 3 financial intermediary in Poland, specializing in mortgages. They aggregate different bank offers, compare them, and recommend the best one for customers.

Notus implemented Higson as part of their new sales system for brokers. The company recognized the need for a rules engine early in their development process.

Higson was chosen over other options for several reasons:

  1. It was more cost-effective when considering Service Level Agreements (SLAs).
  2. It empowers business users to control the configuration, which Notus valued highly.
  3. It offers flexible pricing.

The implementation of Higson helped Notus deliver a system that:

  1. Is manageable by business users
  2. Offers a wide range of configuration options
  3. Can create new mortgage products
  4. Handles cross-sell conditions, insurance pricing, and marketing descriptions
  5. Provides an API for banks
  6. Integrates with the client's CRM
  7. Enables users to compare different offers
  8. Speeds up form filling (one form for all banks)
  9. Validates applications automatically
  10. Creates payment schedules for customers
  11. Allows sending required documents online in a GDPR-compliant way

The new system powered by Higson enabled Notus to significantly shorten the time spent on each customer.

The Future of Underwriting

The underwriting world is changing fast with technological advancements and changing customer expectations. Future advancements in the risk assessment process will further streamline risk mitigation efforts, provide real-time risk understanding, and support business growth. Artificial intelligence, machine learning and big data will play an even bigger role in the future to get more accurate risk assessment, faster decisions and personalized insurance products.

While some may think technology will replace human underwriters the reality is it will enhance their capabilities. Underwriters will be freed from mundane tasks and can focus on complex cases, build stronger customer relationships and provide expert insights. But upskilling and adapting to new technology will be key for underwriters to remain relevant in this changing world.

The Future of Underwriters

In the future underwriters will be more strategic advisors using technology to guide customers through the insurance process and provide tailored solutions. They will play a crucial role in conducting risk assessments, leveraging technology to streamline these processes and provide real-time risk insights. They will interpret complex data, explain risk to customers and build trust through transparent communication.

Conclusion

Underwriting is going digital. Get with technology and partner with Higson and you’ll be ahead of the game and open up new growth, improve customer satisfaction and stay ahead in a competitive market.

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