While your underwriters scrutinize risk, your competitors are quietly automating their operations. The difference between manual and automated workflows is shrinking every day – with quantifiable impacts to your combined ratios and responsiveness to market changes. Despite significant investments in digital transformation initiatives, many carriers find themselves bound to inefficient workflows that prevent them from achieving their profitability goals. The evidence on fighting this is unambiguous, though: these persistent problems can be resolved through automation.
Why Underwriting Automation is Important
Underwriting is the foundation of risk management in insurance. While underwriting processes have evolved to include digital elements, in practice, manual processes still create inefficiencies for underwriters. The lag time that you see with manual workflows adds inefficiencies that will negatively influence profitability and likely your responsiveness to market changes. Automated workflows have, in a study by McKinsey & Company, proven to provide processing time cuts of 40-60% and operating cost reductions of 30% for insurers.
Four Key Pitfalls Automated Underwriting Systems Address
1. Reduce Variability in Decision-Making with Automated Workflows
Manual underwriting makes use of human judgment values and, in the process, undeniably creates variability in underwriting. This leads to pricing inconsistencies and regulatory exposures. A recent report by Deloitte has noted inconsistency in decisions can range from 15-25% among underwriters underwriting the identical risks.
Automated underwriting systems will make use of standardized rule engines and decision matrices to ensure consistency. It will also leverage machine learning algorithms to track risk patterns, ensuring consistency that is backed by data.
Tech Implementation: A rules-based decision engine backed by configurable business logic matrices lets you develop a versioned set of underwriting criteria, standardize exceptions, and offer you a clear audit trail where every step in decisioning is documented.
2. Enhancing Risk Assessment with Multi-dimensional Data Analytics
In a study into the limitations of traditional risk assessment, a Willis Towers Watson survey revealed that traditional risk models only considered around 30-40% of the potentially predictive risk variables. Not only did this data utilization gap create blind spots in their existing risk portfolios, but it left them oblivious to additional risks and claims losses.
Today’s automated underwriting platforms consider significantly more risk factors by leveraging capabilities such as:
- Multi-variate predictive modeling
- Natural language processing to analyze unstructured data
- Geospatial risk correlation analysis
- Real-time connectivity and query to third-party sources
- Recognizing behavioral risk patterns
With these enhanced capabilities, insurers are better placed to create risk profiles covering many of the traditional risk factors and emerging risk factors. This increased ability will help to deliver improved pricing accuracy and improve loss ratios.
3. Increasing Efficiency by Addressing Inefficiencies in Resource Allocation
Resource allocation inefficiencies in traditional underwriting are rooted in linear workflows. Much of the time, high-value underwriting talent spends approximately 40% of their time completing administrative work rather than more sophisticated risk assessments, according to Accenture.
Workflow automation drives tremendous operational efficiencies with:
- Automating document collection and document validation
- Leveraging straight-through processing for low-complexity underwriting risks
- Automatically routing complex cases to specialty resources
- Prioritizing submissions based on business value algorithms
- Removing duplicate entry of data with API integration
By moving human capital towards higher-value work, it is normal for organizations to see (the Boston Consulting Group states) around 25%-35% productivity improvement without additional headcount.
4. Shortening Decision-Making Cycles with Real-time Processing
Speed offers a substantial competitive advantage in the current marketplace. Traditional underwriting cycles, taking an average of 7-14 days, fail to meet market expectations, especially within standardized risk categories (Gartner).
Automated systems reduce this total cycle time dramatically by:
- Allowing submission components to be processed in parallel
- Providing the ability to conduct real-time document validation with internal/external standardized datasets
- Performing ongoing background compliance checks
- Automatically generating policy documentation
- Delivering binding agreements via electronic format
Commercial carriers deploying automation across their organizations realize 70-90% reductions in processing times for standard risk submissions; complex risks generally achieve a 30-50% improvement in cycle times (KPMG).
Conclusion
The implementation of automated underwriting systems provides measurable benefits across key performance indicators, including expense ratios, underwriting accuracy, and customer acquisition metrics. These systems no longer represent merely operational improvements but have become strategic necessities for maintaining competitive positioning.
For carriers seeking market leadership, automation investment delivers the dual advantage of cost efficiency and enhanced risk management precision. The technology ecosystem has matured to a point where implementation barriers have significantly decreased, making now the optimal time to deploy these solutions to secure market advantage.
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