By Vinod K Singh
AI underwriting is a game-changing advancement in the insurance sector that leverages artificial intelligence and data analytics to enhance the accuracy, efficiency, and personalization of the underwriting process. Underwriting, traditionally a manual and time-consuming task, involves evaluating risks associated with potential policyholders and determining appropriate coverage and premiums. The integration of AI technologies into this process has the potential to reshape the industry by offering quicker, more accurate risk assessments and personalised policy offerings
When we started Concirrus 10 years back, our fundamental belief was that behaviour is better indicator of risk than other traditional methods, but challenge was around how do we harness enough data to extract behaviour of insurable assets and over last 10 years there has been several technical advancements such as IoT, Cloud Computing and Machine Learning which made new types of data available and computing advancement helped process this huge amount of data and together with these evolution we were able to help insurers build a more dynamic and advance pricing models that leverages huge amount of data, several thousand rating factors and predicts the risk and help insurers to offer competitive price to the policy holder.
Potential with Evolution of AI Underwriting
- Enhanced Risk Assessment: As AI algorithms continue to improve, underwriters will have access to even more accurate and comprehensive data. This will enable them to assess risks with a higher degree of precision, resulting in more tailored coverage and fairer premiums for policyholders.
- Real-time Underwriting: With AI, the underwriting process can become almost instantaneous. Insurers will be able to evaluate risks and provide quotes in real-time, enhancing the customer experience and speeding up the policy issuance process.
- Automated Claims Processing: AI underwriting will extend beyond policy issuance and premium calculation. Machine learning models can analyse claims data to detect fraudulent activities, assess the validity of claims, and expedite the claims settlement process.
Key Challenges to be addressed to harness true power of these technical evolutions
Each evolutionary leap introduces its own set of challenges, and the ongoing evolution towards a connected world and the integration of machine learning is no exception. While this progression holds immense potential value for the industry, it concurrently presents substantial challenges for insurers to grapple with –
- Data Deluge: The process of digitization has engulfed virtually every aspect, leading to an overwhelming surge in data volumes. For insurers, this influx of data, while rich in potential, also presents challenges. The potential of AI, Machine Learning, and Cloud computing remains unrealized unless fueled by analytics and AI-prepped data. However, transforming this massive and disparate data influx into analytics-ready form demands significant exertion and necessitates multimillion-dollar investments. Central to this predicament are questions of economic feasibility: how to achieve this transformation cost-effectively and efficiently? How can this data be curated and tools be developed to harness its potential optimally?
- Data Privacy and Ethics: Collecting and analysing personal data for underwriting purposes raises concerns about privacy and ethical use. Striking a balance between data utilisation and individual privacy is essential to maintain trust with policyholders.
- Bias and Fairness: AI models can inherit biases present in historical data, leading to unfair or discriminatory outcomes. It’s critical to develop models that are free from biases and ensure that underwriting practices remain fair and unbiased.
Conclusion:While AI-powered underwriting offers significant advantages in accuracy, efficiency, and personalization, its adoption requires careful consideration of these challenges. Insurers must navigate the complexities of data quality, ethics, fairness, regulations, and integration to successfully implement AI underwriting and realise its full potential in transforming the insurance industry.
The author is serial entrepeneur, tech visionary, advisor