Why AI Isn’t a Problem of Insurance

It is evident that billions of people rely on insurers, but the enormous problem that the sector faces is sometimes overlooked. The rising frequency of natural disasters has caused unheard-of losses, which have skyrocketed deductibles and premiums. In addition to the criticism levelled at insurers for leaving high-risk sectors, the rate hikes and underwriting limitations put in place to deal with the mounting losses could not be sufficient in the long run.

The enormous potential of Artificial intelligence (AI) to provide the agility and insights that the sector sorely needs to reinvigorate, reimagine, and even future-proof itself cannot be understated. AI in insurance has advanced from basic ideas to very creative and complex applications in a truly revolutionary way.

The use of GenAI enhances customer personalisation and frictionless experiences while creating a wealth of new options for insurers. Massive linguistic models (LLMs) in artificial intelligence (AI) have allowed us to access powerful AI technologies that will expand this potential. According to SAS’s recent poll, 94% of APAC firms have set aside money for GenAI investments in the upcoming fiscal year. In order to fully exploit this promise, insurers will need to dedicate their attention in the upcoming years to creating reliable AI, supported by strong moral principles and watchful human supervision.

These five urgent technical concerns should be the insurance community’s top priority above all else.

1. The quality of data and regulatory compliance

In order to spur innovation and obtain a competitive edge in the market, data is still essential.

The Monetary Authority of Singapore (MAS) outlines the regulatory expectations and best practices for data governance and management within banks and financial institutions. Key focus areas include data quality management, data risk management, and ensuring compliance with MAS guidelines, ensuring adherence to robust governance frameworks for data management.

The provenance and management of data must come first before developing AI capabilities. Errors and inconsistencies in their massive data sets should be removed to improve decision-making accuracy and reusability, as well as productivity and result reliability. Encouraging data literacy inside the company and providing all teams with the tools they need to discuss, comprehend, and implement ethical AI practices are equally vital.

2. Data governance as responsible AI’s pillar

The significance of robust data governance in ensuring the effective deployment of AI cannot be overstated. According to a survey conducted among APAC respondents, one of the most common worries in this field is customer or client data misuse (34%). It is obvious that stringent quality and privacy regulations are needed to ensure ethical AI practices when using large language models (LLMs) for business applications.

Insurers must build a strong infrastructure and avoid “black box” solutions that lack the requisite openness and explainability in order to deploy AI responsibly and safely. They should investigate more extensive generative AI use cases beyond massive language models, but their primary focus should be on integrating AI into current systems as part of a defined business strategy with robust governance. For instance, creating synthetic data can optimise pricing, reserving, and actuarial modelling while enhancing data privacy.

3. Using data for good

The World Health Organisation claims that preventable behaviours are to blame for almost 30% of cancer-related deaths worldwide. Insurers already gather a lot of health information in order to offer coverage, so they now have the chance to use this information to change the world and go from being reactive indemnifiers to proactive partners for both businesses and policyholders.

Insurers may, for instance, employ smartphone apps to give AI-driven health coaching that offers customised guidance to enhance customer satisfaction while lowering insurance payouts. Partnerships in the fields of ESG and climate change could resolve solvency problems and enhance the industry’s reputation in addition to wellness.

4. The balance between fraud prevention and consumer convenience

Over time, there have been significant changes in what customers anticipate. These days, people anticipate ever-more customised goods and services in addition to “simple” transactions, such as opening a bank account or purchasing insurance. However, because it is so simple for customers to join up online, fraudsters and hackers also benefit from this. As a result, insurance premiums for customers will eventually increase if insurers are unable to accurately identify those customers who are most likely to commit fraud or who are just an unwanted risk.

Organisations need to simplify risk management, client acquisition, and service—ideally all on a cloud-based platform—in order to succeed. Integrating the functions of fraud analysts, underwriters, and actuaries guarantees that insurers manage risk responsibly, provide excellent customer service, and uphold fair pricing.

5. Reducing obstacles to entry for the uninsured community

Life insurance, as opposed to property insurance, focuses on safeguarding the one thing that all people possess—life. The death of a person can cause financial hardship and impoverish the grieving. Despite the fact that life insurance can lessen this burden, historical constraints and access issues keep a large number of people without insurance.

Here’s another area where insurance may contribute to positive change. Insurance companies may use digital platforms to reach a wider audience, educate and protect more people, and potentially end the cycle of suffering that occurs throughout generations if they have access to reliable data and a framework for ethical pricing. Everything boils down to data.

The essential human touch in insurance

The insurance sector is confronted with intricate and interrelated difficulties. While artificial intelligence (AI) and technology can help with a variety of problems and provide traditional insurers with a competitive edge, human inventiveness will be what really shapes the future and makes the most of these developments.