How Digital Insurance is Transforming Business Risk Management

In an interaction with Asia Business Outlook, Lasitha Wimalaratne, CEO of HNB Assurance PLC, has shared his views and thoughts on what compliance risks businesses should know when adopting digital insurance solutions as well as how businesses can ensure the accuracy and reliability of risk assessments while avoiding bias in AI-driven models. Lasitha is a CEO and Chartered Insurer, and has over 27 years of expertise in insurance operations, underwriting, sales, marketing, product development, reinsurance, and project management, with experience at top insurers like Aviva, AIA, Union Assurance, Softlogic Life, and HNB Assurance.

1. Digital insurance is transforming business risk management in unprecedented ways. How do you see this evolution shaping the future of risk mitigation for enterprises?

Digital insurance is fundamentally transforming risk management across the industry. With advancements in data analytics, artificial intelligence, and automation, insurers can now assess risks with greater precision and in real-time. This shift enables a proactive approach to risk mitigation, moving beyond traditional reactive coverage. Significant investments in digital transformation underscore the sector’s commitment to enhancing accessibility, efficiency, and predictive capabilities. Innovations such as instant policy issuance, automated claims processing, and AI-driven underwriting are redefining the insurance landscape, empowering businesses with tailored risk solutions that align with their evolving needs.

2. With the increased use of data and automation, what compliance risks should businesses be aware of when adopting digital insurance solutions?

As the industry advances towards automation and data-driven decision-making, compliance and data security remain paramount. Regulations such as Sri Lanka’s Personal Data Protection Act necessitate stringent data handling practices, requiring insurers to adopt robust measures to safeguard sensitive information. To meet these challenges, the focus is on enhancing data collection through secure digital platforms, implementing encrypted storage solutions, and leveraging AI-driven fraud detection to protect both customer and business data. Furthermore, close collaboration with regulators ensures transparency and alignment with evolving legal frameworks, reinforcing the industry’s commitment to ethical and compliant operations.

3. As digital insurance evolves, regulatory environments are also adapting. What are the key challenges in aligning new digital practices with traditional regulatory frameworks, and how can organizations navigate these challenges?

A key challenge in Sri Lanka and globally is that regulatory frameworks were designed for traditional insurance models, often struggling to keep pace with digital transformation. To bridge this gap, industry stakeholders are increasingly collaborating with regulators, industry bodies, and partners to shape policies that facilitate digital adoption. Innovative solutions, such as online term insurance products, demonstrate how insurers can align with regulatory requirements while offering customers seamless access to insurance anytime, anywhere. Proactive engagement with policymakers remains essential in fostering a regulatory environment that drives innovation while ensuring robust consumer protection.

4. Digital tools can improve efficiency but may also introduce vulnerabilities. How can organizations ensure operational resilience when adopting digital insurance solutions, particularly in managing unforeseen risks?

Operational resilience is a critical focus across the insurance industry, particularly as digital service offerings continue to expand. To mitigate risks, insurers are investing in secure, cloud-based infrastructures with multiple redundancies, ensuring business continuity even in the face of technical failures or cyber threats. The adoption of AI-driven risk detection systems plays a key role in proactively identifying vulnerabilities, while advanced digital solutions enhance protection against evolving security risks. Additionally, continuous training and upskilling initiatives equip professionals with the expertise needed to navigate emerging challenges and maintain robust operational resilience.

5. With the rise of big data and predictive analytics in insurance, how can businesses ensure the accuracy and reliability of risk assessments while avoiding bias in AI-driven models?

AI and predictive analytics, while transformative, will never operate in isolation. Human expertise remains essential to ensuring fairness, precise decision-making, and contextual understanding. The industry's approach must center on integrating AI-driven insights with expert judgment, striking a balance between automation and a customer-centric focus. Rather than merely streamlining processes, the goal is to harness AI to deliver more personalized, transparent, and seamless insurance experiences.

As digital capabilities evolve, leveraging diverse datasets and conducting regular audits of predictive models will be crucial in minimizing biases. Collaboration across industry networks, including parent organizations and strategic partners, can enhance data validation mechanisms, ensuring that risk models accurately reflect real-world scenarios and drive more equitable outcomes.