Insurers must adopt AI responsibly and ensure it is used on representative, impartial data for training purposes as well as regularly reviewing bias-free systems for use.
As AI becomes more mainstream by 2024, insurance technology will evolve quickly; however, traditional functions must also make adjustments quickly to adapt.
Introduction
AI (Artificial Intelligence) promises to transform every facet of insurance, including customer service, claims processing and even underwriting. Although we can never predict exactly how this technology will play out for each policyholder individually, trends indicate its positive potential.
AI can reduce customer calls by automatically sending status updates based on data. Not only does this save time for human customer service agents, but it also enhances the overall experience for customers.
AI can use data available to insurers such as social media posts, demographic information and environmental conditions to develop customer profiles and determine who needs reengagement the most. This allows insurers to optimize channels, products and targeting of marketing campaigns more effectively.
AI's powerful data analysis capabilities enable it to accelerate and streamline underwriting and pricing processes while making them more competitive, while at the same time helping insurers avoid bias or discrimination in decision making processes. However, insurers must constantly evaluate how AI is being utilized and ensure effective governance to avoid ethical concerns arising.
Risk Assessment
Insurance firms using AI technologies must conduct thorough risk analyses. This involves considering all risks posed by their system and documenting how the insurer evaluates them.
AI can quickly and efficiently analyze large datasets, helping underwriters quickly identify potential risk more accurately and improve policy wordings and coverages as well as premium pricing more quickly and cost effectively.
However, inaccurate or outdated input could compromise AI systems and lead to inaccurate predictions. Furthermore, generative AI systems may be exploited for cyber fraud using convincing but false information called deep fakes - known as deep fakes.
At Armilla Assurance, they specialize in third party coverage indemnifying AI algorithms and models; such policies help mitigate some of the risks presented by artificial intelligence to personal insurance policies.
Claim Process
AI technology offers substantial advantages to insurance businesses when it comes to processing claims. It can expedite simple cases quickly and even allow instantaneous settlement, as well as automate scheduling repairs appointments post settlement.
Insurance carriers have used artificial intelligence (AI) software to reduce costs and enhance customer experiences, but this approach comes with its own challenges. Determining the cause of damage may be challenging when AI software analyzes images of damaged property; misinterpretation such as misinterpreting shadows on roofs as preexisting damage could result in denials.
To address these challenges, insurers should conduct a business analysis of their claims processes. They should identify which aspects are most frequently being complained about by customers and which areas can benefit from automation; after which, custom AI solutions can be created to tackle those problems.
Loans Concerns
AI promises much, but its introduction into the insurance process still poses many risks. One major concern is that AI could become biased; particularly if data collected and analyzed incorrectly. Furthermore, this technology could reinforce certain forms of discrimination such as redlining. (Intro Video)
Banks should ensure their artificial intelligence models are ethically sourced and carefully evaluated to eliminate data bias, while also making certain the AI model explains its decision-making process for maximum transparency and fair decisions - creating trust and accountability between themselves and customers.
AI provides numerous efficiencies and safeguards to the financial industry. For instance, phishing detection apps help combat cyber crime that has cost the global economy an estimated $400 billion while voice and language processing reduce service times and customer frustration when filing simple claims. Likewise, AI-based document processing software assists lenders streamline their document review processes.
