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ISG Provider Lens™ Insurance Services - Insurance ITO Services - North America 2023
ISG Provider Lens™ Insurance Services - Life and Retirement (L&R) Insurance BPO Services - North America 2023
ISG Provider Lens™ Insurance Services - Life and Retirement (L&R) Insurance TPA Services - North America 2023
ISG Provider Lens™ Insurance Services - Property and Casualty (P&C) Insurance BPO Services - North America 2023
Insurance carriers will progress gradually toward becoming fully data-driven and tech-enabled
Insurers face some unusual challenges such as responding to the rapidly evolving risk landscape due to extreme weather conditions, increased cyberattacks and their ever-changing forms, consistent hyper-inflation scenarios amid perpetually uncertain macro-economic situations. Catering to the fast-changing insurance needs of customers with the correct value proposition at an optimal price is tough within the present business and IT landscape.
Building a customer-centric and a business optimum insurance proposition requires considerable experimentation and newer strategies. It gets restricted by the layers of processes, decades of legacy culture within insurance organizations, siloed legacy technology and lack of required data granularity.
The modest efficiencies brought about by digitization for insurers are insufficient since they fail to protect policyholders from wandering and suffering unpleasant shocks.
Insurance carriers’ digitalization should and must focus on:
● Eliminating customer journey difficulties that generate policyholder dissatisfaction
● Boosting the value it delivers in the form of insurance
● Helping the insurer strike a balance between the desired service and the post-claims trauma stage.
Insurance carriers must persistently and relentlessly try to find out:
● Which friction points jeopardize policyholders’ trust and the variables influencing policy persistency rates and long-term loyalty
● How they can make their business designs responsive enough to the needs of policyholders and potential customers
● What kind of IT systems they require to track fluctuations in policyholders’ sentiment
While AI for insurance has generated a lot of talk and enthusiasm among insurance executives and ITO service providers, it is important to realize AI just anticipates what data or references it should deploy next without any knowledge.
AI is simply a prediction model using a large amount of data; cultivating and harvesting the appropriate level of data granularity will be the most critical AI capability differentiation among insurers.
AI is worthwhile for insurers to look at services that project their unique AI models and have favorable terms and conditions to ensure they want to retain copyright or intellectual property rights (IPR).
AI is only expected to perform within the boundaries programmed to be successful.
Hence, one cannot depend on it to deliver an intelligent reaction or solution outside its designed and defined capabilities.
Lack of access to first-party data sources and data privacy will continue to haunt insurers because creators hardly built AI with security in mind. Insurers must implement controls to guarantee that data does not egress from the model, which is feasible in both classical data plus machine learning and large language models (LLMs).
Pre-digital incumbent insurers and insurtech startups should focus on solving customer problems and issues in the larger insurance value chain, including engineering, support, operations and intermediaries channel
challenges that AI can solve. Anything that works well for internal problems may eventually be exposed to external users.
Most pre-digital incumbent insurers will seek to excessively use AI to optimize pricing, distribution, claims leakages and other aspects, denying the powerful AI from leading to organizational change (business design,
operating model, product innovation/roadmap, customer journeys or organizational culture).
Insurers of the future will be those who will think more rationally and ask their people across all levels: “What can AI optimize?” and “How will it benefit our customers and us?” Their leaders will embrace AI thoughtfully and orchestrate efforts toward democratizing AI use throughout the insurance organization and across its value chain.
Considering its superior analytical and performance capabilities, AI will be pivotal in:
● Simplifying and streamlining the complex products, their construct and underlying processes, and corresponding customer journeys that define the insurance industry
● Attaining the required cost optimization across the insurance value chain
Insurance will remain a distribution-heavy business. This means AI will have to have a profound intrinsic impact on the operating model and its underlying business design of insurance carriers to make them more
customer-centric and more profitable.
AI will not be able to deliver much tangible business benefits to insurers without a paradigm shift in where AI should be applied, its clearly defined objectives and which opportunity costs are being let go to make its
Constantly changing customer expectations, a complicated, rapidly growing regulatory structure and skill shortages are some of the issues the insurance sector faces worldwide. Insurance chief executive officers (CXOs) should focus on unlocking the full potential of data, technology and people, and they should be open to new procedures to drive transformation and growth.
Insurance CXOs must regularly identify the business and IT skills necessary and cohesively collaborate with those who can support them. It will adequately equip them to assist carriers in accomplishing their goals.
Insurance companies must continually innovate in all aspects of their business to remain relevant in today’s market. By utilizing strategic managed services, insurance carriers may gain access to digital capabilities, process expertise and specialized talent more efficiently.
All these require a continued holisitc approach to partner strategically with insurance services providers in the digital change journey of insurance enterprises.
They require a strategic partner that is ready to put ever more skin in the game to ensure the success of experimental approaches. The partner should help create and deliver an innovative operating model through its continued investment, upskilled and talented business and technology workforce at all three delivery models (offshore, nearshore and onshore) to ensure an uninterrupted business as usual (BAU). It should also help pilot innovation at a large scale to future-proof its clients’ business and differentiate its offerings in this competitive market.
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