The Insurance industry benefits from advancements in applied AI, owing to the massive influx of automation tools for improved process efficiencies.
Industry experts say that the next decade will witness a massive adoption of cutting-edge AI for security and governance platforms used by insurers. This is because the risk of fraudulent claims is on the rise, and as is the urgency for a transparent but fully secure data architectures to govern insurance practices.
Applied AI is when Artificial Intelligence is applied to real world scenarios like automating sales workflows or building intelligent conversational bots, enabling systems with enhanced capabilities to perform tasks faster via automation. By augmenting processes with AI & ML integrations, applied AI deals with the impact and incorporation of AI tools to improve business output.
AI & ML is already endorsed by organizations like Microsoft, IBM, Amazon, etc., introducing advancements in RPA and the various applications of AI tech.
McKinsey’s report on Insurance 2030 – The Impact of AI on the Future of Insurance states that “Around 50% of the insurance claims will be automated by 2025 owing to advancements in applied AI and Machine Learning techniques.”
Building user interfaces to challenge the evolving nature of web 3.0, intelligent analytical tools and high-performance AI workflows are key to securing insurers with compelling investment opportunities and industry partnerships.
No other industry needs reinforced system security like insurance. A single cloud data breach could cost customer’s their lifetime value of assets, the company their reputation and the market could turn volatile as pent-up demand for resources hits the roof. Thus, a better way to govern the insurance practice is every insurer’s imminent need.
This post summarizes how insurers can leverage the latest technology trends for better, more secure, and predictable business outcomes.
Listed below are 5 key areas of advancement in InsurTech tools that insurers can leverage in 2022.
The use of IoT in telemedicine, fitness and BFSI are promising derivatives of the future of insurance. With wearable watches and smart devices that can monitor anything from blood oxygen levels to heart rate – people are more informed about the decisions they must take for a better-quality life. Insurers can thus capitalize on the IoT wave with affordable premiums delivered to users who find expediency with the insurance product’s competitive perks offered.
An example of IoT in insurance would be flexible insurance policies for self-driven cars where data from accidents are made available to insures to take the right course of action on time. As AI evolves, the use of drones for public and private transport is also a means by which financial systems and trade will be impacted.
Insuring valuable goods and purchase orders in retail will inevitably lead to BFSI operations that can armour customers with economic dividends to boost business output.
Insurers face massive losses due to fraudulent claims, exposing the need for more efficient claims processing and risk mitigation techniques within the enterprise systems. This implies that Insurance companies are more vested in technological ease afforded to customers and employees than ever before.
With the added advantage of AI based predictive analytics – insurers can ensure that facilitating great experiences coincide with the vision for secure, seamless, and viable transactions.
Shown below is a Data Science Workflow that helps in effective insurance automation.
An example would be special character authentication or digital signatures used to authorize data at various touchpoints of the insurance practice. The digital traces assure that fraudulent claims are constrained by the authenticity of historical events recorded in a centralized system. This is good news for insurers looking to save millions in claims processing charges that don’t meet the intended beneficiaries.
As per a recent report by IoT Analytics, the total number of connected IoT networks is estimated to exceed by 9% of all existing 12.3 billion feedback channels in 2022. It is forecasted that by the year 2025, there will be close to 27 billion IoT connections going live. Smart devices, applied AI and global connectivity ensures that insurers gather real-time insights on consumer behaviour and wants, addressing the demand for effective policies, products, and possibilities.
How underwriting in insurance works now, is not how it’s going to be in the coming year. Applied AI that can scan and consolidate vast sums of data is already helping insurers combine business intelligence with progressive needs of their ideal customer of the future.
Financial planning and investment forecasting are key areas of the insurance practice, depending on which insurance policies can appeal to insurer and customer alike. Having efficient billing consoles is not all, but the ability to translate each transaction in the database into business tools that offer fiscal autonomy to the end user.
Automation using applied AI is paving way for efficient billing systems driven by faster feedback channels for flexible workflows in InsurTech. An example of efficient billing systems for financial planning are omnichannel gateways for customers to personalize their insurance benefits based on current and future needs, leveraging flexible payment integrations across a single network of administrators. This allows for insurers to tap into a global market, unrestricted by centralized policies.
Every insurer offers something unique to the customer, and not all InsurTech inventions were created equal. For example, citizen development using low code tools was a far-fetched reality just a decade ago. Today, insurers can empower their workforce with tools to create, optimize and accelerate digital transformation efforts within their organization. Employees become more involved in the growth of their company and the insurance practices can leverage modernization tools faster. This allows for a clearer understanding of customers and helps insurers prioritize high value customers to diversify key offerings accordingly. Quicker product time-to-market and optimally governed processes are key benefits of personalizing the user experience with data-driven workflows.
Data-driven pricing strategies are also a clear example of how personalized insurance offerings are succeeding the traditional subscription-based alternatives restricted by the legacy system architectures.
With increased transparency into the insurance practice and related processes, technological agility is a bonus for insurance companies of the day. If not for IT disruption, most legacy processes would have hindered industrial growth and led to inconsistencies in national and global markets. This resolve is pivotal to adopting smarter and more economic ways of doing business – which is to personalize the experience for people who put faith in your product, ensuring that your business agility raises the bar for competitors in the industry to accomplish.
Bill Gates says,
“Information technology and business are becoming inextricably interwoven. I don’t think anybody can talk meaningfully about one without talking about the other.”
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