The Power of AI for Insurance: Can your Advisors tap Iron Man’s powers?

Combining human intellect and creativity with the processing speed and power of AI will be the key to creating more meaningful and long-lasting customer relationships.

(Man of Steel sculpture proposed for Rotherham, Yorkshire. Image by sculptor Steve Mehdi.)

There was a time when Artificial Intelligence (AI) was an idea brought to life on the silver screen. If you’ve watched the Iron Man movies, you’ll remember JARVIS (Just a Rather Very Intelligent System), a highly advanced computerized armor that interacts intuitively with Iron Man, billionaire Tony Stark. What’s more, JARVIS has a complete understanding of Stark’s history, habits, behavior and preferences, allowing him to not just respond to instructions but also provide contextualized recommendations and prepare better by predicting Iron Man’s next move.  It wouldn’t be too farfetched to say that it is JARVIS that makes Iron Man successful.

Imagine a similar AI system that works as a personal agent or advisor for your customers. As a Virtual Personal Assistant (VPA), such a system understands the contextual needs of customer, offers relevant and personalized advice, and more. In today’s hyper-connected world, AI is the logical next step to providing value added insurance services and enhancing the overall customer experience. 

Ready for business: Exploring the potential of AI in Insurance

With exponential growth in data, advances in analytics, and surge in cloud adoption, AI is at its tipping point. Massive leaps in AI – across areas of machine learning, natural language processing, predictive modeling, and cognitive computing – have changed the way information is processed and leveraged for business advantage.  By using AI, insurers can target digitally savvy segments such as young professionals and DIY investors who seek active and reasonably priced assistance, at a time and place convenient to them.

Here are some of the ways in which AI-powered software can transform the insurance industry

Customer service: Financial services providers are using cognitive computing technology to help customers set and progress towards personalized goals. Users receive access to a diverse range of complex questions around education, health insurance, housing, and retirement. By consistently learning and adding value, solutions like these offer several advantages over scripted systems and rule-based decision trees that need to be constantly updated to ensure currency and relevance.  Customers can also complete routine tasks such as bill payments and claim filings using voice self-service.

Portfolio planning and advisory: Robo-advisors are set to transform personal financial planning and wealth management. Not only do these systems provide rapid responses, they also take into account several independent factors and dimensions to deliver customized and relevant advice. For instance, brokerage and banking companies use computer algorithms combined with professional insights to build, manage, and rebalance client portfolios. In these programs, investors receive portfolio recommendations based on their stated goals, time horizon, and risk tolerance. Moreover, these services are complimentary, without advisory and account services fees or commissions attached, which goes a long way in building customer confidence and brand loyalty.

Lead management: Insurance agents deal with a high volume of prospect interactions. With lead volumes increasing, timely follow-up has become a challenge. Virtual sales assistants help carry on a natural two-way dialogue to engage and qualify leads, reducing the grunt work done by agents. Sales teams can instead channelize their efforts towards personalized interactions and building relationships with customers.

IT optimization: AI platforms can also be used to automate and optimize IT operations and processes to increase agility, reduce operational risks, and enhance user experience. Neural automations systems, which function like the human neural system, are designed to sense, think, and act for the enterprise.  They can run a wide variety of IT processes autonomously with minimal human intervention. These include daily business checks before starting operations, rapid resolution of IT incidents, automated systems provisioning and more.

Other applications: AI can also automate underwriting and identify fraud through pattern recognition and deep learning techniques. Autonomous learning enables AI powered systems to identify anomalies and recognize duplicate claims by analyzing key information.  AI is also expected to transform claims management because of its ability to extract actionable information from massive amounts of data accurately and consistently. It can accelerate claims assessment and identify claims leakages while reducing costs and improving customer engagement.

Where do we go from here?

It is evident that AI has moved beyond the silver screen and is weaving its way into the business world. In the insurance industry, it has the potential to drive product, service, and process innovation. However, insurance is as much about managing human emotions as it is about mitigating risks and meeting investment goals. AI platforms cannot be expected to run on auto-pilot just yet, and may require human checkpoints. An AI system embedded with a certain amount of emotional intelligence can bring in the human element missing in interactions with machines. Combining human intellect and creativity with the processing speed and power of AI will be the key to creating more meaningful and long-lasting customer relationships.

Arunashish Majumdar // Arunashish (Arun) Majumdar, Chief Architect, leads TCS’ Insurance technology practice in North America. He specializes in transformation initiatives that improve customer experience, business agility, operational efficiency, and technical currency. He has handled strategic initiatives to define and deliver enterprise digital strategy, IT portfolio simplification, and core systems modernization for several TCS customers.

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