The power of disruption: Digital transformation in insurance
The emerging roles of AI technologies for the insurance market are creating new opportunities for innovation.
Scale, brand heritage and proprietary technology are the very things that are becoming hurdles for insurance innovation.
The insurance industry is rapidly undergoing a digital transformation, enabled by artificial intelligence (A)I technologies such as machine learning (ML), neural networks, natural language processing (NLP) and computer vision. This evolution will fundamentally change the insurance industry from its current state of “detect and repair” to “predict and prevent,” transforming every aspect of the industry in the process.
To remain relevant, traditional insurers will need to move quickly to infuse AI throughout their strategy and operations. A report from PwC forecasted that AI’s initial impact would primarily relate to improving efficiencies and automating existing customer-facing underwriting and claims processes. Over time, its impact will be more far-reaching; it can identify, assess and underwrite emerging risks and identify new revenue sources, impacting nearly every aspect of the insurance industry.
Although some insurers have realized the need to invest in AI to slash costs and enhance customer experience, they will need to increase the scale of deployment to reap the benefits and compete effectively.
AI technologies are poised to reimagine the entire insurance lifecycle. It already impacts many points in the customer journey, such as claims, underwriting and new business. These technologies can handle an ever-expanding range of tasks faster and more accurately than humans while freeing employees to focus on complex and higher-value activities.
AI as a capability
While many insurers are starting to see benefits from AI applications, the companies driving significant returns are approaching AI as a capability —not a tool. Insurance carriers can thus gain a competitive edge once they broaden their focus and include the following six areas of AI in their operational strategy:
- Machine learning: Machine learning enables computers to automatically learn from data without human intervention and without being explicitly programmed. It is writing a new chapter in the old insurance book.
- Natural language processing: NLP will play a critical role on the road to digitalization due to the continuous advancement in its algorithms. AI is becoming proficient at understanding spoken or written language and at facial recognition, helping to make it more useful and intuitive.
Insurers have a unique opportunity to leverage multiple data sources to create deeper customer relationships and become more efficient. NLP applications have been increasing as more companies find uses for their text data. This includes insurance companies with large stores of data from claims and customer support tickets. Apart from the usual data entry, NLP can help underwriters pull up relevant data on the risks they are writing using search-based analytics to speed up data access.
- Behavior data models: Data has always played a central role in the insurance industry. Today, insurance carriers have access to more of it than ever before. We have created more data in the past two years than the human race has ever created before. Insurers are overwhelmed by the explosion in data from a host of sources, including telematics, online and social media activity, voice analytics, connected sensors and wearable devices.
Most insurance companies process only 10-15% of the data they have access to, most of which is the structured data they house in traditional databases. That means they are not only failing to unlock value from their structured data but also overlooking the valuable insights hidden in their unstructured data. They need machines to process this information and data models to unearth analytical insights.
Behavioral data models can be used to analyze the real-time customer data from IoT devices for precise risk classification and product innovation. Using that data, insurance companies can launch new products that incentivize life insurance customers to lead healthier lives, or auto insurance customers to drive safer.
- Internet of Things: IoT-connected insurance represents a new paradigm for the insurance business. This new approach is based on the use of sensors to monitor the state of an insured risk. IoT technologies enable insurance companies to determine risks more precisely. Digital networking through the IoT can allow insurers to significantly reduce costs and generate additional revenues.
- Voice authentication: Also known as voice biometrics, voice recognition or voiceprint, this is currently one of the most common forms of AI. When you contact customer service, insurers can use AI to validate your identity and gather basic information before being connected to a representative. This frees up time for the employee to complete other tasks. Voice authentication also uses sentiment analysis to automatically and accurately determine emotion and tone in the customer’s voice. When fully integrated with semantic interpretation, this can route calls faster to the appropriate team, and less time switching between teams means more time helping and pleasing customers.
- Computer vision: Also known as machine vision, this is an AI-based analysis of images from sources like smartphones, drones, low-lying aircraft, satellites and dashcams. Machine vision has the potential to virtually transform all the stages of underwriting and claims lifecycles. It can help insurers evaluate a broader range of risk and automate decision-making.
Digital transformation won’t progress in a giant leap or through an abrupt change — it takes time and commitment. To be able to leverage AI effectively, organizations need to focus on customer and business outcomes leveraging the technology. The advantage of adopting digital systems is that as more data is collected, aggregated and analyzed, the AI system gets better and better at improving and speeding up processes. As change accelerates, only insurers with an agile culture and operating model will be able to keep pace with the radical innovation.
By implementing AI techniques with smaller use cases and simpler products, insurance companies can see how the results fare and scale AI adoption from there. Digital transformation with AI-based systems is expected to help insurers boost customer service, improve processes and cut costs, and eventually move from “detect and repair” to “predict and prevent”.
Sumit Taneja is the global lead for Digital EXLerator Framework at EXL. He is responsible for the development, deployment and enhancement of Digital EXLerator Framework (EXL’s proprietary digital transformation framework). Contact him at Sumit.Taneja@exlservice.com.
Rupesh Malik is a content manager for Digital EXLerator Framework at EXL, focusing on enhancing content intelligence and unlocking digital transformation through focused articulation in the form of different collaterals that drive customer engagement. Contact him at Rupesh.Malik@exlservice.com. More information on the emerging roles of AI technology is available here.
Related: