AI in Insurance – Sector at the Cusp of Transformation

Written By : Nishant W
Date Posted : 24 May 2019

Automation and AI are often used interchangeably, however there is a vast difference between the two. Automation deals with making rule based systems, which enable a hardware/software to do a task on its own – with no human intervention involved.

On the other hand, Artificial Intelligence is a science of making intelligent machines. AI is designed to simulate human thinking and is about trying to make machines or software mimic, and eventually supersede human behavior and intelligence. It is one level above automation as it gives ability to computers to learn without explicitly being programmed.

An independent survey suggested that 56% of the CIOs of Insurance companies quote that multiple business issues across the value chain can be solved by “improving operational efficiencies”.

Insurance Industry is a data heavy industry which sits on a pile of huge data. With the advent of tech based companies, the traditional paper based insurance companies will have to find a way to improve operational efficiencies and strive hard for customer satisfaction. AI in insurance is definitely the way forward. There is news that tech companies like Google, Facebook Amazon have huge data with them about people – which sooner or later will be used to made customized insurance offerings, post all approvals in place. Once this happens, it will be a revolution in the insurance industry and if existing players don’t want to miss the bus then they must brace themselves for intelligent automation in insurance. This intelligent automation in insurance will not only help in reducing turnaround time but also lead to increased efficiencies and customer satisfaction in an already competitive sector. Artificial Intelligence in insurance has the potential to allow companies to do things differently. Intelligent automation at scale with increased efficiencies will lead to cost reduction which helps is reducing the premiums to stay competitive.

Talking about the hierarchy of data – at the bottom there is raw data which is characterized by 3 Vs – huge volumes, variety in the data and the velocity with which data is processed. This data can be from different media sources and in unstructured format. Machine learning sits on top of this layer which has the ability to self-learn and identify solutions for problems for which it is not coded. Followed by this, there are applications like RPA, chatbots, email bots which remove human intervention. These bots can help insurance automation scale with applications like reverting to thousands of queries online in real time, detecting fraudulent claims etc. Thus machine learning in insurance can reduce help in saving time and remove errors in fraud detection all leading to improved efficiency.

Despite challenges, many organizations are using cognitive technologies to relieve various business pain points. Here is how they achieve it:

Use Cases for AI in Insurance Sector
  • Cognitive AI: The combination of RPA and data science, robotics and cognitive automation involves the automation of repetitive manual tasks and workflows by allowing RPA bots to replicate human actions and judgments.
  • Cognitive insights: Cognitive technologies such as machine learning (ML) and natural language processing (NLP) can find complex patterns in data that are not easily identifiable by humans and help organizations make better decisions and more accurate predictions.
  • Cognitive engagement: Used for answering customer queries to providing technical support to employees, an increasing number of applications with minimum or no human involvement.

Chatbots in AI: Artificial Intelligence (AI) will enable the use chatbots, where claims requests, if met with a certain predefined conditions can be routed for automatic handling. The chatbots will be capable of detecting frauds there by reducing the manual effort. AI using Chatbots can enhance customer experience by personal interactions using customers geographic and social data.

Behavioral policy pricing Ais another yet another application of AI in Insurance where people who are healthy or people who have safe driving history will have to pay comparatively lesser premiums.

Insurance Analytics: Insurance Analytics is emerging exponentially as it Internet of Things (IoT) and Data science enables predictions based on real events using large data sets rather than analysis on samples collected in the past. These IoT based sensors calculate premiums and link it to an individual rather than mapping it to a group.

Huge piles of paper are generated when policy is issued and during claims process. Manually entering this data into sheets is a time consuming and as well erroneous task. Robotics Process Automation (RPA) can read and extract information from these scanned documents, use OCR capabilities to read, use smart references, machine learning and NLP capabilities to process data. Integrating this system with current processes can lead to intelligent automation at scale and companies can stay ahead of the curve. While using RPA in insurance, over automation should be avoided, this means that if there is a task which will be performed only once, in the entire life cycle of the project then there is no need to using RPA for this task. This is because RPA in insurance will come with its own cost associated with it.

Looking at the below table gives us a sense of the rising demand for chatbots and its acceptability among the audiences:

Allstate launched chatbots which enables agents to learn about different ways to sell commercial insurance products for the first time. It gives the agent a walkthrough of entire process, helps them if they are stuck in the middle and can even help in retrieving documents.

Indian insurance player HDFC adopted AI tech to run a questionnaire to help people solve their queries related to insurance via mobile chatbots platform. This enabled them to handle huge amount of queries with minimum errors, and quick response time.

Another example of how AI can be used in Insurance space is to transform user experience using a speech recognition application combined with artificial intelligence that will enable customers to check balance premiums, claim status and solve all insurance related queries at ease.

MACHINE LEARNING

Technology

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