Intelligent Automation: The Road Ahead for Insurers in a Post-Covid World


(By Asheesh Mehra)

The insurance industry is one of the most regulated and oldest business service industries in the world. An industry built on trust and customer care that is still reliant on the human touch by way of complicated, manual, and paper-based processes. As a result of this, customer care, one of the main pillars that the industry has been built on, lacked much-needed quality for a long time now. Customers have to endure time-consuming bureaucratic processes that are often not even tailored to their special needs or demands when it comes to applying for insurance policies.

The New Opportunity

Analysts are predicting that there will be an increased demand for insurance in India because of the ongoing COVID19 pandemic situation. Past experience with Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) has shown that demand for health insurance picks up during epidemics. A recent news report stated that online sales of health insurance in India rose to 30% due to the growing number of COVID 19 cases in the country.

In such a scenario, the slow-paced nature of processes, delays in generating insurance renewals will start to impact a firm’s ability to generate revenue. The sheer volume of business data, mainly comprised of unstructured data , which will account for 80% of world’s data by 2025, needs to be processed and analysed, along with the complex business rules that need to be followed, point towards a desperate need for improvement. Time has now come for insurance companies to look at ways to improve their operational processes through technology innovation. AI has the capabilities to help insurance practitioners to do business much faster, more efficiently, and with greater security.

InsurTech: The inflection point

India stands at the second position, globally, given PE/VC investments in InsurTech (Second only to the US). Artificial Intelligence and Machine Learning have gained a reputation as a silver bullet for the insurance industry. This is mainly due to its capability of automating and delivering greater levels of intelligence to specific insurance and business processes. What is more, with the help of AI, insurance companies can improve the overall efficiency of their operations.

Many insurance companies have started adopting and implementing different AI technologies in their operational processes in a bid to not only improve their customer experience but also their bottom line. One of them is Intelligent Automation (IA), the holistic automation of business data of all kinds. Many Insurers are looking to expedite renewal policy quotes with automation to gain faster and more customer centric results. IA can process large volumes of data and ensure the generation of faster, and more accurate results. In fact, according to a recent McKinsey report, automation can reduce the cost of insurance claims journeys by almost 30 percent.

This is not a surprise considering Intelligent Automation Platforms can analyse and process large amounts of unstructured data, complex business contracts at a fraction of the time compared to traditional insurance processes. IA does this two-fold; firstly, by process discovery, as this can help identify and confirm the feasibility of process automation opportunities, therefore optimising repetitive human-driven processes and achieving enterprise-wide scalability. Secondly, by way of identifying and seeking out clean, readily available data via straight-through processing.

A Global  Insurance Provider automated their lengthy processing period for detailed documents. The large volume of policy management documents which required manual handling, held vast amounts of unstructured data, specifically handwritten text in bold and cursive.  Extracted data primarily handwritten (cursive) and signature, had to be verified for the accuracy of information capture. AntWorks Cognitive Machine Reading solution helped them eliminate manual tasks and increase accuracy.

AntWorks is able to process unstructured data that included handwritten fields (both block & cursive), check-boxes and signatures within the policy documents and contextualise the extracted fields.

IA platforms built with powerful data ingestion modules can read printed and handwritten text scanned documents and images, signatures, and PDFs. This enables insurers to generate more insurance renewal quotes in less time and with better quality. Faster, superior, and more tailor-made insurance renewal quotes will certainly improve the bottom line as well as customer retention and acquisition rates. In addition to this, enterprises will also be able to speed up workflows and unlock new revenue streams.

Taking a Cognitive Approach

Bearing all these factors in mind, there’s an increasing realisation that, if you’re an insurance company trying to automate your business processes to drive growth, your success will depend on your ability to capture and digitise data – and specifically, unstructured data.

Traditionally, being able to capture and digitise data to underpin and drive process automation initiatives has largely been down to OCR (Optical Character Recognition) technology. The problem is OCR falls down when you present it with anything other than neat, nicely structured data.

The ‘data chasm’ caused by unstructured data can include images, web pages, handwritten documents, signatures, and even mobile content. Right now, as an insurer you may or may not be particularly worried about this chasm –  the problem comes when you realise you need to leverage unstructured data to underpin and drive forward your business process automation initiatives in the current climate and beyond.

In the insurance industry, customer interactions will become more personalised in a post Covid era as it will become the new benchmark of competitive differentiator. When it comes to automation, Insurance companies will need to relook it from an end-to-end business process perspective rather than looking it from the lens of a single business process. Taking a cognitive machine reading (CMR) approach to automation will give them a competitive edge because it can capture and curate all types of data, helping them ensure the success of their business process automation initiatives – essential in today’s challenging environment.

(The author is the Co-Founder and Group CEO, AntWorks Pte. Ltd.)


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