How advanced analytics helps insurance sector by improving revenue visibility

With advanced analytics making a foray into the insurance sector, enterprises are cashing-in on the technology to track and enhance sales productivity, creating robust performance management dashboards, and forecasting sales for improved revenue visibility. Nimilita Chatterjee, Partner, Financial Services Analytics Advisory at EY India, gives the entire rundown on the process, the roadblocks and the future of advanced analytics in the insurance sector.

Edited excerpts:

With more advanced analytics coming into the picture, how do you think it can benefit the BFSI sector, particularly Insurance? Also, what added advantage will an insurance company have with advanced analytics over the regular analytics tools?

Analytics is being given a great impetus with the advent of new data sources, tools, techniques and technologies across industries. Advanced analytics tools and techniques are now in a position to use structured and unstructured data from various internal and external sources in real time/near real time, process large amounts of this data and direct action on customers. This is driving better and more personalized customer experiences across industry sectors.

In BFSI, advanced analytics allows organizations to leverage their entire gamut of internal data that has been unexplored in the past such as audio files from the call centre, emails and chat interactions that the customer has had with the institution, mobile app interactions and transactions etc. In conjunction with the customer’s increased digital footprint and e-enabled processes, the amount of alternate data being created is adding to the overall pool from where better insights and therefore improved experience can be driven.

In insurance, analytics can be used in general insurance as well as life insurance across the lifecycle of the products and the customer. Right from targeting the right products to the right customers, being able to increase persistency on the policies, early claim prediction fast tracking claims and automating processes for claims management as specific use cases in which analytics can be used. Insurance companies are using analytics to manage some of their internal processes like sales performance and reducing frontline sales attrition through analytics driven right profile identification at recruitment.

How has been the adoption of advanced analytics in the insurance sector in India?

There has been a steady increase in the adoption of analytics across the insurance sector in India, both across life and general insurance. Analytics has been used in improving/enhancing customer experiences, targeting the right customers with the right products using tools like cross sell propensity models, customer retention analytics and customer management using customer lifetime value models.

Analytics is also being used in business process improvement to track and enhance sales productivity, creating robust performance management dashboards, forecasting sales and renewals for improved revenue visibility and forecasting demand at call centres to improve operational efficiency. Digital marketing analytics is being undertaken to track digital asset adoption and measurement of its effectiveness. Analytics is also being used to strengthen risk management by embedding analytics in internal audit and estimating the risk of early claims etc.

What are the key roadblocks in the adoption of advanced analytics? Also, how can we overcome these challenges?

As organizations become more analytically driven, the outcomes of models and analytics would challenge the traditional ways of doing business. Adoption is driven by the top management of the organization by setting up a clear analytics agenda and driving that agenda relentlessly. Starting small and getting early successes in analytics is important to evangelize the benefits from analytics clearly.

Setting up clear and measurable outcomes from analytical interventions is key so that the benefits can be communicated in actual value delivered. Investment in talent in analytics with a dedicated team of people who work closely with the business is imperative to delivery of value from analytics.

With buy in from the senior management, a clear business agenda to solve, and investment in talent, the team needs to be enabled with the requisite investments in technology as well.

Can you share some success stories with real benefits to the organization, where EY has played a key role?

EY works with multiple general and life insurance providers. We have setup and currently operate multiple Analytics Centres of Excellence for Insurers over multi-year engagements. We have helped our clients drive breadth of analytics usage (developed analytics solutions for team’s who were not using analytics earlier), improved depth of analytics usage (created solutions that didn’t exist) and improved accuracy of existing models using advanced techniques (e.g. machine learning).

We’ve supported setting up the Analytics led Transformation CoE for an Indian Life Insurer where we have developed analytics roadmap for capability build – up and helped the client build innovative analytics led solutions on Sales Forecasting, Branch Profitability based segmentation, Sales Force management and CXO level dashboards. We have also trained the client team members to take over roles and run the team themselves.

We have built pre-packaged algorithms for key standard business problems which help us accelerate the set up and enhance the capabilities of our client’s analytics teams. These are solutions built around persistence management, automated insights for enabling sales and early claim prediction to name a few.

How is EY helping insurance companies in India with its offerings?

We work with multiple insurance companies in India. We have delivered analytics projects across underwriting, cross sell, customer management, distribution, digital, planning, claims and risk functions where we have leveraged machine learning based predictive algorithms and interactive visualizations for process improvement. We work with these organizations to deliver specific projects, built out their analytical capabilities in the center of excellence build model and help them with their data organization, data governance and data quality area as well. We provide end to end services in analytics from data engineering to advanced analytical modelling, implementation and tracking of various analytical initiatives to drive adoption of analytics in the insurance industry.

What does the future hold for the insurance companies in India, and what role can advanced analytics play there?

India is an under insured country across life and general insurance. There are multiple areas where this industry is focussing right from increasing adoption of insurance, calculating the right insurance amount for individuals and making the claim experience easier and more digitally enabled. While on one end the adoption of insurance is a key agenda there is also a big push to digitize underwriting processes and claims in the industry.

Better customer experience, optimized cost, lower documentation etc are all initiatives that are being worked upon. The future holds immense potential for single click based policy issuance, single click claims management enabled by artificial intelligence along with recommendation engines for what products one should be buying when, customized insurance offers etc. All of these will be enabled by advanced analytics - artificial intelligence enabled virtual assistants, audio, image and video enabled claims processing etc.

The future also holds promise in terms of customized pricing for life insurance based on health status and lifestyle and in motor insurance linked to driving style and locations etc. These pricing options would need regulatory reform. In conjunction with the digital revolution and the advances in analytics, the applications and benefits in the insurance industry are limitless.

Source: The Economic Times