Leveraging AI to drive operational improvement

By Johan Reyneke, Customer Engagement Lead at SilverBridge Holdings

Companies are using artificial intelligence (AI) as a tool to generate value. This is hardly surprising given the rapid push to modernise systems and embrace digitalisation over the last two years. Organisations are therefore likely to increase their AI investments as they look to become more efficient and deliver a better customer experience given current global uncertainties coming out of the COVID-19 pandemic.

Half of respondents in a recent global survey have indicated that their companies have adopted AI in at least one business function. And while these functions remain largely unchanged from 2019, with service operations, product or service development, and marketing and sales again taking top spots, this reinforcement highlights how important customer-centricity is in the business value chain.

According to this McKinsey survey, the largest share of respondents has reported revenue increases for pricing and promotion, customer-service analytics, and sales and demand forecasting. More than two-thirds who report adopting each of these use cases say it has resulted in increased revenue.

Insurance focus

For their part, insurers have also turned to AI to cut costs, reduce risk, and generate more advanced customer insights. The initial focus during the hard lockdown was on business survival. This has given way to the realisation that the operating environment after COVID-19 will be significantly different to the one at the start of 2020. To this end, those insurers who have gained a better understanding of their business needs during this time will be able to develop an AI strategy and make targeted AI investments to deliver a high return on investment without putting significant strain on already tight budgets.

Even though the immediate priorities might include cost and risk reduction, the importance of delivering a quality (and consistent) customer experience cannot be ignored. Churn has become a reality for many insurers especially the incumbents battling against agile insurtechs that are not constrained by legacy infrastructure. To this end, if existing customers do not feel they get good value from their service provider, they will likely jump ship to an insurer who can give them an integrated environment that delivers self-service while offering more customised solutions relevant to their needs.

Leveraging the likes of AI to provide advanced analytics on the wealth of data they have at their disposal, insurers can mitigate the risk of this happening. Along with AI comes the ability to reduce fraudulent claims, predict underwriting risks, improve customer relationship management, and identify process areas that can be improved on to free up employee expertise to focus on delivering strategic value.

Attending to customers

Research shows that global spending on cognitive and AI systems will approach the $80 billion mark by 2022 with a significant portion of that focused on conversational AI applications such as chatbots and deep learning and machine learning capabilities.

According to KPMG, the most critical tools for creating positive customer experiences and building data sets with insights that drive sales are AI-powered customer journey mapping and understanding customer behaviour. For example, insurers are using advanced analytics and AI to derive insights from customer profiles in order to re-engage inactive customers and upselling or cross-selling to them.

By combining AI, advanced analytics, and machine learning, insurers can position themselves favourably to deliver operational improvements while servicing customers in ways that befit today’s evolving digital landscape.