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4 ways to take a 'business first' approach to IA
The London Market is in the throes of an era of tumultuous change. Market participants are introducing new technologies to improve internal efficiency, agility and process control. At the heart of many of the changes lies intelligent automation (IA). When implemented and used correctly, the technology has the potential to drive growth and revenue. Insurers need to take a ‘business first’ approach to introduce it, identify areas where it can add value and the skills required to use it effectively.
Traditional insurance practices in the London Market have predominantly been manual and paper-based. Processes were often undocumented, which resulted in a lack of consistency and valuable data missed or left unstructured – duplication and rekeying are still rife.
Introducing IA, while providing a solution to these issues, has been resisted by some. They consider classifying data and documentation needed to implement IA technology labour-intensive. Coupled with an understandable fear of job losses, some organisations continue with known traditional but outdated working methods.
However, advances in technology have made the transition from unstructured procedures to automated digital systems much easier. Using IA and robotic process automation (RPA) to emulate human interactions when categorising paperwork, data extraction from all kinds of unstructured documentation is now possible. The result? A much faster route to data analysis without the need for exhaustive human input.
Adding value, improving efficiency and process control
IA can be used across all functions in insurance benefitting both the businesses across the value chain and the end customers. By extracting, manipulating, analysing and interpreting data effectively, organisations can create long-term IA capability, which drives value and reduces costs.
Underwriting: IA can make underwriting more accurate by providing a complete picture for risk analysis. Or, where there isn't much historical data available, interpreting external data from similar scenarios to inform decision making.
Pricing: using an enhanced number of risk factors, policies can be priced more accurately. The Internet of Things can provide personalised data to directly inform insurers of risk behaviour and help them price policies accordingly..
Customer experience: IA will be integral to improving customer experience. Chatbots can deal with routine enquiries and direct clients to relevant information. Providing multiple communication channels linked to a centralised information base will suit customers’ differing preferences. Using data to help create more tailored products and communication according to the nature of the risks being underwritten.
Claims: will benefit from the automation of claims data processing. The use of online self-service portals to submit claims information will speed up claim processing and add transparency to the process. AI and machine learning can deal with administrative tasks, reducing errors and duplication, improving process control and streamlining the claims process. Fraud detection can be enhanced by using IA algorithms to identify patterns and flag them to claims staff, reducing payouts for fraudulent claims.
New technology requires new skills
Some have questioned whether introducing IA will mean job losses in the insurance industry. Rather than replacing humans, the adoption of new technologies will change the skillset needed for many roles. As tasks become increasingly data-heavy and administration-light, the demand for technical skills will increase, as will high-quality customer service and support skills.
Automation will remove routine, manual tasks, allowing employees to focus on more analytical and complex tasks, such as business intelligence and creating risk mitigation strategies. For example, claims adjusters are already using drone and satellite images to view damage and make faster settlement decisions.
Technology will be used to support human decision making. Areas like claims and underwriting require subjective judgements to be made. IA will provide the data needed to make accurate decisions, reducing the risk of error and improving the customer experience.
The challenges of introducing IA
Introducing IA comes with its own unique challenges. Dealing with high volumes of data in real-time requires a set of tools and techniques to support it. Elements of traditional IT architecture will become obsolete as insurers make more use of cloud-based data storage instead of internal servers and systems.
Data security and privacy is of paramount importance as data breaches increase and cyberattacks become more sophisticated. Data also needs to be cleansed, relevant and free of bias to produce valuable information for an organisation to use effectively.
However, the advantages to the London Market of IA outweigh the associated risks and challenges. Benefits range from process optimisation to improved customer satisfaction, higher-skilled employees and unlocking value from the vast quantities of accessible data. Market participants should understand the technologies, their impact and identify the ones that will provide the highest return on investment so they can implement them successfully.
If you’d like to find out more about IA and other technologies influencing the London Market, then join us for TINtech London Market 2020. Enjoy keynote presentations from industry thought leaders and participate in workshops and discussion sessions with your peers.