Data and analytics: Unlocking the power of claims

Faced with the threat of disruptive new digital entrants capturing market share via modern client experiences and operational efficiencies, the case for change is clear. Established market players have large pools of client information that can facilitate informed, evidence-based decision making but it must become accessible in new ways to unlock insights — and one of the answers is digital technology.

In KPMG Insurance professionals' view, there is clearly little time to lose in levelling the playing field as insurtech companies boldly challenge the industry’s status quo with modern business models. Using new technologies, including machine learning (ML) and Artificial Intelligence (AI), these disruptive players are overhauling conventional processes in the insurance value chain to optimize efficiency and enhance the client experience.

Data use can help insurers reduce indemnity spend by improving loss prevention and claims processing. By proactively using data and engaging with clients to identify risks related to vehicle safety or home security, for example, insurers can provide clients with personalized service that enhances their experience. This can, over time, also provide wider societal benefits related to personal injury or environmental damage, which can help insurers demonstrate their ESG credentials alongside advancing their commercial position.

Additionally, insurers tapping into data can price reserves dynamically to predict cash flows in real time.

Leading insurers are also beginning to use claims data to automate the processing of routine claims. This allows claims teams to focus on complex claims in which expertise and judgement are crucial. They can also assess the level of risk posed by automatically processing certain claims, and quickly identify and manage more-complex claims. The result gives insurers the capability to dynamically adjust their risk appetite through analytics while also being able to improve the claims experience for clients by providing a timely resolution.

Data analysis can also identify unusual patterns of activity related to fraud. Historically, claims handlers have used their experience and intuition to spot fraud (or simple algorithms). Data use can help to identify and respond to potential threats, such as fraud, as they arise, and complex cases can be escalated quickly to skilled analysts for further review. Enhanced fraud identification and response will help insurers reduce costs and improve the client experience.

Insurers can use claims data to develop new product solutions that are designed to complement a change in focus from traditional claims management to consistent and reliable claims prevention. ‘Parametric’ products can be created for a variety of insurance lines, with prior claims data used to determine a set of conditions whereby a settlement is instantly confirmed for the client. A parametric product would also support the insurer by providing increased certainty to their exposure, providing additional clarity to the pricing process for the business.

Enhancing the current use of data and analytics can also help insurers to engage in claims prevention for clients. This could be done by taking in external data streams, such as car dashboard camera footage to support motor insurance claims, or by supporting clients by offering analytics-backed risk management as a service and assisting them in reducing their exposure to a claims event.

Unlocking the various benefits of a digital, data-based claims environment begins by ensuring that the data being entered is clean, accurate, and able to be 'read' by other systems. In many cases, insurers can improve both their data quality and the time that is spent on value adding data-based activities by improving their current state processes. For example, a large insurer refined their processes to reduce the amount of time that was spent inputting and monitoring actuarial data from 80 percent and using the time to analyze the clean data instead.

Legacy systems will need to be reviewed to determine whether the right information is being adequately captured to optimize analytics results — and whether the procedures around processing the data are ensuring the information captured is of sufficient quality. Many insurers face the difficult decision of whether legacy systems can and should be patched, or whether a new platform should be added to their architecture or replace an existing system. As underwriting, pricing and claims become increasingly data-centric, insurers should ensure they can use their data to provide value-adding insights to their clients. The answer of how to unlock this value will vary for different insurers. KPMG firms have provided support to some insurers by helping them leverage their data by transforming the processes governing how they capture data into core systems. We have also guided others on identifying new systems that ingest data cleanly and provided them with advanced analytics.

Insurers need to recognize that continuing to use legacy systems and processes can be as costly as pursuing a transformation project due to inefficiencies, and the unrealized benefits of harnessing the data held within the claims department. Many insurers cite past digital transformation projects as expensive and ultimately delivering little on their promised advantages. Integrating transformation requirements and capabilities into the end-to-end client journey is crucial and it requires executive level input and strategic support to ensure new processes or system changes encompass all organizational needs beyond claims.

Another significant obstacle we have seen in the journey to leveraging data is an inability to extract and manipulate valuable claims data, which limits key capabilities, from managing operations effectively to being able to reserve or price products accurately. By utilizing the data held within the department, and overlaying analytics, leaders can receive enhanced management information reports, which will support their decision making - such as providing better quality resource management information, helping the business to flex capacity to meet demand.

We are seeing some insurers successfully identify trends in claims and enhance their claims operations — identifying spikes in demand or providing real-time data to suppliers to resolve claims more efficiently. The challenge for many organizations, however, includes their desire for a completely accurate view of past performance, restricting their focus to lagging indicators instead of building leading indicators for the business. Additionally, some companies have paid for a point solution to enhance their analytics capability for a specific use case that typically cannot be leveraged across the business.

There also remains a perception that using data and analytics is a ‘magic bullet’ that will either solve all problems or replace all people in the claims team, neither of which is the case. Insurers ultimately need to strategically identify both what data and analytics can do for their business, and how it will be deployed to achieve their goals.

Transitioning to a data-based claims department will not just require insurers to review whether they need to update or upgrade their systems architecture. Insurers will also need to review the adequacy of the processes that underpin data processing and analytics, alongside ensuring claims colleagues are receiving sufficient training to leverage the data available.

One insurer enhanced their processes and their colleague capability in using data across their business, which helped them redirect resources towards more value adding activities. However, they found that their two policy administration systems still caused material inefficiencies as some manual tasks could not be automated, which led to a high level of operational risk. Therefore they, purchased a new policy admin system and acquired the modules needed to integrate with the rest of their architecture to achieve the required functionality, which while being a major investment, has helped to transform their business.

Once an insurer has the right quality of data being entered into their systems, and the right processes and people capabilities to maintain the information, it is important that they develop the system intelligence needed to effectively utilize their data. This will require analytics functionality that combines policy-administration data with data from various key internal and external sources. To maximize the opportunity, insurers will need to enhance their data-science capabilities to interpret the data for analysis as models become more complex and increasing amounts of data are used to derive outcomes.

It should be clear to today’s insurers that improving their use of existing data, augmenting it with external data sources, and introducing advanced analytics can help drive new client and marketplace insights, improve efficiency, competitiveness and decision making, and enhance the client experience.