Internal processes in the insurance sector are coined by a high overall complexity due to numerous different varieties and process sequences. Especially (external) communication steps decelerate the process and cause great internal costs. In accordance, insurance companies face a lack of transparency which affects process performance as well as conformance. To regain transparency and power of the process, KPMG used Process Mining technology to visualize the process for an American automotive insurance. In order to discover the best possible optimization potential, professional KPMG insurance experts supported to analyse and evaluate the created transparency of the process. This cross-functional team was able to detect the main activity costs drivers in the damage claim handling process of the American automotive insurer.

During the project and the continuous exchange with the client, two key challenges were identified:

Lack of transparency of actual process / Process heterogeneity

The client assumed that majority of the damage claims being processed does not follow the optimal and most cost efficient path. Also, a high number of different ways how damage claims can pass the End-to-End process was expected. KPMG Process Mining discovered more than 130.000 different process variants of 360.000 analysed claims.

Process inefficiency and high process cost

On top of having a great complexity throughout the damage claim for process, some essential process steps such as all communication steps were highly cost-intensive. When adding actual costs per activity to the process model, cost transparency of the overall damage claim process was created. Adding the Automation Rate of each of the involved and targeted process steps, it was easy to realize that mostly manual activities occur for the high process costs. Moreover, bottlenecks occurred whenever communication loops were needed which not only result in a higher throughput time, but again also in higher internal process costs. Apart from that, the Process Mining analysis has revealed that a change of the processing channel of damage claims generate high internal costs. Following the originally assigned processing channel entails a more streamlined and straightforward process and reduces process costs.

As definite costs have been matched to each of the activities in the process, an accurate saving potential was identified. To tackle the above described key challenges, the following solutions have been developed:

• In order to increase transparency and homogeneity, the process needs to be more streamlined. In line with that is the definition of a desired To-Be-Process (Happy Path) that should be primarily followed. Once such a process is implemented, it is easier to track deviations and define countermeasures to prevent outliers
• Unnecessary loops, especially for communication activities, must be reduced to a minimum. KPMG Benchmarking has shown that other insurance companies face similar issues but were able to reduce costs due to a reduction of rework activities and loops
• Processing channel jump are cost driver that must be reduced and kept at a minimum
• An increase of automatic and/ or semi-automatic activities will reduce manual efforts and therefore process costs. The Automation Rate increases and process steps are performed faster and cheaper. KPMG proposed approaches for activities that show high automation potential (e.g. inputting invoice into SAP system; booking invoice, etc.)
• Identification of specific suppliers which could be automated using Robotic Process Automation (RPA) and creating individual business case for bots.
• Identification of main process cost drivers and reduction of redundant manual activities whenever possible

During the project execution phase, the KPMG Process Mining team worked closely with insurance expert as well as RPA teams to maximize the impact and value that can be delivered to the client by using synergies from all three solutions. A roadmap was developed to group measures into priorities and sequence for implementation.

Identified savings in numbers:

• Automation potential of ~ $1 Mio
• Process optimization of $3.4 Mio by reducing manual rework activities
• Process optimization of $3.4 Mio by streamlining the overall process activities
• Potential of $0.6 Mio by reducing jumps within the processing channels

For more information on process mining solutions feel free to contact us.