Modernizing the insurance business with RPA
The concept of insurance has been among us for quite some time: maybe 5 or 6 centuries. Insurance companies have a little less (about 3 centuries), and they are certainly an essential player in the financial system since then. However, like other financial companies, today they face challenges that can put their businesses at risk:
The regulations that insurers must comply are increasingly complex and changing. Businesses must keep on realigning themselves with the changed regulations in order to ensure that they are compliant; Failure to do so may have consequences from operational to legal.
Difficulty updating technologically
The systems in which their businesses run the insurers are complex, and therefore many companies continue tend use versions with several years (legacy). Replacing one or more of these systems involves a significant effort in time, money and people.
Customers with more demands
Customers seek for better products, better prices and better shopping experiences. If an insurer continues to base its sales processes and claims on manual processes such as filling out paper forms, capturing information on multiple screens, etc., there is not only a high probability of making mistakes and having inconsistencies of information, but even of losing customers facing competitors who are digitizing and shortening their processes.
How are insurers facing these challenges? Nitin Verma, a veteran technology expert explains: “To dramatically improve profit margins as well as transform customer experience, insurance companies globally are turning to automation to streamline business processes and effectively serve customers. […]RPA works best when the underlying processes are rules-based, repetitive, and frequent. It reduces the effort by 20 to 30 percent at an enterprise level whilst minimizing operational risk and improving customer experience.” According to Verma, some areas where RPA can help are:
Streamline Claims Processing
By replacing the manual processing of claims with RPA, the amount of time spent on performing repetitive processes and reduce, if not eliminate, human errors, obtaining efficient and accurate processes.
Scalability is easy to achieve with RPA as it is possible to increase or decrease active RPA software robots (according to the number of claims or quotes that will be processed during a particular time of the year, for example).
RPA can be implemented in synchronization with existing applications, without the need to replace the configuration of current systems. RPA imitates human keystrokes and mouse clicks, interacting with the presentation layer of computer programs and applications, which makes it a non-invasive technology.
RPA ensures that the data is accurate and the software robots maintain running logs of their actions. Therefore, companies must monitor regulatory compliance on an ongoing basis through internal reviews.
Better data quality.
One of the biggest challenges in implementing RPA is the quality of the data used to work with. The use of RPA can represent a solid data capture and extraction solution, which is essential to ensure that a robot does not stop with batches of data sources in which they cannot work.
Some best practices that Verma has found in implementing RPA projects in the insurance industry are:
- Apply a process optimization (the Lean methodology works well in most cases) before the RPA implementation.
- Identify the candidate processes for RPA by assessing their business criticality, and applying a component-based architecture.
- Implement a Center of Excellence (CoE) that defines the guidelines for the evaluation, design, development and deployment of robots.
- Create a RPA operations center to proactively monitoring progress, benefits, capacity and interdependencies.
- Form a library of shared assets and align RPA implementation architectures throughout functional and geographic areas.
RPA is, of course, a strategic tool on the road to digitalization and transformation of the insurance business. Without affecting the core systems, it is possible to start with a small and scalable RPA pilot project that allow a gradual improvement in customer experience, cost reduction and data governance.
Author: Conciliac Team.
Nitin Verma; “RPA and the Insurance Industry”, February 2018, Medium.com
Wikipedia; Historia del Seguro.