Most insurance companies today must address a diverse set of challenges, such as...How do you create a dynamic and growing business while managing risks and reducing costs?
In many ways, they are caught between two antagonistic concepts. On the one hand, insurance customers are no different from general customers, and today everyone is informed, connected and demanding. They expect fast, autonomous and transparent experiences on any device, no matter where they are. On the other hand, commercial applications in most insurance companies are 10 to 30 years old and not ready, let alone equipped with the features and capabilities needed to meet the expectations of today's customers. Systems have become more complex and rigid in order to adapt, as well as to meet new business and compliance needs.
But most insurance companies perceive the investment and risk associated with upgrading legacy systems as cost prohibitive. Instead, they look for technologies that connect functions and capabilities that must remain competitive.
The perfect assistant
Automation has always been linked to repetitive tasks in which human intervention does not add value, and its scope and application are expanding thanks to advances in Artificial Intelligence. Thus, not only are software robots or bots capable of processing, practically in real time, large volumes of information whose analysis would require days of human work, but they also have increasingly advanced capabilities for self-learning and communication in natural language.
These capabilities make software bots the perfect assistants in the development of tasks such as customer analysis and classification, claims assessment, fraud and delinquency prevention, abandonment detection and personalized marketing.
Challenges for the insurance industry
This is why there are many and diverse operational challenges facing insurance companies, such as
Manual entry of various data sources: Insurance companies regularly handle mixed data formats, including a variety of paper files and electronic documents. This means that, in order to process an insurance claim or provide a quote to a customer, employees must manually enter information from various data sources into the company's database. This process is slow and costly, and furthermore, this manual work is highly prone to errors and inconsistencies, which could result in significant discrepancies in company records.
Legacy applications and disparate systems: Many insurers still rely on legacy systems or multiple different systems, applications and software to manage their business functions. When implementing new software solutions, such as ERP (Enterprise Resource Planning) or BPM (Business Process Management), many companies face challenges in integrating them with their existing IT configuration. As a result, integrating new software can involve replacing part or all of the existing configuration and require a significant investment in time, money, and employee effort. Because of these challenges, many companies are left with older systems that no longer provide the necessary support for company growth and development.
Maintaining regulation and compliance: All companies, but especially insurance companies, must comply with a number of compliance standards including, for example, tax laws and privacy rules. Updates or improvements to these regulations are common, and this often means that business processes suffer or must be re-established to reflect these changes. While such laws are intended to protect business operations, company employees and customers, compliance difficulties and non-compliance by insurance companies can result in a number of detrimental financial and operational consequences.
How RPA can help
Despite these challenges, when successfully implemented, RPA can help reduce some of the business barriers faced by insurance companies. RPA can free up 20 to 30 percent of capacity at the enterprise level, while minimizing operational risks and improving the customer experience.
Now that we have discussed some of the major difficulties faced by insurance companies in streamlining their back-office processes, we can look at how RPA can overcome these obstacles by
Expediting claims processing: Successful claims processing is critical to the profitability of insurance providers. Claims processing is typically error-prone and time-consuming, requiring significant investment by company employees. By replacing the need to process insurance claims manually, RPA can reduce the amount of time spent on these repetitive processes and reduce, if not eliminate, human error. This means that insurance claims can be processed much more efficiently, accurately and conveniently.
Scale with ease: Because the number of active RPA software robots can be increased or decreased in a matter of seconds, scalability is easy to achieve with RPA. Software robots can be scaled up or down during certain times of the day or year when there is a large number of claims or quotes to be processed. While such temporary scaling of RPA software robots is essential in the short term, the number of active robots can also be increased permanently to meet long-term growth demands.
Non-invasive compatibility: Many insurance providers still rely on disparate legacy systems or programs, so the non-invasive nature of RPA makes the technology an ideal solution for companies that want to easily simplify their business processes. RPA mimics human keystrokes and mouse clicks, interacting with the computer's display layer of programs and applications. As a result, RPA can be deployed in addition to existing programs, without the need for insurance providers to replace their existing IT configuration. RPA can also be implemented with limited support from an insurance company's IT team because it does not require users to have programming skills.
Improving regulatory compliance: Compliance is an important component of insurance company success, RPA ensures data accuracy and its software robots keep a continuous record of their actions. As a result, regulatory compliance can be continuously monitored through internal reviews. This allows insurance companies to monitor compliance themselves, as well as be better prepared in the event of an external audit.
Long-term RPA
Automation, robotics and Artificial Intelligence (AI) are redefining the insurance sector and insurance companies are increasingly integrating these technologies into their processes. Even so, this sector is not one of the most advanced in the use of Robotic Process Automation (RPA), as opposed to others such as banking or telecommunications.
In fact, a study conducted by Deloitte based on 400 companies consulted from all sectors, highlights that the main advantages experienced by organizations that have made a successful transition to RPA are cost reduction (59%), drastic reduction of errors and increased quality (90%), increased productivity (86%) and high compliance (92%), among others.
It is very likely that those insurance companies that do not bet on process automation in combination with the constant advance of artificial intelligence will be relegated to the back burner and even endanger their own viability.
