Finance and accounting teams across many organizations have been facing challenges in achieving high efficiency, reduced operational costs, and drive profits due to dependencies on manual processing which in turn leads to high turnaround times, increased chances of errors, and poor management. RPA’s benefits are too many to ignore for organizations already on the path of digital transformation, and the results emerging have positioned it as a strategic necessity for enterprises.
The insurance industry has its unique set of challenges - given the complex legacy system landscape, complex business models especially in claim management and underwriting. To add to this, there are multiple variants of the same processes which requires large workforce deployment for data entry and customer management activities. Speed, Data management and regulatory compliance is key to success to implementing RPA in Insurance.
The HR department of any business is responsible for a plethora of tasks along the hiring process - many of which are repetitive, time-consuming, and still dependent on manual-driven processes to help employees get work done. This high degree of reliance on labor intensive processes is costly and inefficient and can often lead to high error rates or even compromise compliance levels. Critical processes for the HR department such as employee onboarding, exits, internal movements, departmental transfers, reporting and routine maintenance were completely dependent on manual effort. The entire process involved multiple touchpoints and systems – making it complicated and time consuming with the manual effort involved.
IT services have gone through major transformation and have been a key adopter of automation. Right from Access Management and Software Upgradation or installation, the level of maturity in this area makes it a critical function for organizations to implement RPA to expand the benefits of all the cutting-edge development. Processes for the IT department such as employee onboarding, exits, System Replacements, departmental transfers, reporting, Email Group activation or deactivation and routine maintenance were time consuming and lot of manual effort.
The banking industry has been aggressive in the digital journey. With a complex technology landscape, stringent regulatory requirements and high risks in handling financial transactions, the need for RPA is higher than ever and it can play a big role as has been shown by some large global banks. Given the huge volume of transactions, call volumes and criticality, the RPA solution must have a cognitive capability to make RPA in banking a success.
Robotic Process Automation can be applied to most of the processes within the Healthcare domain as well, ranging from the patient registration processes to the patient data migration, patient data processing, reporting for doctors, medical bill processing, insurance data automation and claim processing, triggering emails from medical billing systems, claim status. This list does not stop here, once the Robotic Process Automation software robots are applied to do these tasks – down the future lane, the processes that are closely related to these would also be required to be automated thereby saving a lot of time.
The number of people turning to telecom companies to connect them with global networks is increasing day-by-day. Many of these providers are burdened with huge volumes of operational processes such as controlling costs and business efficiency, managing data, increasing business agility, acquiring and retaining talent and developing new services. These processes prevent them from focusing primarily on their customers. In such a scenario, telecom companies are competing with one another to provide fast, affordable and cutting-edge offerings to their customers.
The telecom industry is well equipped to take advantage of an out-of-the-box technology such as Robotic Process Automation to help them tackle problems and streamline their business processes. RPA enables telecom companies to manage their back-office tasks easily and deal with huge volumes of repetitive and rules-based operational processes.
