As a senior anaylst at Deloitte stated, leasing processes are often fraught with cost and time inefficiencies and inaccuracies. In addition, they have limited capacity to capitalize on the insights locked within their documents, while the high level of human intervention also increases the probability of fraud and error.
The good news is that automation comes to the rescue.
As a leasing company has access to sensitive client data, such as personal and financial information, it is crucial to manage it responsibly. Moreover, due to legacy systems, that data was stored in databases where it couldn’t be accessed directly, but changes must be made in a separate application and then saved to the database.
Additionally, the client had their mind set on the solution they ought with defined goals in mind from the start. This meant that the reports needed to have specific columns and dates selected. In the end, data was to be entered on particular days only.
Our client is a specialized company that offers its customers vehicle financing options and insurance. Their aim is to offer comprehensive financial solutions and reliable management services to their partners and customers.
The leasing company possesses extensive knowledge of financial and insurance products in the market, allowing them to offer their clients the most suitable solution at any given time, tailored to their capabilities and desires.
- Data entry, selection, and generating reports
- Data archiving - merging and sending documentation to archive
- Creating new client profiles
See how RPA helped our client's business.
It is well-known that leasing companies face significant amounts of paperwork, which entails repetitive tasks for employees, and, consequently, a higher error rate.
As the company grew, leases that were opened and daily change requests that needed to be processed rose steadily. To a person, processing one such task does not require a lot of mental capacity but dealing with hundreds of them consequently consumes much energy and time. Also, all these minor changes had to be made across multiple systems, which requires reliable connections between them.
All things considered, the board was aware of the need to keep the competitive advantage in the long run, and they recognized process automation as a more cost-effective solution than massive hiring.
We developed functional up-to-the-task software robots with the clients’ requirements in mind that instantly answer clients' requests for early redemption.
First, we always guide a client through the roadmap creation so that RPA gets the most for them. It includes process selection and assessment, ending with confirmed RPA suitability. Then, after the client comes with a process candidate, we make sure that developing a robot is entirely possible and will bring savings for the client. In other words, we check all the details, make a process video and create a process map.
Before the robot is pushed to production, the process and testing results are presented and confirmed in the testing environment, followed by the UAT. And that is the process we went through with the client to develop software robots that saved the day (and many days ahead).
In leasing, robots perform data entry, selection, and generating reports. At the same time, some of them contain a complex data algorithm, so the task is completed only on specific dates, considering the data from the last two days. Having a date algorithm makes it decide when the robot is starting the process and when the process ends before the data is gathered.
Robots also help with archiving, an essential part of leasing processes. They collect and merge the documentation, send it to e-archive, and remove documents in old locations.
The third use case is creating new client profiles in the internal system or app based on the data collected by OCR, making the client and policy entry more efficient.
Software robots are great for the leasing industry since they are non-invasive but function as add-ons on the legacy systems. In addition, they have a low error rate and don't get tired after processing thousands of documentations.
The robot does data-gathering, and data-entry for specific values fetched from a website within the first process. Then, the second and the third software robots generate reports for specific debt collection agencies.
For the mentioned three processes to work correctly (executing data entry, selecting data, and generating the reports), it was necessary to optimize the date algorithm specifically tailored to our customer’s needs. The algorithm was crucial as it gave the robot the understanding of which day is a working day and which day is considered a weekend or a holiday. In the latter case, the robot pauses for a day and restarts on the next working day when it finishes the task.
Besides this, it was essential to enable the robot to select the correct options using selectors inside the legacy application. These selectors would give the robot an indication of whether the checkbox was checked or unchecked. Besides this, RegEx played a significant role in correctly processing data as it allowed the robot to precisely extract the needed data.
Finally, the robot needed access to an on-prem internal server. This was resolved by creating a secure file transfer protocol connection that enabled the robot to upload the files securely to the server.
These people are primarily thorough. They don’t stop in from the problem but reach out to us with multiple solutions and ask us for our opinion. They are trying to find the one that will make our lives easier and not the one that is easier for them to develop.
