How to smartly robotise key business processes in financial institutions? | Mindbox

How to smartly robotise key business processes in financial institutions?

Customer: Credit Agricole Tool:  UiPath, UiPath Orchestrator Date: 2020

Crédit Agricole is using Robotic Process Automation (RPA) tools to speed up the credit granting decision-making processes – freeing the analysts from manual routine tasks of collecting and verifying data, leaving just the final decision in their hands.

 


Customer: Crédit Agricole

The process robotised: collection and processing of information required for credit decision-making by the analysts

Utilised solutions: UiPath, UiPath Orchestrator

Benefits: process acceleration, freeing the analysts from routine manual work


Crédit Agricole Bank, part of the Crédit Agricole Group that’s among the world’s top 10 banks by assets, has been on the Polish market for over 20 years. It is a universal bank focused on retail banking, corporate banking, agricultural and SME banking and on consumer finance. Moreover, it offers a broad selection of automotive, property and life insurances.

In line with its motto of “100% digital, 100% human bank”, it is consistently investing in new technologies and making its services more easily accessible via remote channels, while at the same time caring about its staff and the quality of its face-to-face customer service. One of the organisation’s digital transformation areas is its consistent smart business process automation done using Robotic Process Automation technologies on the processes picked by the employees of the bank, taking into the account the automation potential and the achievable benefits that are calculated in detail.

 

 

Challenge: automating the credit decision-making support

 

Credit decisions made by the bank’s analysts depend on numerous factors. One of them is the potential customer’s creditworthiness assessment based on the information they present and a check of their credit history data in online registers containing information about the repaid and outstanding debts.

The credit decision-making process at Crédit Agricole in fact can follow one of the two paths: the standard and the individual one. Some applications are entered directly by the account managers into the relevant banking system. Based on the data it stores, the analysts check the internal bank systems and the external registers that include the Polish National Debt Register, the Credit Information Bureau and the Economic Information Bureau for information about the clients, and then they aggregate it in custom-predefined spreadsheets. These group all information, highlight the master data and calculate the credit score for individual clients. Finally, using the results of these calculations, the analyst makes the credit award or refusal decision.

There is also a second path of arrival of credit applications, called Individual Acceptance Path. Account managers from branches are sending information by email to the credit department employees who process such the applications by performing similar tasks, however, outside the rigid constraints of the IT system that sometimes unnecessarily block a positive decision from being made.

“Every day we have new applications for various types of loans: cash, mortgages, consolidations, etc. Each needs to be processed in a similar way – by retrieving information from online credit and economic databases and entering it into the spreadsheets – it was quite a burden on the analysts” – explains [a representative of] Crédit Agricole.

This is why a team of banking robotisation specialists in collaboration with the representatives of the business units concerned has analysed this process for the automation potential and the achievable benefits. The results of the analysis looked promising, so the decision to robotise was made.

 

 

Solution: automating the verification of data in internal systems and retrieval of information from external registers with the use of RPA tools.

 

Due to the complexity of the process as well as its importance to the bank, the partner selected for the robotic process automation was the experienced team of experts from Mindbox. It was to closely collaborate with the Crédit Agricole’s in-house team that included the representatives of the business units responsible for the process and the member of the bank’s RPA team made responsible for the correct integration of the robot with the corporate smart automation environment.

The duties of the analysts have been taken over by the UiPath robot. It validates the data in the application, retrieves the basic client(s) identification data – there may be a maximum of four codebtors, checks the data in the registers and then aggregates the information in spreadsheets – e.g., enters information about debts repaid and outstanding in relevant tabs and finally calculates the credit score. Every so often it may happen that the robot will not find information about all or some clients in the registers, then it will also provide such information. From the robot’s perspective, the difference between the two paths practised at the bank was whether data was retrieved from the system or from an email message. Subsequent steps were the same.

To develop the robot, the UiPath technology was selected. Additionally, UiPath Orchestrator was used to manage the robot’s operation and generate reports on it.

 

 

Benefits: speeding up the process and freeing the analysts from routine manual data entry and verification tasks

 

Robotising a part of the credit decision-making process significantly sped it up and reduced the burden on the analysts by freeing them from the repeated manual work of checking the data in the applications, in the registers and rekeying it to the spreadsheet.

“This task took the analysts between a few and a dozen or so minutes to perform. This may seem not a lot, however, if we consider that every day at least a hundred applications need to be reviewed, short minutes become long hours for many people. The robot is able to get through one application in a smashing 120 seconds and provide the analyst with the material ready to be scored” – says [the representative of] Crédit Agricole.

The project itself was delivered at lightning pace: work commenced in November and was completed in just over three months in February 2021. The project’s rapid success was mainly made possible by the technology maturity of the bank, its high awareness of the RPA and good up-front preparation to go ahead with the project.

RPA is not a novelty to the bank. It has been robotising and automating business processes for quite a time now. When looking for the partner for this project, the bank already had its processes mapped for the robot. Moreover, the return on investment assessment was done.

“Bank’s representatives involved in the projects understood what the main robotisation challenges were about and were correctly reacting to subsequent work stages and difficulties that arose. The initial assumptions had to be somewhat modified, the processes turned out to be slightly more complicated than they seemed initially, however, with good communication and collaboration the obstacles were overcome quickly and efficiently as they appeared. The weekly status meetings were of help here, where current goals, issues, and priorities were discussed” – says [the representative of] Mindbox.

The good work organisation also included the technical aspect. The project was developed in 100% in the test environment. The subsequent transfer of the approved solution to the production environment was the responsibility of the bank’s representatives. Mindbox’s experts had no access to sensitive client data. All data in the test environment were anonymised. This has made the project delivery easier and faster.