By manually verifying the charges made by the POS vendors and using various rates for various POS merchants, the bank performs reconciliation on data files that POS vendors send to it. A bot was created that, without human assistance, downloads attachments from POS vendors and uses the specified rates to reconcile each transaction.

To generate Tax Certificates for corporate clients, a client wanted to automate the procedure. To do this, customer information from the T24 Core-banking application had to be extracted into a CSV file, certificates had to be created using a preset template, and certificates sent to customers. By creating a bot that pulls customer information from T24 core banking and generates tax certificates, the entire process of certificate generation and distribution has been fully automated.

To make sure that customers are not overcharged, undercharged, or uncharged during reconciliation, the bank follows a manual procedure. Due to the human element involved, the process takes days to complete and is prone to mistakes. The entire revenue assurance process is automated using RPA by creating a bot that replicates the entire process without the need for human assistance. It automates data extraction, shortens processing times, organizes the validation process, and produces accurate results.

Customers must fill out a hard copy, printed form to open an account. The Account opening staff manually enters these customer details into the banking system. The difficulties with manual processes include the lengthy time it takes to meet customer needs and mistakes made when collecting customer data. The process of opening an account has been made simpler by developing a bot that uses machine learning and AI to extract customer information from scanned documents and input it into the banking application. The turnaround time for opening an account has been reduced from approximately 50 minutes to 4 minutes for each client. Additionally, it has increased customer satisfaction for increased industry competition and eliminated 99 percent of errors in customer information.

The customer account number, transaction date, and transaction amount were taken from the narrations column in the Acquirer or Issuer worksheet to create a daily ATM Visa Reconciliation report on all VISA transactions made through various channels. RPA has completely automated the reconciliation process, and the exception sheet is produced without error in a matter of minutes.

At the conclusion of each working day, the bank generates a report by extracting information from various data sources in the core database using business intelligence (BI). By creating a bot that performs all the actions automatically, this process is simplified and reports are generated with shorter completion times.

The bank’s corporate office receives requests from branches from clients who want their ATM cards’ limits increased via mail. Through automation, a staff member with access only must log into the ATM card application and download the attachment from the email before seamlessly implementing the changes for each customer on the list.

Mail-in requests from customers who want their ATM card blocked are sent to the bank’s headquarters by the branch offices. Through automation, a staff member with access only must log into the ATM card application and download the attachment from the mail and immediately disables the card for each customer on the list.

The IT manager of a bank must spend numerous hours creating users from HR lists and individually applying each user’s license, user privileges, etc. A manual process may be ineffective, prone to error, and unsustainable. The process has time-consuming, error-prone, and unsustainable problems. The procedure entails creating a bot that downloads the branch request attachment from a specified email, logs in to the user creation application, creates users for each person on the list, and sends a notification email once everything is finished.

The client is a top provider of financial services, and it generates enormous quantities of transactional data from various sources. Based on its liquidity position, the bank must act quickly. To automate repetitive tasks and cut down processing time from three hours to under ten minutes, a software bot is used. This makes it possible for the bank to meet regulatory requirements and gain quick insights into its liquidity position.