Data reconciliation is a critical component of the banking industry. However, the reconciliation systems and processes within banking and financial services firms are facing significant challenges due to the continual increase in transaction volumes, the introduction of new financial instruments, and heightened regulatory compliance requirements. In the realm of these challenges, it has become crucial to improve the reconciliation process in banking with cost maintenance and operational efficiency.
Hence, before we dive into solutions to streamline the reconciliation process, let’s discuss what data reconciliation is, why it is important for banking, and how automation technologies can help in a reconciliation Process.
Understanding Reconciliation in Banking
Banking reconciliation is the procedure used to align the recorded bank account balance within a company’s financial records with the balance indicated in the latest statement from the financial institution.
Typically, this reconciliation involves comparing the bank’s statement with the internal financial records of the entity. For larger organizations with numerous transactions, banks often offer a spreadsheet format of transactions to be integrated into the institution’s accounting software for streamlined reconciliation.
In the banking industry, reconciliation is important to
Avoid balance sheet errors and accounting mistakes
Help against fraud, and ensure financial integrity
Understand accounts better with clear details of incomes & expenses
Typically, these reconciliations are performed monthly, following the closure of the previous month’s accounting records. During this procedure, all balance sheet accounts undergo thorough scrutiny to ensure that transactions have been accurately recorded in the appropriate general ledger accounts. In cases where inaccuracies are identified, companies must make necessary adjustments through journal entries.
Challenges with Reconciliation in Banking
The Banking industry typically deals with two types of reconciliation- account and transaction. Account reconciliation pertains to various aspects, such as the establishment of new accounts, the management of sub-accounts, the handling of accounts transferred between different business divisions, and the integration of accounts facilitated by new brokers or agents.
On the other hand, transaction reconciliation involves a variety of tasks, including internal transfers between accounts, settlement of transactions based on documentation, and other financial transactions necessary to run the business, such as collections, claims, trades, payments, and so forth. With the reconciliation process being a time-consuming process, the banking industry deals with a lot of challenges like-
Difference in formatting
Trade volume & compliance requirements
Untimely Transaction Recording
Automation in the Reconciliation Process
The reconciliation process can be complicated, time-consuming, and costly if manual tasks are not eliminated. The primary roadblocks are inaccurate or inconsistent data transmitted by senders, different file formats, and disparate systems. Leveraging automation in the reconciliation process can streamline the whole process and enable the banking industry to perform data reconciliation autonomously. Using automation technologies like RPA and intelligent Document Processing in data reconciliation, banking employees can reduce the risk involved with data reconciliation and perform the whole process in a timely manner.
Let’s see how RPA can work in the reconciliation process, RPA integrated with an intelligent document processing solution can-
Extract data like transaction records, and account statements, from various sources, such as spreadsheets, databases, emails, and external systems
Perform necessary data transformations, such as formatting, cleaning, and standardizing data.
Compare data from different sources to identify discrepancies, such as mismatched transaction records or balances.
Handle exceptions by flagging discrepancies for manual review or by automating specific resolution processes.
Generate reconciliation reports and logs, documenting the results of the reconciliation process for audit report generation.
Top 45 Types of Reconciliation in Banking with AutomationEdge RPA
As we have discussed above, automated reconciliation in banking works. You might be wondering what type of reconciliation we can perform using automation in banking. Being an automation solution provider, AutomationEdge has helped multiple banking customers perform reconciliation autonomously. Here are 60 types of reconciliation in banking you can perform with AutomationEdge. Wondering how it’s possible? Let’s have a look at 45 types of reconciliation in banking-
ATM, Debit Cards Transaction Recon
IMPS(Immediate Payment Services)
Bharat Bill Payment System
AADHAAR Enabled Payment System
Nostro & MIrror Account
Accounting & Third Party
Payable/GL Wise Reconciliation
Receivable/GL Wise Recon
ATM Cash Recon
B2C Collection Recon
Account Receivable Recon
Accounts Payable Recon
GL Accounting Recon
Trops Report Recon
Bank Statement Recon
Unique Transaction Record
RKB Remittance Recon
Auto Spooling – SWIFT
Fund Transfer & Treasury Data
EasyPay App Recon
CMS Pool Account Recon
Exchange Record Recon
Purchase Price Variant
Bank Recon Consortium
Motor PH Automation Banking
AMC Bank Statement
Bank Vendor Recon
Bank Reconciliation System
Cash CBR Process
Considering the challenges encircling the reconciliation process, it is imperative that the banking reconciliation process requires effort and time. To cut back the time and cost involved in the reconciliation process, automation is one such solution that can perform reconciliation effortlessly.
Implementing RPA for data reconciliation in banking can significantly reduce the risk of errors, improve efficiency, and free up human resources to focus on more complex tasks. However, it’s essential to carefully plan and design the RPA solution to ensure it aligns with the specific requirements and regulations of the banking industry. Regular monitoring and maintenance are also critical to ensure the accuracy and reliability of the automated reconciliation process.