As per the Reserve Bank Of India’s FSR report released in January 2021, the GNPAs (Gross Non-Performing Assets) of the Scheduled Commercial Banks may be at the level of 13.5 percent by September 2021 under the baseline scenario. This clearly rings an alarm for all the lending institutions to make wise credit decisions by properly screening the borrowers before granting loans.
Need for a Sturdy Bank Statement Analysis
Bank statement analysis is one of the prime processes of assessing the creditworthiness of borrowers. It is the process of assessing a borrower’s earning and spending patterns based on their bank statements. This kind of analysis is performed by all lending institutions before making credit decisions.
Bank statement being one of the most reliable documents to showcase the financial position of a borrower, lending institutions generally perform a thorough analysis of the statements as part of the borrower screening process.
However, manually going through pages and pages of bank statements can be cumbersome and prone to human errors or even subjective biases. This is where automated bank statement analysers, called BSA engines, come to the rescue.
Key Features of Bank Statement Analysis Solution that Can Help Mitigate Risk
1. Transaction Pattern Analysis:
Bank statements contain the borrowers’ transaction history in the specified period of time. It gives detailed information on one’s expenditures, income sources, cheque payments, transfers, recurring ECS debits, EMIs, credit card payments, bill payments, penalties levied on defaults, cheque returns, etc. As a result, it enables NBFCs and banks to make better credit decisions.
Below are some of the important patterns a good BSA engine should catch and highlight.
High Valued Transactions
The BSA engine should be able to identify and highlight the high valued transactions separately based on a preset value limit. The frequency and the amount of outgoing high valued transactions give a good idea of the potential spending capacity of the borrower.
Usually, in the case of a high net worth borrower, many high valued transactions are expected. But, in case a normal borrower has several high valued transactions, the engine should throw an alarm bell. The value limit must also be configurable, according to the value of the loan and the net worth of the borrower.
Debit / Credit Analysis
The number of credits and debits in an account is a good indicator of one’s income and expense. The credit frequency and amount gives a clear demonstration of one’s different sources of income. The BSA engine should be able to provide a clear summary of the credits and debits and highlight any abnormality based on the rules set in the engine.
Daily / Monthly Closing Balances
Closing balances play a critical part in understanding the consistency in the financial position of a borrower. For example, the BSA engine should be able to analyse daily closing balance data and highlight how many days in a month the closing balance is more than two standard deviations from the mean.
If the number of instances beyond two standard deviations is less, it indicates the borrower is consistent in maintaining his/her finances. This validation range also should be configurable, so that for different borrowers, the engine can apply the rule with different limits.
Not all credit transactions can be considered as income. A good BSA engine should have a definite rule to identify the income alone. This is very important when the lending institution is dealing with retail borrowers who are typically salaried employees
2. Charges and Returns Analysis:
The BSA engine should be able to identify all the charges and returns from the account statements. If the number of instances is less or nil, it indicates the financial discipline of the borrower.
Below are some of the important aspects a good BSA engine should be able to identify in the parsing.
Cheque returns attract heavy penalties and can also impact the financial credibility of the cheque issuer. Depending on the amount involved and the impact on the receiver, cheque returns can also incur legal actions. The BSA engine should be able to do a thorough analysis of all the cheques issued and their realisation details to identify any returns.
The statement analyser should be able to identify and list down all the penalties like charges for not maintaining a minimum balance, charges on cheque returns, charges on forex conversions, charges on any pre closures of deposits, charges on delayed payments, charges levied due to insufficient funds on recurring payments, etc.
3. Fraud Analysis:
The BSA engine should be able to identify and flag down any fraudulent activities based on the details available in the statement.
Below are some of the important aspects to be checked by the analyser.
Circular transactions are a kind of artificial transaction that happens between the companies that are under a single group or a single controller. Usually, these transactions are done for inflating the income or expense of the companies involved. This practice is legally considered a scam and is banned in several countries. The BSA engine should be able to catch such transactions, especially in the case of business borrowers.
Multiple Small Credits
If there are a large number of small credits from different and new sources in an account, that is a potential money laundering practice. The BSA engine should be able to identify such patterns and high light for further investigation.
According to the geography of the lending institution, there will be a definite set of blacklisted countries or specific institutions. Any fund transfer to such banned entities is considered to be illegal. BSA engine should be able to identify such suspicious transactions and bring them to the notice of the reviewer.
More Cash Deposits
In the case of retail borrowers, frequent and more cash deposits other than salary is a clear element of suspicion. BSA engine should be able to identify this pattern and highlight the cases.
4. Predictive and Statistical Analysis:
The BSA engine should be able to aggregate data from multiple account statements and conduct a thorough predictive and statistical analysis based on the defined set of rules. The engine should have real-time integration with GST and credit bureaus to get the latest information on the borrowers’ credit history. The output should be an overall credit score of the borrowers that will act as a guiding light.
The above are some essential features that can play a pivotal role in analysing a borrowers’ creditworthiness. Having a robust bank statement analysis engine that does a thorough parsing of the borrowers’ bank statements and highlights all the critical information to make an informed decision is essential for the lending institutions to grant good loans and reduce the NPAs.
Try Precisa, the simple and robust bank statement analysis tool, that allows you to simply upload bank statements and presents actionable insights in visually appealing, intuitive dashboards in real-time.
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