Auditors and regulators expect that the data submissions of banks should be in details. However, there is a plethora of banks that are still using outdated and obsolete black holes or credit decision system in which the valuable data might disappear. Thus, they will not be used anymore for critical processes like stress testing. This write-up includes the advantages of data warehouse solutions for delivering higher returns on different risks at the time of making the regulatory compliance affordable and easier.
As per the commercial banks, granting of loan is recognized to be a dynamic and iterative procedure and not any sort of distinct event, featuring a no or yes outcomes. It is known to include a wide array of data outputs and inputs, in addition to examination risks, as well as revenue tradeoffs. A facility is found to evolve prior to finalization in a substantial manner.
A loan file might be closed essentially as a bank completes the facility, opt for a credit decision and the release of funds. Bank credit policies are known to need an annual review, in which the bank will be updating the borrower rating and the loan file is closed after another year. The staffs of banks check the compliance status of different loan covenants. Banks at rare situations place sufficient, consistent, quality and clean data in a searchable system for the determination of covenant compliance without the need to reopen the credit file manually.
The data and information from the process of loan decisioning for different complicated credit facilities are aggregated rarely into any sort of auditable, reportable and searchable system. The data is loaded into different word or excel documents into different source systems after which it is left in different flat files where it will not be re-used for different critical procedures like covenant monitoring, stress testing, or the validation of models.
The data and details of a commercial loan decision depends on different areas such as the core system, customer relationship management, scoring system, financial statement spreading system, exposure and deposit system. Such aggravated details are used in a frequent manner for the facilitation of different credit committee decisions and it is not stored in either system conveniently. Thus, banks might run the risks of losing the invaluable opportunities for repurposing an enriched dataset for the conduction of different meaningful activities. This might lead to loss of revenue, and lead to enhanced audit rates and reduced compliance.
Credit decision data is useful in answering different questions of the regulators
According to the latest financial crisis, there are few banks which do not store data electronically from the lacked systems and credit decisioning procedures for tracking the covenant compliance. Besides this, the regulatory expectations for the storage, retention and reporting of data have enhanced in a considerable manner. Both the auditors and regulators need that banks should capture as well as store different crucial key points as well as collateral details in order to make an informed decision. Standalone and antiquated systems do not accomplish such demands or optimize any revenues.
Entering the period of modern commercial lending decisions online
Data warehouse plays an integral role in bringing an improvement in the credit lending decisioning process. It offers different benefits such as improvement of the loans at a faster rate which will increase the loan throutput and closure rate of the banks. It also helps in covenant reporting and monitoring in an automated way. It also ensures reduced regulatory compliance prices. It also provides the capabilities for re-using the origination data for the validation of model and stress testing. It is also effective in more consistent underwriting as well as providing better returns on the risks.
Faster loan approvals enhance the productivity and loan closure rate of loans
Approval of loans might lead to bottlenecks, as the deals might surpass the credit authority. There are plethoras of modern credit decisioning systems that are known to assign approvals to reroute requests and the right credit officer when the resources are not in the office. Bankers make use of data warehouses for bringing an improvement in the efficiency, accuracy and speed of the loan decision process. It helps in enhancing the revenue of the system. Credit teams are known to add new approvers on a specific system and maintain a schedule or service level which will be outlining the tasks of the credit process which needs to be completed.
Such technical efficiencies are effective in reducing the cycles for making credit decisions. In case a process of complicated commercial credit procedure is reduced, the profitability and productivity will increase in a dramatically way, which might lead to an increase in the loan throughout in a significant manner.
Automated covenants reporting and monitoring
The data warehousing solutions can raise the scrutiny of covenant reporting and monitoring. For instance, the regulators are providing MRAs or Matters Requiring Attention to different banks for bringing an improvement in the compliance reporting and systematic monitoring for different non-financial and financial covenants.
An effective and improved credit decision process is known to capture the covenants during credit underwriting as well as tracking them during the life of the loan. Banks can choose from a standard covenants library. Integrating with data warehouse solutions can help in testing the financial covenants in an automated manner as the annual, quarterly or monthly financial statements are found to be analyzed. Business line value or portfolio reports can be useful in identifying different customers who are not accomplishing the requirements and needs of the covenants. Thus, the banks will monitor the complete covenant resolution procedure and provide them an opportunity for curing the covenant as well as monitoring the cure periods. It is useful in bringing an improvement in the procedure.
The data warehouse solutions are used by the commercial lenders on a wide scale for the identification of different trends of a bank. It also provides a competitive edge and increase the commercial portfolio revenue. It also helps in spotting the performance trend of the financials of the borrowers and different industry and regional trends.