One of the primary inefficiencies that most hinders the lending process is a lack of Straight-Through Processing. Let’s begin with loan origination by way of example. When considering a credit, information regarding the borrower must be gathered, documented, and be made accessible to other employees within the financial institution involved in the credit origination and analysis process. If a single piece of data is required in multiple places along the credit application process, and it is re-keyed several times, there is risk that data will not be consistent. For example, client related data that is gathered from the bank’s CRM system, a report  generated from the core banking system, a risk analysis generated either manually by a credit analyst or by a piece of risk analysis software, along with market data and information about the project. All this combined with any other data the relationship manager deems relevant is included in the credit file that is now growing at an alarming rate. The resulting loan application process can quickly become unruly, disjointed, inconsistent and impossible to view as a concerted whole.  Even if you have credit application software, it is likely that certain data must be acquired from a secondary source - the CRM system, as well as from a third source – either the risk analysis software or the credit analyst’s Excel sheet. These three systems are often standalone systems and require staff to manually rekey the data from the CRM and Risk software systems into the credit application software. This increases the likelihood that the data will be inconsistent, and increases the operational risk associated with re-keying and slowing the whole process down, tying up time and resources. To add to the complexities, once the decision has been made to approve the loan, the manual booking procedure will require taking the credit approval offline and rekeying data, adding yet another opportunity for error.

Gathering and documenting borrower data can be a tedious process as relevant information comes from a myriad of sources. Relevant information includes items such as: the borrower’s current banking information, facilities, aggregated exposures; as well as demographic information, industry and market data, related parties, ownership structure, financial analyses, customer related documentation, correspondence and information gleaned from external sources such as credit bureaus and rating companies. Financial institution on top of their processes will ensure that this task need be performed only one time. Once keyed in, the data persists, precluding the need for rekeying and become accessible to other employees. Adopting this practice will reduce opportunity for discrepancies and slip-ups, maintaining data integrity.

Customer data should only be updated incrementally as the loan is reviewed, renewed, or additional credit is requested, notwithstanding any noteworthy borrower or market related events. Throughout the life of the loan, noteworthy events may occur either directly affecting the borrower or affecting the industry in which the borrower operates. This data, similar to the initial borrower information gathered and recorded, should be documented and made accessible to all involved in the credit management process. This capability is known as Straight-Through Processing (STP) and if properly implemented and utilised, increases the quality of the bank’s data and the efficiency in which credit is analyzed and decisions are made.