Picture a Thursday credit committee. A member points at the turnover figure in the memo and asks where it came from. If the analyst has to reopen a stack of bank statement PDFs to answer, the credit process is digital on the surface but not in how the work is done.
OJK’s banking digital transformation blueprint offers a framework for seeing that gap. For a credit team, the question is simple: what does the blueprint mean for day-to-day analysis?
What the blueprint is
OJK launched its banking digital transformation blueprint on 26 October 2021. It describes five connected elements: data, technology, IT risk management, collaboration and institutional arrangements. OJK’s release calls it a living document that will be updated as banking develops.
The blueprint is written for the banking sector, and a BPR is a bank. Multifinance companies are outside its scope, although their teams can use the same framework as a reference. It is a strategic reference, not a rule requiring a particular architecture or product.
Which elements sit closest to the credit team?
Technology, IT risk management and collaboration usually belong to the IT, risk and procurement functions. Data and institutional arrangements are felt most in the credit process, because that is where borrower documents become figures and figures become decisions. In our reading, they mean two practical things for an analyst:
- Traceable data. Every figure in the credit memo has a clear origin, down to the page of its source document.
- Decisions that stay with the analyst. Processed document output is input to judgement; the assessment and the responsibility remain with the credit team.
These two points are our application of the framework, not a quotation from OJK.
Traceable data
A faster credit process helps only when its output stays easy to review. The most useful measure is therefore not how fast documents are read, but how quickly an analyst can answer “where does this figure come from?”.
Example: a BPR analyses the bank statements of a fictitious borrower, CV Tirta Jaya. Total credits over six months come to IDR 1.250.000.000 and match the statement. Tracing the lines, the analyst finds that IDR 300.000.000 came from the owner’s personal account, which is not sales. Because every line links to its source page, the finding surfaces before the memo reaches committee, and the turnover used becomes IDR 950.000.000.
The same reading issue is covered in more detail in how to read extracted bank statement data.
The decision stays with the analyst
Digital document processing speeds up repetitive work: moving figures, building facility tables, finding the same name across several documents. Its output is most useful when it arrives as material ready to check, with its reasons, so the analyst can accept, correct or reject it.
Parts of a document that could not be read also need to be visible. A flagged gap can be filled by the analyst; a gap filled silently is only discovered at committee.
Summary for credit teams
- Read OJK’s blueprint as a direction, not a list of required products.
- Make sure every figure in the credit memo can be traced to its source page.
- Separate credits from turnover before figures enter the analysis.
- Ask for unreadable parts of a document to be flagged, not filled in.
Sxored helps credit teams work this way: it scores the extraction quality of each bank statement and lists the checks that failed, reads SLIK iDeb reports into facility tables, and suggests related parties with the reason for each match for the analyst to confirm. For the credit-report side of the same file, see how to read SLIK, CLIK, PEFINDO and CBI reports.
