Hindrances to sound loan review scoping
A portfolio can be sliced in many ways to draw out both the obvious and less apparent data to guide the scoping process. Unfortunately, effective scoping is often hindered by several persistent challenges:
- Data limitations
Loan review can only scope based on the data it has—and how it’s presented. Missing data elements (like NAICS codes) or poor data quality (no validation or controls) make it difficult, sometimes impossible, to build a usable scope. This isn’t a minor inconvenience; it’s a safety and soundness issue that warrants immediate board attention and a directive to management to fix it. Making a business case for loan review automation is a good first step toward efficiency.
- Organizational silos
Loan review scope is often constrained by how the bank is organized. Many institutions present data by market, cost center, or region—each essentially its own island. For example, if cattle lending occurs across four markets, reviewing it holistically requires manual effort just to piece together a universe from which to draw a sample. Most loan review teams don’t have the luxury of this kind of extra-curricular effort. As a result, targeted and effective loan reviews often don’t happen.
- Threshold limitations
Penetration thresholds—like reviewing 40% of exposure in a given area—may sound good on paper, but they often skew focus toward size instead of risk. The largest exposures may be reviewed the most, yet often carry the least risk and already receive scrutiny elsewhere in the organization. Meanwhile, genuinely risky segments can go unnoticed because they fall outside the threshold.
