Credit scoring helps banks and financial institutions in limit-setting and pricing decisions. While every project undertaken in credit scoring is targeted at a specific outcome, in terms of changes in approval rate, loss-rate or cure-rate, etc., there is not much clarity on the revenue impact of the implementation. There is no uniform or consistent approach that exists within the industry to address this issue.
Benefits of Application Scoring:
There can be several business objectives for developing an application scorecard. The possible benefits from implementing an application scorecard can be broadly categorized as follows:
- Profitability increase: Implementing an application scorecard allows institutions to approve more loans without undertaking higher risk.
- Loss reduction: In geographies where the credit market is saturated and there is not much scope for expansion in terms of volume, benefits from application redevelopment can reduce losses by reducing bad-debt.
- Assessment cost reduction: In markets where the credit decision process is not automated and a substantial amount of manual assessment is involved, the implementation of an application scorecard can help reduce manual assessment cost.
- Regulatory compliance assurance: Lending institutions using the advanced internal rating based (A-IRB) approach need to have internal estimates of Probability of Default (PD), Exposure at Default (EAD), and Loss Ggiven default (LGD) for their assets.
Application scoring models are widely used by banks and financial institutions for credit assessment of new applicants. However, quite often the quantitative benefits of implementing these models remain unaccounted for leaving stakeholders uncertain about the extent of their impact.
Read on to know how application scoring models can be extended to other areas of credit risk modeling, including behavior and collection scoring and provide a risk-manager in a lending institution with an array of tools to manage model risk, based on quantitative measures.