With increasing pressure on lenders to illustrate and stimulate small business lending are you optimally placed to clearly evaluate requests for credit, set appropriate lending terms and make confident lending decisions? With increasing pressure on lenders to illustrate and stimulate small business lending are you optimally placed to clearly evaluate requests for credit, set appropriate lending terms and make confident lending decisions?
Commercial scorecards can be used at the point of acquisition to accurately assess risk and help lenders to make decisions on whether to lend to businesses. In addition, they can be used within a customer management environment and are often used to support with Basel provisioning.
Experian has a wealth of data sources and experience in combining these to develop bespoke commercial scorecards that can help you, as a lender, achieve business requirements.
Our scorecards can help you with:
- Improved lending decisions
- Supporting regulatory requirements
- The potential to offer the right product terms (including decisioning)
- Managing credit risk
- Incorporating new data sources into your decisions to increase predictive capability
In addition, they will:
- Reflect the latest market conditions
- Provide an up-to-date profile of your customers – new and current
- Optimally blend commercial Delphi data, commercial CAIS & consumer data from Directors/Proprietors/Sole Traders (where applicable) along with any additional necessary data
- Provide a multi-purpose use by supporting Basel provisioning in addition to predicting risk – there is a proven relationship between Commercial Delphi score and profitability of debt.
- Reduce the number of referrals and therefore associated underwriting costs
- Help you make faster decisions that in turn can improve customer experience
How it works
A range of modeling algorithms are available including logistic and linear regression modeling techniques. Considering all available predictive data items, a scorecard will be produced that combines these to output a score which accurately predicts any associated risk or concern of the applicant based on their profile and your policy and scoring rules. This score can then be incorporated into existing processes, allowing increased automation of your decisioning.