Aug 2021 | Open Banking |
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Discover your performance uplift

One of the main benefits of transactional data is the enrichment benefit it can provide to traditional data models and scores. The data can help deliver several different operational improvement gains. To demonstrate the value of transactional data, we’ve developed an uplift calculator that looks at the improvement of the Gini-coefficient and potential impact on non-performing loans management. This will give you an indication of the value that transactional data can bring to your business.

Gini co-efficient uplift calculator

The Gini Coefficient is a statistical measure. We use Gini to assess how well scoring models differentiate between good and bad customer credit applications. The higher the Gini, the more accurate the decisioning model. The more accurate the models perform, the more profitable a business should become. By utilising transactional data within the model development, you can increase the Gini coefficient and deliver more accurate decisions.

Enter your Current Gini

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Projected improvement in Non Performing Loan management

Transactional data can be used to enhance early warning indicators to identify customers falling into debt so you can take fast and appropriate action to minimise losses.

Early Stage (days 1-30)

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Recovery (days 31-90)

0% 100%

Default (>90 days)

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The above calculation and results are only indicative and have been created based on simple inputs to demonstrate the potential uplift. In reality every business is different, and therefore the actual results could be lower (or indeed higher) than highlighted in the calculator. To more accurately assess the value of transactional insight for your business, we would need to understand your current circumstances and KPIs in more detail. We work with each client to develop a business case based on current performance KPIs to demonstrate a more accurate view of the likely performance uplift for each specific business.

What you can expect: some of our recent projects

Transactional score

+60%

Gini using transactional data only

Credit Risk Origination

25%

increase on the existing scorecard

Acceptance

+3%

Improvement in approval rates

-18%

Decrease in number of delinquent accounts

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