Scores4All
Top 5 considerations when creating an in-house Data Science Team!
We're diving into the Dos and Don'ts of creating a Data Science Team.
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Carolyn Röhm
- Oct 10
- 3 min
What is the difference between a bureau score and a Scores4All collections score?
Mōrena It's been a hectic few weeks 🤩🌟🚀 I've attended two conferences, and they were excellent; I have been networking and meeting all...
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Scores4All
- Sep 6
- 4 min
How to maximise Customer Lifetime Value with Credit Bureau Data
How to enhance account management with credit bureau data.
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Carolyn Röhm
- Aug 17
- 6 min
How to use Tilt-by-Risk Principles to Design Effective Collections Strategies
Scorecards are the gold standard of retail credit risk assessment. So, you’ve got a scorecard! 🎉🤩🥳 Now what? The really great news is...
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Scores4All
- Jul 31
- 5 min
How to Better Unlock Untapped Potential: Harnessing the Predictive Power of Existing Data
The power of existing data In recent years, a number of terms have become the topic of choice in everyday conversations across the globe....
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Carolyn Röhm
- Jul 20
- 4 min
How the Credit Cycle, Credit Risk Cycle and Credit Risk Scores Interact
Take advantage of credit risk scores to manage credit risk during different phases of the credit cycle and credit risk life cycle.
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Scores4All
- Jul 13
- 4 min
How to Unlock Credit Risk Management: Create Competitive Advantage with Expert Models
Expert models are not a silver bullet, but they can be used effectively as an interim solution, on the journey to implementing bespoke score
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Carolyn Röhm
- Jul 5
- 4 min
Credit risk assessment: Why we're harnessing our powerful drive to improve the status quo
Eva and I have been working in retail consumer credit risk for a while; between us, we have over 50 years of experience. When it comes to...
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Carolyn Röhm
- May 25
- 4 min
What does exceptional customer service feel like - and how to create it?
We’ve recently embarked on our new venture, and as anyone who has ever done this knows, there are many demands on one’s attention. I’ve...
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Carolyn Röhm
- May 17
- 4 min
Perhaps I should have started with “Kia Ora”
Kia Ora, Thank you for stopping by and taking the time to let us introduce ourselves. I thought I would start by throwing out a few...
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Carolyn Röhm
- May 9
- 5 min
Surely you can't build predictive models without data?!?
How we can (and do) build models without historical data.
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