Blog
Insights, Case Studies and Product Deep-Dives
How banks, lenders and insurers use Zoral fOS to automate lending, banking and finance operations, with the numbers behind the results.

5 min read
Zoral fOS: one platform at the centre of your lending
Your core isn’t the problem. Everything around it is. How Zoral fOS automates lending, banking and finance operations around the systems you already run.
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Technical7 min read
Conversational onboarding: chat that follows your bank’s rules
Customers can now explain their situation in their own words. The hard part is control. How the chat channel uses the same workflows, credit rules and audit trail as every other channel.
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Product4 min read
Customer, staff and partner screens your bank can maintain
Closing the gap between the experience a bank thinks it offers and the one customers see takes many small changes, made quickly, by the people who see the problem.
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Product4 min read
Checked document data, straight into your credit decisions
Loan-file documents, sorted, read and checked before anyone relies on them, with the data going straight into the credit decision.
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Product4 min read
Automation that keeps working when screens change
Many portals and old systems offer no way to connect. Zoral Resilient RPA reads and enters the data on screen, inside your lending workflows.
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Product4 min read
One record of every application, decision and change
Your credit team, auditors and supervisors should work from one record. Here is why Zoral Data Fabric sits at the centre of Zoral fOS.
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Product8 min read
One decision engine, from first lead to final payment
The second your customer arrives, you need to start making decisions. How one decision engine handles them all, from first lead to final payment.
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Case Study7 min read
Pricing motor insurance at quote time, on more than claims
Predicting claims is only part of the picture. How a motor insurance company priced at quote time on default, cancellation, renewal, fraud and add-on sales too.
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Case Study9 min read
Lending to mobile customers with no credit file
Can mobile-operator data predict credit risk where bureau data is thin or missing? How three tuned models supported a micro-loan pilot.
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Case Study6 min read
Automating underwriting across stores and online
A consumer lender with a large store network automated underwriting in stores and online, and its operating costs stopped rising with the size of its portfolio.
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Case Study6 min read
SME underwriting that scales without losing consistency
A North American SME lender had good underwriters, but not enough of them, and results varied from one to the next. How automated underwriting changed that.
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Case Study5 min read
Pricing leads before you buy them
Should we buy this lead, and at what price? How a global lender scored every lead in real time, across countries and lead generators.
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