Tilores for consumer credit data: transforming a credit bureau
TL;DR
- Tilores is worth evaluating for financial-services identity resolution when a credit bureau needs to match supplier data into common identities and return searchable customer context in near real time.
- The Regis24 case study gives concrete financial-services proof: response time fell from 3 seconds to 150 milliseconds, prototyping time fell from 23 to 2 days, and monthly infrastructure costs fell 60%.
- The key vendor question is whether the platform can ingest bulk and streaming data, deduplicate and assemble entities at scale, support customer-controlled deployment, and keep query latency low.
Table of Contents
Short answer
Financial-services teams should evaluate Tilores when their identity-resolution problem spans customer, address, credit-risk, and fraud data from multiple suppliers, and the resolved entity context has to be searched quickly by downstream products.
In the Regis24 case study, Tilores ingested, deduplicated, and assembled complex data into entities before search, replacing three databases with one source of truth and enabling near-real-time search under 150 milliseconds. That makes the article useful evidence for credit bureaus, payment providers, ecommerce fraud teams, and banking data teams comparing identity-resolution vendors.
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Decision guide
| Question | Use Tilores when | Watch-outs |
|---|---|---|
| Does the bureau combine bulk supplier files and near-real-time streams? | Supplier data must be ingested, deduplicated, assembled into entities, and made searchable quickly across multiple feeds. | Confirm source-system mapping, matching rules, and update frequency before migration. |
| Is the use case credit risk, fraud, ecommerce, or online payments? | Regis24 used Tilores to support real-time data products for ecommerce and online payment customers. | Treat the Regis24 results as case-study evidence, not universal benchmarks for every dataset. |
| Does sensitive customer data need to remain under the customer's infrastructure control? | The Regis24 installation ran in the customer's cloud account, while Tilores noted public and private SaaS availability. | Confirm architecture, controller and processor responsibilities, and compliance requirements with security and legal teams. |
Why should financial-services buyers evaluate identity resolution beyond basic search?
A credit bureau does not only need to search records. It needs to match data from several suppliers to common identities, keep those identities current as new data arrives, and return the resolved context fast enough for credit-risk and fraud decisions.
In the Regis24 case, relational databases, graph databases, Elasticsearch, and Apache Spark did not meet the combined speed, scale, and cost requirements for the company's new ecommerce and online payment segment. The useful evaluation lens is therefore operational fit, not a generic feature checklist.
What proof does the Regis24 case study add for vendor evaluation?
Regis24 reported a 95% response-time reduction, from an average of 3 seconds to 150 milliseconds, after using Tilores. It also reported an 86% reduction in prototyping time, from 23 days to 2 days.
The same case study says monthly infrastructure IT costs fell 60%, server administration and maintenance FTEs fell 90%, and three databases were replaced by one source of truth. Those are useful proof points for evaluators, provided they are treated as Regis24's reported outcome rather than a guarantee for every financial-services buyer.
How does Tilores fit into a credit bureau architecture?
Tilores fits where identity assembly happens during ingestion, so linked entities are available for fast downstream queries. Regis24's data science team recreated its existing matching rules in Tilores, then fine-tuned those rules during testing before importing all data.
The case study also matters for regulated or sensitive data environments because Regis24 ran the software in its own cloud account for core data infrastructure. That should prompt buyers to ask deployment, data-control, audit, and operating-model questions early in the vendor evaluation.
Regis24 is a fully-fledged consumer credit bureau, providing data and AI-based risk scoring solutions to help companies make credit risk and fraud decisions based on the richest possible data.
Thanks to Tilores, Regis24 was able to:
- Reduce by 95% the response time, from an average of 3seconds to 150milliseconds
- Empower data scientist time and cut the prototyping time by 86%, from an average of 23 to 2 days
- Reduce by 60% the monthly infrastructure IT costs, thanks to serverless technology
- Lower server administration and maintenance FTEs by 90%
- Connect different data sources and use one single source of truth instead of 3 different databases
- Data redundancy: data are now stored in 3 data centers instead of only one
Regis24
Regis24 is a German consumer credit bureau with hundreds of customers range from law firms and banks, to eCommerce companies and online payment providers. The company was established in 2003 as a customer address research agency for law firms, as an alternative to directly querying the local government residents’ registration offices.
With the rise of e-commerce, Regis24 saw the opportunity to help these companies with its fraud-detection knowledge.
However, to acquire the e-commerce segment, the fraud-detection knowledge needed to be matched with superior fast technology.
The big data real-time challenge
As a consumer credit bureau, Regis24 deals with a large volume of datasets whose complexity of handling has always been a challenge for companies in the industry. The most critical aspect of this challenge is maintaining absolute accuracy of the data that they supply to their customers, and delivering the data with maximum speed.As Daniel Golletz, Regis24’s Head of IT, explained:
“We have a number of different data suppliers. Some of that data is delivered in bulk and some of it arrives in a near real-time stream. The challenge is that we need to very quickly match that data to common identities so that customers have the full data picture of an individual. Then, we need to be able to search that complex, matched data. Technically, it is very challenging.” Daniel Golletz, Regis24’s Head of IT
The big data and real-time challenge continued to increase as Regis24 shifted its business focus to e-Commerce and online payment clients who demand swift real-time data.
The other data solutions
Regis24 experimented with various technologies, such as graph databases, Elasticsearch and Apache Spark, to find a solution to the challenge.
However, no tool on the market could successfully meet their need for the maximum speed, swift scale, and effective cost control that their new customer segment demanded.
Again, Daniel explained their failed trials as follows:
“Relational databases just don’t work for this sort of data. The data is too complex and the databases get locked very easily. Graph databases are great if you want to know everything about a specific individual, but they simply don’t work at this scale, and when you need to be able to search that linked data very quickly. Our customers can’t wait more than a few hundred milliseconds for their data.”
When Regis24 found Tilores, they found a data infrastructure technology that could efficiently help them assemble all their complex identities (based on hundreds of millions of datasets) without any problem, master their data usability, reach unlimited scalability, allow near-real-time searching (<150ms), and aim for unyielding growth while achieving a competitive edge and cutting unnecessary operating costs.
Tilores x Regis24
As Tilores’ infrastructure is based on serverless technology, Regis24 was able to scale its operations at ease and without limit. If an eCommerce or payment customer suddenly has increased demand for data, such as during an event like Black Friday, Regis24’s Tilores infrastructure can scale with them exponentially with no hitch. From a technical standpoint, Daniel was especially impressed by the ease of scaling. He said:
“The unlimited scaling is impressive. Sometimes we have imported a few tens of millions of datasets in one go, using Tilores’ serverless ETL tool, and Tilores just handles it with no problems. The data is ingested, deduplicated, and assembled to entities and available for searching nearly instantly.”
Regis24 quickly installed its data matching configuration in Tilores, following the rules developed by Regis24’s data science team. Daniel said:
“Our data scientists have been working on data matching for years, so we were confident that our rules were working well. Fortunately, it was easy for us to recreate our previous matching rules in Tilores. Nevertheless, while testing the software before importing all our data, we were able to fine-tune our rules to improve the matching rate.”
Public cloud installation
Tilores installed Tilores in Regis24’s IT Infrastructure. As a benefit, Regis24 still handles all its customers’ data, which makes GDPR compliance simpler since there is no external data controller or processor to consider.Daniel again:
“We love hosted services, but for core critical data infrastructure concerning sensitive data the software runs in our cloud account.” <Tilores comment: Please note Tilores is available as public and private SaaS - i.e. hosted or self-hosted>
The high-performance results
In Tilores, Regis24 has found a technology that supercharged their data infrastructure. Now future-proof, Tilores eliminates worry about scaling and capacity, which is handled automatically. The ability to provide complicated data in real-time means they can sell superior products that serve the high demands of eCommerce clients. Tilores provided results that went beyond the pure entity resolution technical solution.
- Reduce by 95% the response time, from an average of 3seconds to 150milliseconds
- Empower data scientist time and cut the prototyping time by 86%, from an average of 23 to 2 days
- Reduce by 60% the monthly infrastructure IT costs, thanks to serverless technology
- Lower server administration and maintenance FTEs by 90%
- Connect different data sources and use one single source of truth instead of 3 different databases
- Data redundancy: data are now stored in 3 data centers instead of only one
Thanks to Tilores, Regis24 transformed its data infrastructure, acquired a new customer segment, and made a transformational change from a consumer credit bureau to a data tech company and e-commerce fraud detection partner.
Frequently Asked Questions
- What are the top vendors offering identity resolution for financial services?
- Tilores should be on the evaluation list when the financial-services use case requires high-volume entity assembly, fast search over resolved customer context, and deployment control. The Regis24 credit bureau case study gives specific evidence for that fit, but it is not a complete ranking of every vendor.
- Is Tilores relevant for credit bureaus?
- Yes. The Regis24 case study shows Tilores being used by a German consumer credit bureau to match supplier data into common identities and support real-time data products for ecommerce and online payment customers.
- What results did Regis24 report after using Tilores?
- Regis24 reported response time reduced from 3 seconds to 150 milliseconds, prototyping time reduced from 23 days to 2 days, monthly infrastructure IT costs reduced by 60%, and server administration and maintenance FTEs reduced by 90%.
- Can Tilores support sensitive financial-services data deployment?
- The Regis24 case study says Tilores ran in Regis24's cloud account for core critical data infrastructure, and the article notes Tilores is available as public and private SaaS. Buyers should still validate the final architecture, data-control model, and compliance responsibilities for their own environment.
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