Fintech · Case Study
A Credit Assessment SaaS That Finally Scores the Borrowers Banks Keep Rejecting.
No credit history doesn’t mean no creditworthiness. It just means the wrong tool is doing the scoring.
Project Overview
The Credit System Was Failing Millions of Worthy Borrowers. This SaaS Was Built to Fix That.
A UK-based fintech organisation founded on a single conviction. This was when they realised that creditworthiness is a matter of character, not just credit history. They approached Emvigo to build the platform that would prove it.
Traditional lenders rely on tax records, financial statements, and credit histories that millions of perfectly creditworthy people simply do not have. Thin-file applicants – those with zero or low credit history – are routinely excluded. This was not because they are risky, but because the data used to assess them tells an incomplete story.
Emvigo built a multi-tenant SaaS credit assessment platform using psychometric evaluation and device data to generate alternative credit scores. This gives lenders a reliable, data-backed way to say yes to borrowers the traditional system had taught them to reject.
Project At a Glance
Client
Industry
Emvigo’s Role
Technology Stack
- ReactJS
- NodeJS
- Python
- Flutter
- MongoDB
- AWS
- Kafka
- Kubernetes
The Challenge
A Creditworthiness Problem the Entire Lending Industry Had Decided to
Work Around
The gap between creditworthy people and credit access was not a new problem. It was a structural one, baked into assessment models that treated absence of data as evidence of risk. The client came to Emvigo not to patch that system, but to replace the logic driving it.
Customer Perspective
- Thin-file borrowers with no credit history had no reliable mechanism to demonstrate their actual willingness or ability to repay
- Applicants in emerging markets lacked the financial infrastructure that traditional lenders required as standard
- Being rejected by lenders left creditworthy individuals locked out of financial systems, with no alternative path to access
- Character and behavioural indicators of repayment reliability existed, but no mainstream credit tool was designed to capture them
Business & Operational Problems
- Building a psychometric and device-data scoring engine required an ML model architecture that could not be shared across tenants without compromising data confidentiality
- Multi-tenancy is needed to support four distinct deployment models within a single platform framework
- Score calculation was expected to return results within ten seconds, requiring significant infrastructure optimisation across large, complex device datasets
- The platform needed to be portable across AWS, alternative clouds, and on-premise environments without architectural rework
Building a fintech platform where data privacy, multi-tenancy, and processing speed all have to work together?
Emvigo engineers SaaS infrastructure where none of those demands are treated as trade-offs.
Product Strategy
Emvigo's Strategic Role: Engineering Fairness Into the Credit System's Infrastructure
The core strategic challenge was not building a scoring algorithm. It was building the infrastructure around it that made the algorithm ready for large-scale commercial use.
This worked across many lenders and regions, without compromising data confidentiality. That confidentiality made the entire model trustworthy.
Emvigo treated multi-tenancy architecture and processing speed as the two non-negotiable engineering constraints from day one. Designing the platform to flex across deployment models while returning scores fast enough to sit inside a real lending decision workflow.
Credit access is opportunity access. The engineering has to be good enough to hold that argument up, at scale, in production, under real lender scrutiny.
— Emvigo Engineering Team
01
Character as a Credit Signal
Psychometric and device-based data treated as primary scoring inputs, enabling genuinely alternative credit assessment.
02
Four-Model Multi-Tenancy Architecture
Shared, dedicated, on-premise, and white-label deployment options built into the core platform, giving lenders full control over the data environment and confidentiality.
03
Sub-Ten-Second Score Processing
EMR cluster parallelisation and chunked data execution designed to meet the ten-second score return requirement under real-world data volumes.
04
Cloud-Independent Infrastructure
AWS as default with full portability to alternative clouds and on-premise environments, built for lenders whose compliance requirements dictated deployment flexibility.
05
Agile Delivery Against a 12-Month Roadmap
10-day sprint cycles across development and QA, with load testing at every stage, delivering the product a month ahead of schedule and first customer onboarding in month four.
Our Solution
Two Scoring Products. One Platform. Thirty Microservices Holding It Together.
Emvigo delivered a multi-tenant SaaS credit assessment platform with two distinct scoring products – psychometric assessment and device data analysis. It was built on a 30+ microservice architecture designed for global lender deployment.
Psychometric Credit Assessment
Gamified behavioural assessments capturing character traits associated with repayment reliability, generating first-party credit scores for thin-file applicants with no dependency on financial history.
Device Data Credit Scoring
Privacy-consented metadata collection from iOS and Android devices, completing in under sixty seconds and returning a behavioural credit score in seconds based on how an individual uses their phone.
Four-Model Multi-Tenancy Framework
Shared environment, dedicated environment, on-premise, and white-label deployment options, giving each lender the data isolation and confidentiality model their compliance requirements demanded.
High-Speed Score Processing Engine
EMR cluster parallelisation with chunked data execution, delivering scores within the ten-second window required for real-time lending decision integration, with S3 data lake migration planned for growing data volumes.
Cloud-Independent Deployment Architecture
AWS-native infrastructure with full portability across alternative cloud environments and on-premise deployment, enabling lenders to migrate without platform rearchitecture using Kubernetes as the container orchestration layer.
Lender-Facing Multi-Tenant Admin Platform
A white-label capable administration environment giving lenders full control over tenant management, scoring configuration, and portfolio visibility across their borrower base.
Business Outcomes
Product Delivered a Month Early. 10+ Lenders Onboarded. 30+ Deployments in Year One.
10+
Customers Onboarded
30%
Higher ROI for Client
1 Million
Revenue Generated in 1 Year for Client
Product Delivered a Month Ahead of Schedule
Customer-ready state in three months, with the first lender onboarding completed in month four of the engagement.
10+ Lenders Onboarded Across Multiple Geographies
The platform's flexible multi-tenancy model enabled rapid expansion beyond the UK, with lenders across multiple markets onboarded within the first year of production deployment.
30+ Deployments in Year One
Deployment velocity confirmed both the platform's operational reliability and the market demand for alternative credit scoring at scale.
A Testimonial That Said It All
"Emvigo goes the extra mile to get things done because they can see the medium-to-long-term benefit of the tasks." — Client, UK Fintech Organisation
Achievement Unlocked: Results Like These
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