Unlock new customers with our credit decisioning software powered by AI designed to enhance the lending process. Our proprietary AI solution can increase lending, reduce defaults and provide real-time data analysis. By providing a quick, reliable and efficient AI-powered credit risk decision engine, your business can better manage risks and prevent losses from defaulted loans. Discover how we can harness the power of your data with a free demo
Credit decisioning is the process of reviewing credit history, financial data and other key risk indicators to determine whether a borrower qualifies for a loan. The process can be time-consuming as it involves reviewing many different factors such as a borrower’s income, past payments and assets, as well as calculating interest rates.
The main issue with this process is that dependable borrowers have been denied credit for reasons such as a limited credit history, postal code, ethnicity and gender. These biases have prevented customers access to credit and restricted lenders from a reliable consumer base. However, when our proprietary AI is coupled with a risk decisioning platform, it eliminates bias by assessing potential based on a borrower’s behaviour, patterns and open banking data. This solution quickly and efficiently analyses various forms of financial data to determine a loan amount a borrower can afford, eliminating bias and risk of defaults.
Our credit risk engine equips lenders with the tools to improve borrower outcomes, reduce default rates and expand credit access to a wider base.
AI-powered credit risk decision engine reduces the amount of time spent on reviewing documents, bank statements and credit scores. By reviewing open banking data and other live data sources, our solution provides a real-time view of a borrower’s financial situation, enabling both quick and reliable decisions. By optimising the decision-making process, more loans are granted to suitable borrowers, increasing approval rates while maintaining low risk and long-term sustainability.
Ongoing affordability monitoring is a proactive measure designed to prevent loans from defaulting. Based on continuous data that is received, our AI-powered solution supports better outcomes for borrowers by detecting early signs of financial strain and enabling timely interventions.
Enhanced credit decisioning software results in approving more loans to dependable borrowers. This optimised process not only results in quicker approval, but it can lead to a stronger, more balanced portfolio that reduces default risk and increases overall profitability through unbiased data-driven lending.
Up to
25%
Reduction in Default Rate
Our goal is to utilise AI in a way that helps lenders enhance operations, while providing more borrowers with access to credit. We feel this is the ultimate win/win for all parties involved, by providing lenders with the solutions to better price risk and assign interest rates, we can unlock credit for millions of trustworthy borrowers who have been excluded due to outdated assessment methods.
Rapidly detect vulnerability in your loan book
Step 1
Share your data through our secure vault
- Data accepted in heterogeneous formats
- No PII required
- ISO 27001 certified
Step 2
Loan book data assessed by FIOLA®
- Data QA process
- Transited to the FIOLA® risk engine
- Data screened through 300+ factors to identify risk
Step 3
See your results
- Vulnerability analysis
- Capital at risk
- Probability of default
- Summary & recommendations
If you can't find what you're looking for, feel free to reach out to our customer support team for further assistance.
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By taking real-time anonymised data from multiple sources, our risk engine is able to not only calculate repayment ability (the focus of our competitors), but, by using advanced ML techniques, is able to accurately measure repayment capability too. In other words, not only are we able to assess whether a borrower has the ability to repay a loan or other form of credit but, also, given their recent financial behaviour and spending patterns, what is the likelihood that they will repay this loan, or will they prioritise other non-essential expenditure instead.
How does Finexos’ approach differ from our competitors?
By taking real-time anonymised data from multiple sources, our risk engine is able to not only calculate repayment ability (the focus of our competitors), but, by using advanced ML techniques, is able to accurately measure repayment capability too. In other words, not only are we able to assess whether a borrower has the ability to repay a loan or other form of credit but, also, given their recent financial behaviour and spending patterns, what is the likelihood that they will repay this loan, or will they prioritise other non-essential expenditure instead.
Does Finexos provide consumer financial transaction data?
No, Finexos is a data intelligence provider that analyses transaction data provided by our customers. Finexos is able to integrate with all Open Banking providers and take data in heterogeneous formats.
Finexos offers an advanced AI solution that manages the time-consuming process of credit decisioning. This provides credit providers with the time to concentrate on other areas to serve their clients. Banks, digital banks, credit unions and fintechs can all benefit from quick, dependable lending decisions to strengthen their portfolio, reduce risk and boost long-term performance.
Schedule a meeting with our helpful team and see how our credit decisioning software coupled with AI can streamline processes, improve decisioning and reduce credit risks across your portfolio.
Read more about what we’ve been up to on our mission to safely enable more people to access affordable credit.
Today, credit scores are a crucial part of everyday life. They affect everything from mortgages to mobile phone contracts, and a poor score or lack of history can be a real barrier. But when were credit scores invented and how did they evolve?
Lending analytics uses data to offer valuable insights for credit unions, banks, fintech and NBFCs (non-bank financial companies) to make faster and better decisions. It efficiently evaluates, processes and completes financial analysis on loan applications.
The Financial Conduct Authority’s (FCA) Consumer Duty has redefined how financial services companies approach customer protection. At its heart are the four Consumer Duty outcomes – a framework designed to ensure products and services not only meet regulatory expectations but actively deliver good results for consumers.
Data from Fair4All Finance shows that 20.3 million people were living in financially vulnerable circumstances as of 2024 – an increase of 16% from 2022. Financial vulnerability can be caused by a range of factors but is universally harmful to both affected individuals and lenders.
An affordability check determines whether a borrower is qualified to receive a loan. Many factors go into deciding whether a borrower is qualified, such as their income, regular bills and in some cases even postal code.
Affordability assessments are a crucial part of the approval process for almost any financial product, from mortgages to personal loans. But what are they, how are they used, why are they so important, what criteria do they assess and what does the process look like?
The Bank of England’s latest survey on AI in financial services revealed that 75% of firms are already using artificial intelligence (AI), with a further 10% planning to use AI over the next three years. The development and implementation of AI programs requires significant financial and operational investment which not all lenders have the capabilities to undertake.
AI is transforming lending operations and unlocking a world of possibilities for consumers and lenders alike. By providing tools to improve decision-making, the utilisation of AI in lending is helping to create more financial inclusion and credit access for an underserved market. A credit decision engine that uses advanced AI also reduces operational overheads and increases efficiency.
The adoption of generative AI for the finance sector is becoming essential for managing data, mitigating risks and enabling data-driven decisions. Businesses embracing this solution are solving challenges faster and gaining a competitive edge in an ever-changing landscape. Many sectors are already using a form of AI to become more efficient, but generative AI is capable of doing so much more.
Optimising and future-proofing Loan Management Software (LMS) is crucial for adapting to evolving market demands and thriving in a competitive landscape. The use of AI is growing as a means to this end, but what are the key considerations for LMS providers when adopting it to achieve the best results?
The Consumer Duty has reshaped the regulatory landscape for UK financial services and is increasingly becoming the underpinning principal of the FCA’s supervisory approach. It sets high standards of consumer protection across financial services and requires firms to put their customers’ needs first. Lenders must ensure that their products deliver genuine value, protect customers from foreseeable harm, and equip them with the information necessary to make informed decisions.
The Bank of England’s latest survey on AI in financial services revealed that 75% of firms are already using artificial intelligence (AI), with a further 10% planning to use AI over the next three years. The development and implementation of AI programs requires significant financial and operational investment which not all lenders have the capabilities to undertake.
In a recent BBC interview, the EU’s Competition Chief, Margrethe Vestager, expressed her concerns about the potential for AI to amplify bias or discrimination in loan and mortgage decisions.
