TechRadiant ranks the top lending software development companies in 2026, evaluated on lending domain depth, security and compliance, credit decisioning and AI, coverage across origination, servicing and collections, and measured outcomes for named lenders.
Lending software is judged on two numbers: how fast a good borrower gets a decision, and how many bad loans slip through. The firms below have built platforms behind CHF 3.4 billion in annual mortgage volume, credit models that have scored more than 500 million loan applications, and AI workflows that cut underwriting time by two-thirds. They cover consumer, mortgage, SME and BNPL lending.
How TechRadiant ranks lending software development companies: Each company is scored on five criteria, lending domain depth, security and compliance, credit decisioning and AI, origination-to-servicing coverage, and client outcomes, using named lender clients, published volumes, awards and certifications. Facts are taken from each company's own case studies and official pages, verified in October 2026. Scores are TechRadiant's editorial assessment. Rankings reviewed quarterly.
Both routes are well served by the companies in this report. The right one depends on whether your edge is in the product itself or in how quickly you can get a standard product to market.
Few partners are strong across every stage. Use these six to see where a company's track record really sits before you shortlist it.
Praxent has worked only in financial services for more than 25 years, and lending is where its recent results are clearest. For Newity, a leading SBA loan facilitator, it built AI-powered lending workflows that delivered 3x faster funding and 67% faster underwriting, a rare example of AI shortening a real credit process at a named lender. It also modernizes legacy lending and banking systems: its PraxentDecode method maps an existing codebase before anything is rebuilt, and its PraxentGuard framework adds 29 AI security checks so risk teams can sign off. Praxent offers outcome-based pricing, tying part of its fee to the KPI the client cares about.
Django Stars has built software since 2008 and is ISO/IEC 27001 certified, and mortgage and lending platforms are the core of its fintech portfolio. For MoneyPark, the Swiss online mortgage broker, it built the platform behind CHF 3.4 billion in annual mortgage volume, more than 80,000 customers and over 150 B2B partners. For Molo Finance, the UK digital mortgage lender, it supported a platform that took £600 million in mortgage applications in 2021. It also works with Saudi bank SAIB. Its services cover consulting on lending architecture and regulation, custom web and mobile builds, credit bureau and KYC integrations, and legacy modernization.
HES FinTech has focused only on lending since 2012, combining its own LoanBox platform with custom lending software development. LoanBox covers digital onboarding, origination, credit decisioning, servicing and debt collection, and HES adds GiniMachine for AI credit decisions and CollectionAgent for AI-assisted collections. It has completed 160 projects in more than 30 countries with over 100 integrated APIs. For ID Finance it launched a custom LoanBox platform in three months. Tavan Bogd Finance runs more than 280,000 customers and a $63 million portfolio on its software, and ATM Online serves 500,000 users in Vietnam. HES opened a US office in 2025.
#4✓ VERIFIEDMiquido's standout lending work is Nextbank, an AI credit-scoring platform that has processed more than 500 million loan applications with 97% prediction accuracy and was a finalist at the 2019 Singapore FinTech Awards. That is one of the clearest examples in this report of machine learning running at real scale inside a lending decision. The Kraków studio has 15+ years of delivery, 200+ experts and more than 250 digital products shipped, and its banking clients include mBank, BNP Paribas and SBAB. It also brings award-winning mobile design, useful for consumer lenders whose application flow is the product. Its site lists no security certifications, so ask for ISO or SOC 2 status.
ScienceSoft has worked in IT since 1989 and in financial services since 2005, and it holds both ISO 27001 and ISO 9001 certification. Its loan management system for Atlas Credit won Best-in-Class Loan Management System at the Global FinTech Innovation Awards 2025, a strong independent signal for buyers comparing lending builders. Since 2016 it has also supported Kapital Bank, a commercial bank with more than $3.5 billion in assets, on its mobile banking app and IT consulting. ScienceSoft reports agentic AI work for a large US investment firm that made analysis up to 70% faster, and it covers lending, banking and insurance software from consulting to support.
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Comarch brings its own banking software and large implementation teams to incumbent banks digitising their lending. It is implementing the Comarch Open Platform omnichannel banking system for BRD Groupe Société Générale, Romania's third-largest bank, with Comarch Loan Origination embedded as the first added service to digitise corporate loan origination. Its finance, banking and insurance practice has more than 25 years of experience, its corporate banking software serves more than 2.5 million corporate clients worldwide, and its named bank clients include BNP Paribas Fortis and ING. Comarch suits banks that want a supported product with customization rather than a fully bespoke build.
10Clouds has moved further than most firms in this report toward AI inside the credit process itself. Its credit process offering uses AI for case intake, document analysis and drafting the decision documents a credit committee reviews, and it runs an AI-supported factoring sales research tool that it describes as live and expanding at a financial institution. The company has been building software since 2009, reports more than 120 AI deployments, and works with BNP Paribas Bank Polska and insurer PZU. It suits banks, factoring and leasing companies that want AI to speed up credit work while keeping humans in the approval loop.
Netguru's lending work centres on FairMoney, the mobile lending and banking platform, where it supplied senior engineers across lending, banking and KYC systems. It also built a mobile MVP for Moove, a mobility fintech that finances vehicles for ride-hailing drivers across three continents, delivered within a strict deadline, and a credit card program for a European automobile club on the Solaris banking-as-a-service platform. With more than 2,500 projects over 18+ years and a design-led approach, Netguru suits consumer lenders and embedded-finance brands where the borrower experience drives conversion. Its site describes PCI DSS and ISO 27001-aligned processes rather than listing certificates.
Kindgeek has worked only on fintech for more than 11 years and holds ISO 27001:2023 and ISO 9001:2015 certification, one of the clearest security baselines in this report. Its white-label modules include lending alongside neobanking, payments and insurtech, which lets lenders start from working components rather than a blank page. For Jaja Finance in the UK it built a banking app with a digital credit card and simple credit management. It has delivered more than 100 regulated projects, 70% of its clients arrive by referral, and partnerships last two years on average, which suits lenders that want a long-term engineering partner.
Ciklum's lending credentials come from operating at scale inside large lenders. For Santander it consistently met an 8-day SLA across more than 100 daily mortgage transfers, the kind of high-volume, deadline-bound process where errors directly affect borrowers. For Inspira it cut costs by 25% and made transactions 40% faster through banking automation. Its client list also includes First American and Atlantic Bay, both connected to US mortgage and title, alongside Payoneer and eToro. Ciklum typically works as embedded engineering and automation capacity inside a client's own teams, which suits lenders modernizing operations around an existing loan system.
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Answers to the questions banks, lenders and fintechs ask most often when building or replacing lending software in 2026.
A lending software development company builds the systems lenders use across the loan lifecycle: online applications and onboarding, loan origination, credit scoring and underwriting, loan servicing, and collections. Many also build broker portals, mortgage platforms and the integrations with credit bureaus, KYC providers and payment rails.
Some, like HES FinTech, combine their own lending platform with custom development. Others, like Django Stars or Praxent, build or modernize platforms around a lender's own products and data.
Choose a partner whose track record matches your loan type, because consumer, mortgage, SME and BNPL lending are very different builds.
A configurable lending platform gets a standard loan product to market fastest. HES FinTech, for example, launched a custom LoanBox platform for ID Finance in three months.
A custom build makes sense when your advantage is in the product or the data: unusual loan types, your own underwriting models, or tight integration with an existing platform or marketplace.
Many lenders combine both, using a platform for standard servicing and collections and custom software for origination and credit decisions where they compete.
AI is now shortening real credit processes, not just pilots. Praxent's work with Newity, an SBA loan facilitator, delivered 3x faster funding and 67% faster underwriting. 10Clouds uses AI for case intake, document analysis and drafting credit decision documents, and Miquido's Nextbank platform has scored more than 500 million loan applications.
The common pattern is AI preparing the work and humans approving the decision, which keeps lenders in control and easier to defend to regulators.
Ask any partner how decisions are explained, logged and reviewed, and how models are monitored for drift.
The EU AI Act classes AI used to assess creditworthiness of individuals as high-risk, with those obligations applying from 2 December 2027.
In practice, credit scoring systems used in the EU will need risk management, quality training data, logging, human oversight, transparency to borrowers and technical documentation.
Lenders building or replacing scoring systems now should design for these requirements from the start rather than retrofit them. A partner should be able to show how its models are documented, monitored and explained.
Yes. The EU's revised Consumer Credit Directive, which applies from 20 November 2026, brings many buy now, pay later and small, short-term credit products into scope that were previously exempt.
For software, that usually means adding creditworthiness assessments, clearer pre-contract information, advertising rules and records that show how each lending decision was made.
BNPL providers and retailers offering credit in the EU should check with their legal advisers which products are covered, then plan the system changes with their development partner.
It depends on how much you reuse. Configuring an existing lending platform can take a few months, as with HES FinTech's three-month launch for ID Finance.
A custom build covering origination, decisioning, servicing and collections takes considerably longer, because each stage needs integrations, testing and compliance sign-off. Many lenders release origination first and add servicing and collections in later phases.
Ask a partner for a phased plan that shows what goes live first, and how existing loans will be migrated safely if you are replacing an old system.
Most lending platforms connect to:
Integration quality decides how much of the lending decision can be automated. HES FinTech, for example, reports more than 100 integrated APIs and external services across its projects.
Ask a partner which of these they have already connected in your market.
These six questions separate lending specialists from general developers:
The answers usually narrow a long list to two or three serious candidates.
Human-verified rankings across AI, development, and marketing — updated quarterly.
