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Solvios is the leading IT company in the business to give you growth, revenue, and a global platform.
We build custom fintech software from digital banking platforms and payment processing systems to investment management tools, lending applications, and AI-integrated fraud detection for financial institutions, fintech startups, and enterprise financial technology companies that need software built to the reliability, security, and compliance standards that financial products demand. Our fintech software development team combines deep financial domain knowledge, PCI-DSS-aligned architecture, and a track record of delivering platforms that handle real money without failures that make headlines.
Years of Experience
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Solvios is a fintech software development company building custom digital banking platforms, payment processing systems, investment and wealth management applications, lending and credit software, and AI-integrated financial tools for financial institutions, fintech startups, and enterprise financial technology companies. We work across the full fintech technology stack — web, mobile, cloud, and AI with PCI-DSS compliance, financial data security, and regulatory architecture built into every engagement from the first day of discovery.
Custom online and mobile banking applications that give customers secure, real-time access to accounts, transfers, payments, and financial management built for the reliability and compliance posture that banking regulation requires.
End-to-end payment infrastructure including payment gateway integration, transaction processing, reconciliation, multi-currency support, and the PCI-DSS-compliant data architecture that payment card industry standards demand.
Portfolio management platforms, robo-advisory tools, investment tracking applications, and wealth management portals built for the data accuracy, real-time performance, and regulatory reporting that investment clients expect.
Loan origination systems, credit decisioning engines, borrower portals, and loan servicing platforms for consumer and commercial lending operations with automated underwriting, compliance controls, and collections workflow.
Real-time transaction monitoring, ML-based fraud detection, behavioral analytics, and risk scoring systems that protect financial platforms from fraud without introducing false positive rates that frustrate legitimate customers.
Fintech is one of the most technically demanding software categories there is not because the engineering is uniquely complex, but because the consequences of getting it wrong are immediate, financial, and public. A payment that fails silently. A fraud detection model that flags the wrong transactions. A compliance audit that finds gaps in the data architecture. We have built in this category for 13 years. Here is what we actually see when we start a fintech software engagement.
Financial platforms hold the most sensitive personal and financial data that exists. PCI-DSS compliance, SOC 2 audit readiness, end-to-end encryption, tokenization of cardholder data, and secrets management are not features to add before a security review; they are architectural decisions that shape how the entire system is designed. Fintech products built by teams without financial security experience accumulate vulnerabilities that compound over time and become expensive to fix after the product is in production.
Payment gateway integration, acquiring bank connectivity, payment scheme rules, chargeback workflows, multi-currency handling, and real-time settlement reconciliation are all significantly more complex in practice than they appear in API documentation. The edge cases of failed webhooks, partial captures, idempotency failures, scheme-specific decline codes are where most payment integrations break, and they almost always break at go-live with real transaction volume rather than in testing.
A fintech company operating in the US might need to address PCI-DSS, SOC 2, FinCEN AML/BSA, CFPB regulations, state money transmission licenses, SEC or FINRA requirements for investment products, and GDPR if any EU customers are involved. Each framework has its own data retention, reporting, and audit trail requirements. Fintech teams that try to address compliance after the product is built spend months retrofitting controls that should have been designed in from the start.
Financial platforms cannot be slow. A payment processing system that adds 400ms of latency to every transaction is unacceptable. A trading platform that lags at market open is a liability. The performance requirements of financial software are stricter than most other categories, and they need to be designed into the architecture from day one database indexing strategy, caching layer design, queue architecture, and horizontal scaling patterns all need to be right before the platform sees production transaction volume.
Fraud patterns evolve constantly. A rules-based fraud detection system that worked at launch becomes outdated within months as fraudsters adapt. ML-based approaches need to be retrained regularly and monitored for model drift. False positive rates that are acceptable at low volume become a customer experience problem at scale every legitimate transaction blocked is a customer who calls support or churns. Getting the balance right between security and friction requires a fraud management architecture designed for evolution, not just for launch.
Every fintech software engagement starts with the regulatory landscape, the transaction architecture, and the security requirements not with a feature list. The software is built to handle real financial transactions at production volume, pass compliance audits, and protect the financial data of real customers.
The fintech market spans regulated financial institutions at one end and early-stage startups disrupting specific payment or lending behaviors at the other. The compliance requirements, performance standards, and user experience expectations are different at each point on that spectrum. We have built for all of them.
Fintech Startups & Founders
MVP-to-production product engineering for founders building new financial technology products from the compliance architecture and security foundation through the first production release and the growth engineering that follows. We understand the regulatory constraints that determine whether a fintech product can operate legally in its target market, and we address them in the architecture from day one rather than treating them as a later problem.
Digital Banks & Neobanks
Core banking-adjacent software, customer-facing banking applications, card management infrastructure, and the compliance and reporting systems that digital banking operations require. We build for neobanks competing on user experience and speed while operating within the same regulatory framework as traditional banks.
Payment Companies & Payment Facilitators
Payment processing infrastructure, merchant onboarding platforms, payment orchestration layers, and the PCI-DSS-compliant architecture that payment companies need to operate. We have integrated with every major payment gateway and understand the operational complexity of payment systems at scale.
Investment Firms & Wealth Management Companies
Portfolio management platforms, client portals, robo-advisory tools, and the compliance and reporting infrastructure that investment firms need to manage client assets and satisfy regulatory obligations. We have built comprehensive wealth management software specifically and understand the data accuracy requirements that investment products demand.
Lending Companies & BNPL Providers
Loan origination systems, credit decisioning platforms, borrower portals, and servicing infrastructure for consumer and commercial lenders. We understand the underwriting workflow, the collections compliance requirements, and the data architecture that lending operations depend on to manage their book of business.
Enterprise Financial Institutions
Custom financial software for banks, insurance companies, and large financial services organizations that need bespoke systems built around their specific workflow, compliance obligations, and integration landscape rather than adapting a generic financial software platform that was not designed for their operating context.
We will map your compliance obligations, identify the payment architecture decisions that matter most, and give you an honest path forward before any code is written. Response within 24 hours.
These are the capabilities that financial software requires to operate securely, handle production transaction volume, satisfy compliance audits, and retain the trust of customers who are letting your platform touch their money.
Tokenization of cardholder data, point-to-point encryption, PCI-DSS scope reduction, and the security controls required for compliance at your transaction volume designed into the architecture from day one, not reviewed before the QSA assessment.
Sub-second transaction authorization, idempotent payment flows, duplicate transaction detection, and the queue architecture that keeps payment processing reliable under load spikes because a payment system that degrades under volume is a payment system that cannot be trusted.
Identity verification, document check integration, sanctions screening, PEP list monitoring, transaction monitoring for suspicious activity, SAR filing support, and the onboarding compliance workflow that satisfies FinCEN requirements without the customer friction that drives legitimate users away.
Real-time transaction scoring combining rule-based signals and ML model outputs, behavioral analytics, device fingerprinting, velocity checks, and the model monitoring infrastructure that keeps detection accuracy current as fraud patterns evolve.
AES-256 encryption at rest, TLS 1.3 in transit, secrets management for API keys and credentials, HSM integration for cryptographic key management where volume justifies it, and the access control architecture that limits financial data exposure to the minimum necessary.
Automated reconciliation between payment provider settlement files and internal ledger entries, exception handling and investigation workflow, and the financial reporting layer that gives finance teams daily visibility into transaction flow and cash position.
Immutable transaction audit logs, regulatory report data capture and export, compliance event logging, and the evidence collection infrastructure that makes a compliance audit a reporting exercise rather than a reconstruction project.
Plaid, Stripe, MX, and open banking API integration for account aggregation and payment initiation with the data normalization, error handling, and connection monitoring that keeps financial data feeds accurate and current.
AI in fintech software is not about adding a chatbot to the banking app or displaying a spending insights widget that no one looks at. It is about building systems where machine learning improves financial decisions, detects fraud before transactions complete, personalizes financial products at the individual customer level, and automates the credit and risk assessment processes that determine whether a business can scale its lending or investment operations without proportionally scaling headcount. Every fintech platform we build is architected with AI capability as a first-class consideration from the first sprint.
ML models scoring transactions at authorization time combining behavioral signals, device context, transaction patterns, network signals, and velocity indicators with sub-100ms decision latency so the fraud check does not add perceptible delay to the payment experience. Models are monitored for drift, retrained on current fraud patterns, and operated alongside rule-based controls that handle the deterministic fraud signals ML is not well-suited for.
Highlights:
ML models scoring transactions at authorization time combining behavioral signals, device context, transaction patterns, network signals, and velocity indicators with sub-100ms decision latency so the fraud check does not add perceptible delay to the payment experience. Models are monitored for drift, retrained on current fraud patterns, and operated alongside rule-based controls that handle the deterministic fraud signals ML is not well-suited for.
Highlights:
Most fintech software projects fail not because of the core product idea but because the compliance architecture was addressed too late, the payment integration was underscoped, or the performance requirements of financial transaction volume were not designed into the system from the start. Our fintech software development services follow a structured, security-first delivery methodology designed to surface those problems at discovery, when they are cheap to fix.
Here's exactly how it works.
We map your regulatory obligations, payment architecture requirements, security constraints, third-party financial data dependencies, and user roles. Output is a project scope that includes a compliance framework, PCI-DSS scope definition, integration plan, and risk register before any development begins.
Security-first technical architecture finalized with the financial data model, payment flow design, and compliance controls built in. UI/UX wireframes designed for the financial user whether that is a consumer banking customer, an investment advisor, or a lending operations team before development starts.
Two-week sprints with working software delivered at the end of each cycle. PCI-DSS controls, payment gateway integration, authentication architecture, and fraud detection baseline are addressed in the first two sprints not deferred to the end of the build where timeline pressure prevents getting them right.
Dedicated QA on every module alongside penetration testing, PCI-DSS compliance validation, payment integration testing at production-realistic transaction volumes, and fraud detection accuracy testing. Financial software QA requires testing the failure modes, partial captures, webhook failures, network timeouts, not just the happy path.
Staged rollout to production with PCI-DSS documentation finalized, payment provider certifications completed where required, compliance controls verified, and post-launch transaction monitoring active. Financial platform go-lives require a higher level of operational readiness than standard software deployments.
Post-launch monitoring, fraud model retraining, compliance maintenance as regulations evolve, payment integration updates as gateway APIs change, and feature development. Fintech platforms require continuous attention, fraud patterns change, regulations update, and payment scheme rules evolve.
Sports and fitness app projects range from a focused MVP build to a multi-year platform evolution programme. The right engagement model depends on how well-defined the product is, how quickly you need to ship, and how much ongoing iteration the product requires after launch.
You are building a multi-quarter fintech platform, a digital banking product, an investment management system, a lending platform scaling a financial product into new markets, or augmenting your in-house team with fintech-specific expertise without the cost and lead time of full-time hires.
Hand-picked engineers with fintech experience, a QA specialist, and a technical lead working exclusively on your platform. Sprint planning and product demos run on your calendar. PCI-DSS compliance architecture, payment integration, fraud detection, and AI financial models are all handled in-house.
Monthly retainer. No surprise invoices, no scope-creep billing. Team composition flexes as your fintech roadmap evolves.
3–10 engineers
6-month minimum
Scales with 30-day notice
Most financial technology companies start with one model and evolve into another as the product scales and the compliance footprint grows. Let's figure out the right starting point together.
Building fintech software requires a development team that understands the consequences of getting financial software wrong and designs every system with that understanding embedded in the architecture. Here is what makes the difference in practice.
Security Is Architecture, Not a Feature
PCI-DSS compliance, financial data encryption, tokenization, secrets management, and the access control architecture that financial data demands all of these are addressed in the first sprint, not reviewed before the security audit. Financial software that was not designed with security as an architectural constraint accumulates vulnerabilities that are expensive to fix and embarrassing when they surface.
Payment Integration Experience Across Major Providers
Stripe, Braintree, Adyen, PayPal, Authorize.Net, Razorpay, and banking-as-a-service platforms have done real payment integrations at production transaction volume. We know where the API documentation does not match live behavior, where idempotency needs to be implemented at the application layer rather than trusted to the gateway, and where reconciliation complexity lives that never appears in the initial integration scope.
AI-Integrated Financial Software from Day One
Fraud detection, credit scoring, financial document processing, and personalized product recommendation all require a data architecture designed to support ML workloads from the start. We address the AI architecture strategy in discovery so that ML capabilities are integrated components of the financial platform rather than bolt-on features that require a data layer rebuild to implement.
Compliance Architecture That Survives the First Audit
PCI-DSS, SOC 2, AML/BSA, and GDPR compliance controls designed into the platform from day one not retrofitted before the first auditor arrives. Financial software that passes its first compliance audit is software that was built by a team that understood the compliance requirements before the architecture was designed.
Delivered Financial Products Across the Spectrum
Wealth management platforms, school fee financing tools, real-time bidding platforms with financial transaction architecture have delivered fintech products that handle real financial workflows at production scale. The case studies on this page are real projects with real financial complexity, not simplified demos.
US-Based Communication, Global Engineering Capacity
Project management and client communication run on US business hours. Fintech projects in particular require fast, clear communication when compliance decisions need to be made, payment integration problems surface, or security findings require immediate architectural changes. The time zone alignment matters more in fintech than in most other software categories.
Honest answers to the questions every fintech founder, financial institution CTO, and product manager asks before choosing a fintech software development company. If something is not covered here, our solution architects will walk you through it on a discovery call, no sales pitch, no fluff.
Cost depends on scope and compliance requirements. A payment integration with reconciliation and basic reporting typically starts at $20,000–$50,000. A lending portal with credit decisioning integration and borrower self-service ranges from $60,000 to $150,000. A digital banking application with account management, transfers, and card controls is typically $100,000–$250,000. A full investment management platform with portfolio tracking, robo-advisory logic, and regulatory reporting ranges from $150,000 to $400,000+. Solvios provides fixed-price proposals after a compliance and product discovery session.
A targeted payment integration with reconciliation and reporting takes 8-14 weeks. A lending portal with credit decisioning and borrower self-service takes 4-7 months. A digital banking application with full account management takes 6–10 months. A wealth management platform with investment tracking and advisory tools typically takes 8-14 months. The biggest variable is regulatory complexity and third-party financial API integration which is why we invest 2-4 weeks in compliance and product discovery before any development begins.
PCI-DSS compliance is an architecture decision, not a pre-launch checklist. We define PCI-DSS scope during discovery the goal is to minimize the cardholder data environment through tokenization and out-of-scope payment flows wherever possible. Where in-scope systems are unavoidable, encryption, access controls, logging, and vulnerability management are designed into the architecture from the first sprint. We support clients through their QSA assessment and produce the required documentation as part of the delivery, not as a separate compliance project.
Yes. Payment gateway integration is one of our core technical competencies for fintech software development. We have integrated with Stripe, Braintree, Adyen, PayPal, Authorize.Net, Square, and Razorpay and with banking-as-a-service platforms including Plaid and MX for account aggregation and payment initiation. We handle the integration architecture, idempotency and retry logic, webhook reliability, reconciliation, and the ongoing maintenance as gateway APIs evolve.
AI-integrated fintech software development means building financial platforms where ML and AI capabilities are part of the core product architecture, not add-ons. In fintech this includes real-time fraud detection models scoring transactions at authorization, ML-based credit scoring incorporating alternative data signals, automated financial document processing extracting structured data from bank statements and loan documents, personalized financial product recommendation, spending intelligence and cash flow forecasting, and AML transaction monitoring using unsupervised anomaly detection. These capabilities require data architecture and model infrastructure designed for them from the start.
Fraud detection in fintech requires a layered approach combining deterministic rules with ML models. Deterministic rules handle the fraud signals that are clear and fast velocity limits, known bad actors, impossible geography. ML models handle the pattern-based signals that rules alone cannot detect behavioral anomalies, structuring patterns, network-level risk signals. We build both layers and operate them together, with model monitoring, drift detection, and retraining pipelines that keep detection accuracy current as fraud patterns evolve. False positive rate management is as important as detection rate; every legitimate transaction blocked is a customer service problem.
Yes. We have built loan origination systems, credit decisioning integrations, borrower portals, and payment infrastructure for consumer lending products including a fintech platform for interest-free school fee installment payments that required a financial model, a compliance framework, and a payment architecture that worked simultaneously for borrowers and educational institutions. We understand the underwriting workflow, the regulatory requirements around adverse action notices, and the collections compliance constraints that govern lending operations.
Three models: Dedicated Fintech Development Team for long-term financial platform builds and scaling products; Time and Material for iterative development where the product model and compliance requirements are still being refined; and Fixed Cost for well-scoped fintech software projects where the regulatory landscape, payment architecture, and feature scope are clearly understood before the engagement starts. We recommend the right model based on where you are in the product and compliance discovery process.
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