AI Development for
FinTech
Fraud detection, credit scoring, KYC automation, and AI for financial services. Compliant architecture, explainable outputs, production-ready. India based engineering team.
Financial products run on data and trust. AI can make both work harder. But AI for FinTech is not just a machine learning problem. It is a regulatory problem, an explainability problem, and a latency problem all at once.
We build AI for FinTech teams who understand the difference between a model that looks good in a notebook and one that holds up under regulatory scrutiny in production.
What We Build for FinTech Teams
Fraud Detection and Prevention
Real-time transaction scoring models that catch fraud patterns as they happen. Trained on your transaction history, tuned to your risk tolerance, fast enough for card-present transactions.
Credit Scoring and Underwriting AI
Alternate data credit models for NBFCs and digital lenders: device data, behavioural signals, and bureau augmentation. Explainable outputs ready for regulatory review.
KYC and AML Automation
Document verification, face match, and risk-based customer screening pipelines. Reduces manual review time without increasing false positive rates.
Algorithmic Trading Signals
Quantitative signal generation pipelines: factor models, sentiment analysis, and order flow analysis. Built to integrate with your existing execution infrastructure.
Customer Support and Onboarding Bots
AI chatbots that handle account queries, loan applications, and onboarding flows end to end. Trained on your product, not generic financial services content.
Regulatory Reporting Automation
Extract, classify, and structure transaction data for SEBI, RBI, or FCA reporting requirements. Cuts manual reporting time and reduces compliance errors significantly.
Document Intelligence: AI pipeline cuts insurance document review by 70 percent
A US insurance firm was processing thousands of documents every week by hand: claims forms, policy documents, medical reports, and legal correspondence. We built a fully automated document intelligence pipeline using Python, LangChain, FastAPI, AWS Textract, and GPT-4. The system went from brief to production in two months and cut manual document review time by 70 percent in its first month of operation.
Read the Document Intelligence Case StudyWhy explainability matters more in FinTech than in most industries
A recommendation engine that gets things wrong occasionally is annoying. A credit model that gets things wrong affects someone's ability to access capital. Regulators in most markets now require that automated credit decisions be explainable to the person who received them. That means black-box models are often not an option for core credit and risk use cases. We design FinTech AI with explainability as a first-class requirement: SHAP values, feature attribution reports, and audit trails that regulators can actually work with. This is not an add-on. It is part of how we build.
FinTech products we are most experienced building
- Fraud detection and real-time transaction risk scoring systems
- Alternative credit scoring for NBFCs and digital lenders
- KYC, AML, and document verification pipelines
- Insurance document processing and claims automation
- Customer-facing financial chatbots and onboarding flows
- Regulatory reporting and data classification tools
Building AI for financial services?
Compliance, explainability, and production reliability are things we build in from the start. Tell us what you are working on and we will give you an honest technical view.
Have a Project in Mind?
Let's Talk.
Tell us what you are building and we will come back within one business day with a plan, a timeline, and an honest cost estimate.
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Your Project
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A118, Sector 63
Noida, UP 201301
304 Krishna Classic, A.B Road
Indore, MP 452008