Fraud detection model development
Models that score card transactions, transfers, account takeovers and application fraud in real time, with reasons your analysts can act on.
Custom AI · Finance
Fintech AI Development for Banks, Lenders & Insurers
Fraud models, credit scoring support, underwriting AI and fintech MVPs, built with the explainability, monitoring and documentation your model risk team will ask for.
Overview
Fintech AI development, from model to audited product
Off-the-shelf tools stop where your advantage starts. A lender wants a scorecard that works for thin-file customers in its own market. A card issuer wants fraud models trained on its own transaction patterns. An insurtech founder needs a working product before the next funding round. These are fintech AI development problems: models built on your data, wrapped in software your teams can use, and documented well enough to get through model risk review.
Finance adds constraints that consumer AI ignores. A credit model has to give reasons, because applicants and regulators will ask why someone was declined, and in the US fair-lending rules require lenders to state specific reasons for an adverse decision. A fraud model has to respond in milliseconds and be watched for drift as fraud patterns shift. Every model needs validation evidence, monitoring and a clear owner. We build with explainable features and reason codes, keep data and model versions traceable, test for bias, and design the workflow so a credit officer, underwriter or fraud analyst makes the final call.
Our published work in other demanding fields shows how we build. Vikk AI is a multi-agent legal assistant built on LLMs and RAG, covering all 50 US states and 50+ legal categories, with document analysis and handoff to lawyers. Its MVP took six weeks and it has 120,000+ users. Medsuccour is a deep-learning model that reads head CT scans in seconds, where a specialist needs 15 to 20 minutes. What transfers to finance is the discipline: grounded answers, careful evaluation and a person who signs off.
You own the code, the models and the trained weights, and we can deploy inside your own cloud account or region.
Use cases
Custom AI Development use cases in Finance
Credit scoring AI
Scorecards and machine-learning models with reason codes that support, not replace, credit officers, including for thin-file and SME borrowers.
Underwriting assistants for insurers
Summarize submissions, extract risk factors and suggest follow-up questions, while the underwriter prices and accepts the risk.
Custom AI for banks' internal knowledge
A staff assistant that answers from your policies, procedures, product manuals and regulator circulars, with a link to every source.
Insurtech MVP and fintech MVP development
Take a lending, payments, wealth or insurance product idea to a working MVP with the model, app and backend included.
AML investigation copilot
Pulls the customer profile, transaction history and related alerts into one view and drafts case notes for the analyst to edit and file.
How it works
How it works
- 01Define the decision and its limitsWe agree which decision the model supports, who owns it, what it may never do and how success is measured.
- 02Assess the dataWe check what history exists, its quality and gaps, consent and legal basis, and whether alternative data is appropriate.
- 03Build and validateModels are trained and tested on held-out and out-of-time data, checked for bias and documented with reason codes and limitations.
- 04Integrate with human reviewThe model plugs into your origination, fraud or underwriting workflow, with a person approving decisions and overrides recorded.
- 05Monitor and reportLive dashboards track performance, drift and override rates, with alerts when the model needs review or retraining.
Capabilities
Key features
Explainable models and reason codes
Every score comes with the factors that drove it, in language a credit officer or customer can understand.
Bias and fairness testing
We test outcomes across customer groups and document the results, so fair-lending and fair-treatment questions have answers.
LLMs, RAG and multi-agent systems
Language AI grounded in your documents for knowledge assistants, document analysis and investigation support.
Model risk documentation
Model cards, data lineage, validation results and change logs ready for your model risk management and audit reviews.
Drift and performance monitoring
Ongoing checks catch shifts in fraud patterns, customer mix or data quality before they hurt results.
100% IP ownership
You own the code, the models and the trained weights, with no licence tied to our platform.
Integrations
Works with your Finance stack
- Python
- PyTorch
- XGBoost
- scikit-learn
- OpenAI
- Google Vertex AI
- AWS
- Azure
- Snowflake
- Plaid
- Stripe
- Mambu
Using something else? If it has an API, a database or a webhook, we can connect to it.
Outcomes
Benefits for Finance teams
Models that fit your customers
Trained on your own portfolio and market, rather than a generic vendor model built for someone else's.
Smoother model risk review
Documentation, explainability and monitoring are built in from the start, not bolted on when validators ask.
A product you can take to market
MVPs built to production standards, so pilots with real customers can start without a rebuild.
Lower long-term cost
Owning core models avoids per-decision or per-seat fees for the capabilities your business depends on.
Our work
Related Work
AI Chatbot2024
Vikk AI: AI-Powered Legal Assistant
Vikk AI is a 24/7 AI-powered legal assistant that gives users instant, private legal guidance, analyzes their documents, and connects them with verified lawyers when needed. We helped build a conversational platform that delivers state-specific answers across dozens of legal categories and languages.
View case study →
Custom AI Model Development2024
Medsuccour AI: Revolutionizing CT Scan Diagnosis
Medsuccour is an AI-powered project designed to revolutionize the diagnosis of traumatic brain injuries through rapid and accurate analysis of CT scans. Given that every minute counts after a head trauma, our model drastically reduces the time required to detect and localize brain injuries, generating detailed reports in seconds.
View case study →
FAQ
Custom AI Development for Finance: FAQs
Can you build a fraud detection model for our bank?
Yes. We build supervised and anomaly-detection models on your transaction and customer history, deliver risk scores with reasons, and connect them to your fraud case management so analysts review the flagged cases.
Is AI credit scoring allowed?
It depends on the market and how it's used. Most regulators expect credit models to be explainable, tested for unfair bias and overseen by people, and some require specific reasons for declines. We build to those expectations and keep the final decision with your credit team.
How do you make AI models explainable for regulators?
We prefer interpretable features and models where they perform well, add reason codes to every score, and document data sources, validation results and known limits. Your validators get the evidence they need to challenge the model.
Do you build insurtech and fintech MVPs?
Yes. We take product ideas to working MVPs with the AI, app and backend included. Our Vikk AI MVP, a multi-agent assistant in the legal field, took six weeks from start to launch.
How much data do we need for a credit or fraud model?
It depends on the decision and how often the outcome occurs. Fraud and default are rare events, so we look at history length, labelled outcomes and data quality first, and tell you honestly whether a model, a rules engine or both is the better start.
Who owns the model and the code?
You do. You keep 100% of the intellectual property, including trained model weights and documentation.
How long does fintech AI development take?
Focused AI features can ship in weeks, and the Vikk AI MVP took six. Models that need validation and integration into origination or fraud systems take longer. We set milestones after discovery.
Explore
More AI services for Finance, Banking & Insurance
AI Voice Agents
AI Voice Agent for Banking and Insurance Contact Centers
Voice agents for bank and insurer contact centers: card blocks, balance and policy queries, claims intake, payment reminders and collections calls, with human handoff.
Explore AI ChatbotsBanking Chatbot Development for Banks, Fintechs & Insurers
Banking, fintech and insurance chatbots for web, app and WhatsApp that answer product questions, pre-qualify leads, collect documents and escalate safely.
Explore AI AutomationAI Automation in Financial Services & Insurance Operations
KYC, loan processing, claims intake, underwriting extraction and renewal workflows, automated end to end with human approval on every decision.
Explore AI Data AnalyticsFinancial Data Analytics for Banking & Insurance
Dashboards, risk analytics and forecasting for banks, lenders and insurers, built on clean data from core, policy, CRM and contact-center systems.
ExploreFurther reading
Custom AI Development for other industries
Build the model your risk team will sign off.
Bring the decision you want to improve and the data you have. We'll tell you plainly what a model can do, how it will be explained and how long it takes.