Services
Financial Services Algorithmic AI and Risk Modeling
Financial Services Algorithmic AI and Risk Modeling
Development of deterministic high-speed trading, real-time fraud detection, algorithmic risk modeling, and hyper-personalized retail banking experiences for fintech firms and traditional banking institutions. Sub-services include real-time AI fraud detection systems, algorithmic trading ML pipeline development, credit risk predictive modeling, and agentic AI for financial compliance auditing.
Algorithmic Trading System Development
Design and engineering of low-latency, high-frequency trading (HFT) systems using reinforcement learning and market microstructure analysis to execute complex strategies with sub-millisecond precision, directly impacting alpha generation.
Real-time Fraud Detection AI Integration
Deployment of multimodal AI systems combining graph neural networks and anomaly detection to identify fraudulent transactions and money laundering patterns in real-time across payment networks, reducing false positives by over 40%.
Credit Risk Predictive Modeling Services
Development of ensemble machine learning models for counterparty and portfolio credit risk assessment, incorporating alternative data and economic scenarios to predict defaults and calculate CECL/IFRS 9 provisions with greater accuracy.
Agentic AI for Financial Compliance
Implementation of autonomous AI agent workflows that continuously monitor transactions, screen for sanctions/PEPs, and automate regulatory reporting (e.g., AML, KYC) to ensure audit-ready compliance and reduce manual review workload by 70%.
Portfolio Optimization Machine Learning
Application of advanced ML techniques, including Bayesian optimization and risk-parity models, to dynamically allocate assets, manage concentration risk, and maximize risk-adjusted returns (e.g., Sharpe ratio) for institutional portfolios.
Financial Sentiment Analysis with LLMs
Fine-tuning of domain-specific large language models on financial news, earnings calls, and regulatory filings to extract real-time sentiment, event impact, and thematic signals for trading and risk management decisions.
AI-Powered Liquidity Risk Modeling
Engineering of AI models to forecast cash flow gaps, simulate stress scenarios, and optimize liquidity coverage ratios (LCR/NSFR) under Basel III, enabling proactive treasury management and regulatory compliance.
Derivatives Pricing AI Solutions
Development of neural network-based models for pricing complex OTC derivatives and calculating XVA adjustments (CVA, DVA, FVA) faster than traditional Monte Carlo simulations, improving hedge effectiveness and capital efficiency.
AI for Anti-Money Laundering (AML)
Building end-to-end AI systems for transaction monitoring, customer risk scoring, and suspicious activity report (SAR) generation, leveraging network analysis and unsupervised learning to adapt to evolving typologies.
Financial Time Series Forecasting
Creation of specialized deep learning models (e.g., LSTMs, Transformers) for high-frequency forecasting of FX rates, commodity prices, and volatility surfaces, providing critical inputs for trading and hedging strategies.
Explainable AI (XAI) for Finance
Implementation of model-agnostic explainability frameworks (SHAP, LIME) and audit trails for credit scoring, trading, and risk models to meet regulatory demands for transparency and facilitate model risk management.
AI Model Risk Management
Establishment of governance frameworks, validation pipelines, and continuous monitoring systems for production AI/ML models in finance, ensuring performance, stability, and compliance with SR 11-7 and model risk policies.
Market Manipulation Pattern Recognition
Development of surveillance AI using pattern recognition and multi-agent simulation to detect spoofing, layering, and other market abuse tactics in equity and derivatives markets in real-time.
AI for Loan Underwriting Automation
Integration of computer vision for document processing and predictive models for income verification and default probability to fully automate commercial and consumer loan origination, cutting decision times from days to minutes.
Insurance Risk Modeling AI
Application of ML to actuarial modeling for pricing, reserving, and catastrophe risk simulation, incorporating geospatial data and climate models to improve loss ratio predictions and portfolio resilience.
Partnered with leading AI, data, and software stack.
How We Work
Custom AI workflows for your Business
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
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Review the use case
We understand the task, the users, and where AI can actually help.
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Pick the right approach
We define what needs search, automation, or product integration.
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Build the first useful version
We implement the part that proves the value first.
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Improve from there
We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
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