Services
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.
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.
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%.
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.
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%.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
How We Work
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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We understand the task, the users, and where AI can actually help.
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We define what needs search, automation, or product integration.
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We implement the part that proves the value first.
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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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