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The gap between financial models and their IT implementation is where projects fail. UCG closes that gap. We deploy PhD-level experts who understand your regulatory burden, model your quantitative risks, and architect your digital resilience. Don't just document and maintain your risk architecture, engineer it for the future.
Consult with a Quantitative Expert
The Scientist-Consultant Approach
The challenges you face, from the granular data demands of FRTB to the stochastic complexity of xVA pricing, cannot be solved by generalists with a spreadsheet. They require scientific rigor.
At United Consulting Group, we have redefined the role of the business analyst. Our team is composed not just of consultants, but of scientists: physicists, mathematicians, and engineers who have turned their analytical lens toward the financial markets.
When your quant team talks about "Monte Carlo convergence" or your risk team discusses "expected xhortfall tail risks," we don't just take notes. We understand the math. We challenge the assumptions. We optimize the logic.
Ambiguity is the enemy of delivery. That is why we employ a "rapid prototyping" methodology. Using Python, R, and advanced modelling tools, we build working proofs-of-concept during the analysis phase. We validate the business logic mathematically and technically before a single line of production code is written.
The modern bank is a web of dependencies. Front office pricing affects risk capital; IT resilience affects regulatory compliance. Our BAs operate across these silos, tracing the impact of a single data point from the trade ticket to the regulatory report.
Converting Compliance into Architecture
The "regulatory super-cycle" is a torrent of financial regulations that are not a one-off event, but a permanent effort to comply with ever increasing demands. We offer a forensic approach to compliance to stay ahead of the curve. UCG transforms regulatory texts into precise technical requirements to keep our clients adaptable in the long run.
The Mathematics of Value
Your competitive edge lies in your ability to price, hedge, and manage risk more accurately than the market. UCG provides the analytical firepower to upgrade your quantitative infrastructure.
We assist in the transition to multi-curve environments and the integration of risk-free rates. Our analysts specify the curve construction logic and volatility surface calibration methods for your pricing libraries.
We help you navigate the complexity of valuation adjustments (CVA, DVA, FVA, KVA). We analyze the cross-desk funding implications and define the requirements for real-time xVA grids that protect your profitability.
We build reliable natural language processing, machine learning, and classification algorithms tailored to your needs. We integrate guardrails, monitoring, and automated backtesting approaches so that you can rest assured your models perform in the long run.
Speed requires governance. We analyze your high-frequency trading (HFT) infrastructure against MiFID II / RTS 6 standards, defining the specifications for "kill switches", pre-trade risk checks, and latency monitoring systems.
Regulatory compliance is strictly quantitative. We steer the implementation of the fundamental review of the trading book (FRTB), bridging the gap between front office and risk. Our experts define the specifications for P&L attribution tests (PLAT) and the transition logic from value-at-risk (VaR) to expected shortfall (ES) to secure your internal model approval.
Confidence requires verification. We design robust model risk management (MRM) frameworks that satisfy SR 11-7 and TRIM guidelines. We analyze your model lifecycle, defining rigorous testing protocols for benchmarking, backtesting, and sensitivity analysis to ensure your models perform under stress.
Signal detection requires cleaner data. We architect the analytical layer for your machine learning initiatives. From natural language processing (NLP) for sentiment analysis to feature engineering for alpha generation, we define the requirements that turn unstructured alternative data into executable trading signals.
Protecting the banking book. We refine the mathematical modeling of non-maturing deposits and prepayment risks in a rising rate environment. Our team analyzes interest rate and credit spread risk in the banking book (IRRBB, CSRBB), specifying the metrics for net interest income (NII) sensitivity and economic value of equity (EVE) optimization.
Capital efficiency demands precision. We guide the optimization of exposure calculations under SA-CCR and the internal model method (IMM). Our analysts specify the simulation logic for potential future exposure (PFE) and effective expected positive exposure (EEPE), ensuring that your netting sets and collateral agreements are mathematically optimized to minimize capital consumption.
Beyond simple capital calculation. We model the tail risk of low-frequency, high-severity events using loss distribution approaches (LDA). We define the specifications for integrating Monte Carlo simulations with scenario analysis, translating operational vulnerabilities and key risk indicators (KRI) into quantifiable economic capital requirements.
Survival depends on cash flow visibility. We architect advanced projection models for LCR and NSFR optimization. We analyze behavioral assumptions—such as deposit run-offs and credit line drawdowns—under stress, defining the requirements for dynamic balance sheet simulation and real-time intraday liquidity monitoring.
Accurate risk differentiation drives lending profitability. We modernize your credit decisioning engines, moving from traditional logistic regression to machine-learning-enhanced scoring models. Our team validates your PD, LGD, and EAD parameters for IRB compliance and refines the Expected Credit Loss (ECL) methodologies required for precise IFRS 9 provisioning.
Sustainability is now a mathematical challenge. We integrate physical and transition risks into your existing stress-testing frameworks. We analyze the transmission channels of climate scenarios onto asset valuations, defining the methodologies to adjust Probability of Default (PD) curves and collateral haircuts based on environmental risk factors and carbon footprint data.
Generating alpha requires disciplined construction. We enhance your investment processes by implementing advanced smart beta and risk parity strategies. Our analysts specify the algorithms for dynamic portfolio rebalancing and attribution analysis, helping you isolate and capture systematic risk premia (factors) while minimizing transaction costs.
Valuing physical assets requires specialized stochastic processes. We upgrade your pricing models for complex energy derivatives and storage facilities. We focus on mean-reverting jump-diffusion models to capture power and gas market dynamics, defining the logic for dispatch optimization and hedging capabilities in volatile commodity markets.
Data quality is the foundation of risk management. We implement the principles of BCBS 239 to ensure the accuracy, integrity, and timeliness of your risk data. Our experts design the data architecture and governance frameworks required to aggregate risk exposures across the enterprise, enabling you to make informed decisions in times of stress.
Strategic decisions require foresight. We develop advanced simulation engines to model the impact of hedging strategies and investment decisions under various market scenarios. By quantifying potential outcomes and risks, we empower you to optimize your portfolio, manage downside risk, and make data-driven choices for capital allocation and disinvestment.
Aligning incentives with long-term value. We design and map sophisticated share-based remuneration models, including stock options, performance shares, and phantom stock plans. Our experts ensure these models are compliant with regulatory standards (e.g., IFRS 2) and aligned with your corporate governance goals, providing a clear framework for valuing and accounting for employee equity compensation.
Building the Future of Finance
"Digitalization" is a buzzword. "Data Architecture" is a discipline. We focus on the latter to deliver the former
We treat data as a supply chain. Our analysts map the lineage of critical data elements (CDEs) from source to report, defining the "golden source" logic that ensures data integrity for AI and analytics.
Moving to the cloud changes your risk profile. We define the non-functional requirements (NFRs) for security, latency, and availability, ensuring your cloud architecture is robust enough for mission-critical financial workloads.
We act as the bridge between your business stakeholders and your DevOps teams. We translate complex business needs into atomic "user stories" and "acceptance criteria" (Gherkin syntax) that developers can execute immediately.
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Regulation is no longer just a legal constraint; it is a data engineering specification.
Consult with a Quantitative Expert