Our Services & Capabilities
We offer four core consulting pillars, each designed to deliver measurable business impact while maintaining the highest standards of technical rigour and governance.
PILLAR 1: Energy Forecasting & Trading Analytics
For energy traders, utilities, LNG desks, hedge funds, and energy SaaS companies.
We build analytics that inform trading decisions, optimise portfolios, and quantify market fundamentals. Our approach combines statistical rigour with deep understanding of energy market structures.
| Service | Description |
|---|---|
| Short-Term Load Forecasting | Day-ahead to week-ahead demand models incorporating weather, calendar effects, and real-time grid data. |
| Long-Term Demand & Price Modelling | Fundamentals-based models for monthly, seasonal, and annual horizons. Supply/demand balances, storage dynamics, and macro-economic drivers. |
| Gas & Power Price Forecasting | Statistical and ML models for spot and forward prices. Weather-driven demand signals, fuel switching dynamics, and cross-market interactions. |
| LNG Supply-Demand Balance Frameworks | Modular balance models tracking liquefaction, shipping, regasification, and storage. Scenario analysis for supply shocks or demand spikes. |
| Weather-Driven Demand Modelling | Integration of meteorological data (temperature, wind, solar irradiance) into demand and price forecasts. |
| Trading Signal Generation | Systematic identification of short-term price opportunities. Mean reversion signals, spread trading opportunities, and event-driven patterns. |
| Fundamentals Dashboards | Interactive visualisations of supply, demand, storage, flows, and prices. Built in Power BI/Tableau for real-time trading desk decisions. |
Relevant Experience:
- Supply-demand forecasting incorporating seasonality, weather, and macro drivers
- Familiarity with European gas, LNG, and power market structures
- Understanding of physical and financial energy instruments (spot, forwards, futures)
- Fundamentals-based modelling frameworks (supply, demand, storage, flows)
- Experience with ENTSO-E, EEX, ICE datasets
PILLAR 2: Credit Risk Modelling & Governance
For banks, building societies, fintech lenders, credit bureaus, and risk consultancies.
We build and validate credit risk models that stand up to regulatory scrutiny—whether for origination, portfolio management, collections, or IFRS9 provisioning. Every model is FCA/PRA compliant with audit-ready documentation.
| Service | Description |
|---|---|
| Application Scorecards | Development of scorecards for unsecured loans, credit cards, and mortgages across Consumer, MSME, Microfinance, and Corporate lending. 8–12% approval rate uplift at constant risk delivered previously. |
| Behavioural Scorecards | Early delinquency detection, limit management, and portfolio monitoring. 25% improvement in early delinquency detection delivered previously. |
| IFRS9 Modelling | Expected Credit Loss (ECL) Models (IFRS9 compliant) incorporating PD, LGD, EAD models with through-the-cycle and point-in-time calibration. Economic scenario integration and stress testing across Consumer, MSME, Microfinance, and Corporate lending. |
| Collections & Recovery Models | Collections scorecards, recovery optimisation, debt sale valuation. 15–20% improvement in recovery rates delivered previously. |
| Fraud & AML Analytics | Fraud detection models, synthetic identity detection, transaction monitoring optimisation. 1.5–2.5% false-positive rates delivered previously. |
| Model Validation & Governance | Independent validation, challenger models, gap analysis against SR 11-7 / SS1-23. Full technical documentation. |
| A/B Testing for Credit Strategies | Design of controlled experiments for pricing, limits, and cross-sell. Causal inference and treatment effect measurement. |
| Portfolio Insights & Risk Reporting | Automated performance monitoring packs, early-warning indicators, vintage analysis. |
Regulatory Alignment:
- FCA: CONC (consumer credit), MCOB (mortgages)
- PRA: SS1-23 (model risk management)
- IFRS9: PD, LGD, EAD development and governance
- SR 11-7: Model development and validation standards
PILLAR 3: GenAI Automation & AI Agents for Regulated Industries
For banks, insurers, energy companies, and operations teams who need AI they can trust.
We design and deploy Generative AI solutions that respect the constraints of regulated environments—secure, explainable, and governance-ready. Every solution includes Model Risk Committee-ready documentation. No black boxes. No compliance headaches.
| Service | Description |
|---|---|
| Intelligent Workflow Automation | Deploying sovereign AI agents for end-to-end task orchestration, document intelligence, and automated compliance reporting. |
| Retrieval-Augmented Generation (RAG) Pipelines | Secure, context-aware question-answering over internal documents. Built on open-source or enterprise LLMs with complete audit trails. |
| Document Intelligence | Automated extraction, classification, and summarisation from contracts, reports, applications, and regulatory filings. 40% reduction in processing time. |
| LLM-Powered Classification | Scalable categorisation of customer inquiries, transaction descriptions, operational tickets, and more. |
| Automated Reporting | GenAI-driven generation of narrative commentary for portfolio reports, risk summaries, and committee packs. |
| Governance-Ready AI Workflows | Designed from day one with model risk management in mind. Explainability, version control, and documentation built in. |
Relevant Experience:
- Led GenAI automation initiatives reducing documentation and processing costs by 40%
- Designed RAG pipelines and automated document intelligence workflows
- Built LLM-powered classification and summarisation systems
- Governance-ready frameworks: Model Risk Committee documentation, audit trails, explainability standards, model lifecycle discipline
PILLAR 4: Forecasting & Operational Optimisation
For retail, logistics, supply chain, and e-commerce leaders.
We build forecasting and optimisation models that reduce costs, improve service levels, and drive operational efficiency.
| Service | Description |
|---|---|
| Demand Forecasting | SKU-level and aggregate demand models incorporating seasonality, promotions, and external drivers. 20–30% accuracy improvement. |
| Inventory Optimisation | Safety stock modelling, replenishment algorithms, and stockout reduction strategies. 25% stockout reduction delivered previously. |
| Route Optimisation | ML-enhanced routing models balancing cost, time, and service constraints. 12% delivery cost reduction delivered previously. |
| Multivariate Operational Analysis | Understanding the drivers of operational performance—labour, weather, demand, and process variables. |
| Promotional Impact Modelling | Causal measurement of promotion effectiveness. Experiment design and incrementality testing. |
| Revenue Analytics & Demand Planning | Campaign prioritization, lead scoring, cross-sell propensity models, and customer lifetime value (CLV) maximization. |
| Predictive Maintenance | AI and machine learning models optimizing asset runtime, reducing machinery downtime, and predicting structural or component failures. |
Relevant Experience:
- Built demand forecasting models reducing product shortages by 28%
- ML-driven replenishment reducing forecast error from 20% → 10%
- Route optimisation models reducing delivery costs by 12%
- Fraud detection preventing £850K annual losses with 1.8% false-positive rate
- NLP-driven inquiry classification improving operations efficiency
Our Engagement Model
Kassriel Quant operates through a limited company structure, with contracts designed to be clearly outside IR35.
| Service | Description |
|---|---|
| Contract Structure | Fixed-price or milestone-based deliverables. Clear scope, agreed outputs, measurable outcomes. |
| Delivery Model | We work as a specialist consultancy delivering defined outputs—models, documentation, dashboards, presentations. Our team brings deep expertise, governance frameworks, and proven methodologies. |
| Governance Deliverables | Every engagement includes appropriate documentation: Model Development Document, Technical Specification, Performance Dashboard, Committee Presentation Pack. |
| Tools & Environment | We work in your environment (Python, SQL, AWS, etc.) using your data. We bring code, expertise, governance templates, and proven methodologies. |
| Reporting | Direct to project sponsor—CDO, CRO, Head of Risk, Head of Analytics, Head of Trading, Head of Operations. |
Why Kassriel Quant?
Cross-industry expertise
Energy, banking, fintech, retail, logistics, e-commerce, healthcare
Regulatory familiarity
FCA (CONC/MCOB), PRA, IFRS9, SR 11-7, SS1-23
End-to-end delivery
From data exploration to committee presentation
Governance mindset
Models built to be audited, not just deployed
Commercial awareness
Analytics that drive revenue, reduce risk, and cut costs
Clear communication
Complex insights explained to non-technical stakeholders
Production-grade code
Scalable, maintainable, documented Python/SQL
Immediate start
Available for contract engagements
Let's Talk
If you need energy analytics, credit risk models, GenAI automation, or operational forecasting—let’s schedule a conversation.