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: Credit Risk Modelling & Governance
Defensive Analytics – 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)corporating seasonality, weather, and macro drivers
- PRA: SS1-23 (model risk management)
- IFRS9: PD, LGD, EAD development and governance
- SR 11-7: Model development and validation standards
PILLAR 2: Revenue & Growth Analytics
Growth Analytics – For banks, fintechs, insurers, retailers, e-commerce businesses, and subscription-led organisations.
We build analytics that identify and prioritise revenue opportunities, improve customer retention, optimise pricing, and measure commercial performance. Our approach combines statistical rigour, experimentation, and practical commercial insight.
| Service | Description |
|---|---|
| Customer Segmentation | Data-driven segmentation to identify high-value customer groups, behavioural patterns, and differentiated growth opportunities. |
| Cross-Sell & Upsell Propensity Models | Predictive models that identify which customers are most likely to take additional products or services. |
| Churn & Retention Modelling | Early-warning models to identify customers at risk of leaving, enabling targeted retention interventions. |
| Pricing & Revenue Optimisation | Analytics to optimise pricing, offers, discounts, and margins while balancing revenue growth, conversion, and customer value. |
| Customer Lifetime Value (CLV) Modelling | Forecasting customer value to guide acquisition spend, retention investment, and portfolio prioritisation. |
| Campaign & Marketing ROI Measurement | Measurement frameworks for campaign effectiveness, incrementality, attribution, and return on marketing investment. |
| Recommendation Engines | Personalised product, content, or offer recommendations to increase engagement, conversion, and basket value. |
| Lead Scoring & Conversion Analytics | Prioritisation models that help commercial teams focus on leads and opportunities with the highest likelihood of conversion. |
| Revenue Performance Dashboards | Interactive reporting for customer acquisition, retention, conversion, pricing, campaign performance, and revenue drivers. |
Relevant Experience:
- Propensity modelling for cross-sell, upsell, and customer engagement
- Churn prediction and retention strategy analytics
- Customer segmentation and lifetime-value modelling
- Pricing, promotion, and campaign-effectiveness analysis
- A/B testing, causal inference, and incrementality measurement
- Automated commercial-performance dashboards and decision-support tools
PILLAR 3: GenAI Automation & AI Agents for Regulated Industries
Acceleration & Automation – 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
Planning & 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
Pay for Impact, Not for Promise
We structure engagements around your business outcomes, not just hours or deliverables.
| Service | Description |
|---|---|
| Fixed-Price Projects | Clear scope, timeline, and deliverables. Ideal for well-defined analytical challenges like credit risk models, forecasting systems, or GenAI solutions. |
| Success Milestone-Lined Fees | Progressive payment as we hit measurable KPIs—approval rate uplift, fraud detection improvement, cost reduction, or revenue growth. Risk and reward aligned. |
| Time & Material + Outcome Tracking | Ideal for exploratory work, model development, or ongoing support. Transparent billing with outcome dashboards. |
| Retained Partnership | Ongoing analytics support, model monitoring, governance, drift detection, and optimization. Full team at your disposal. |
All engagements include: Governance documentation | Audit readiness | Regulatory compliance | Impact dashboards
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
Business Impact Measurement
We measure success by outcomes and ROI, not just models
Let's Talk
If you need credit risk models, revenue & energy analytics, GenAI automation, or operational forecasting.
Let’s schedule a conversation.