StratLytics Research Hub
Research, technical perspectives, and applied insights on decision intelligence, grid analytics, supply chain optimisation, and governed AI systems.
How modern financial institutions move from fragmented analytics workflows to governed AI decision systems integrating acquisition, underwriting, portfolio management, and model lifecycle governance.
Read ResearchThe past five years exposed the fragility of global supply chains. Most companies responded by building buffer inventory — an expensive and limited strategy. ...
Read articleMost manufacturers still manage inventory with static safety stock formulas and min-max policies that were designed for simpler supply chains. Machine learning ...
Read articleManufacturing supply chains face demand forecasting challenges that overwhelm traditional statistical methods — SKU proliferation, intermittent demand, short ...
Read articleDemand response programmes are critical grid flexibility resources, but most utilities manage them with crude analytics — broad customer segments, conservativ...
Read articleTraditional load forecasting methods are struggling with the complexity introduced by renewables, distributed energy resources, and demand flexibility. This art...
Read articleUtilities have invested billions in Advanced Metering Infrastructure, generating unprecedented volumes of consumption data. Yet most struggle to extract operati...
Read articleMost banks still monitor credit portfolios through monthly cohort reports and static dashboards. As portfolio dynamics accelerate and economic conditions shift ...
Read articleBuilding a modern credit underwriting system requires more than deploying a machine learning model. It demands an architecture that integrates bureau data, alte...
Read articleRegulatory guidance on model risk management is clear in principle but complex in execution. This article breaks down what SR 11-7 and OCC 2011-12 demand in pra...
Read articleFinancial institutions have spent decades layering scorecards, rule engines, and point solutions across credit acquisition, underwriting, and portfolio manageme...
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Longer technical perspectives on platform architecture, model governance, and decision system design.
How to build continuous monitoring pipelines that detect model drift, population shifts, and performance degradation before they affect business decisions.
Read deep diveA structural comparison of decision engines and predictive models — when each applies, how they interact, and what governance each requires in regulated institutions.
Read deep diveHow explainability requirements in consumer lending shape model architecture decisions — from SHAP values and LIME to adverse action compliance frameworks.
Read deep diveTalk to our team about SLERA, SLIQ, or SLICE.
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