Expert Consulting in Modeling, Transactions, Financial Forensics, and AI Systems
Since 1998, we’ve provided expert consulting in predictive modeling, data analytics, financial forensics, transaction support, litigation services, and—most recently—artificial intelligence and Retrieval-Augmented Generation (RAG) systems.
Our Core Consulting Services
- Predictive Modeling & Analytics: Economic forecasting, risk scoring, and performance analysis built on proven statistical techniques.
- Loan, MBS & Structured Finance Analytics: Deep experience in mortgage performance, loss modeling, and regulatory reporting.
- Transaction Support Services: Due diligence, asset purchases and sales, and transactional document review.
- AI & RAG Systems Consulting: Strategic guidance on AI architecture, internal data readiness, and the role of Retrieval-Augmented Generation in business operations.
- Forensic Accounting & Investigations: Financial modeling, bankruptcy analysis, and fraud detection in support of litigation and regulatory review.
- Litigation Support & Dispute Advisory: Expert opinions, damages models, and technical analysis for attorneys and stakeholders.
Why Choose BGLP
🎓 Trusted Expertise
We bring decades of consulting experience across financial assets, data science, legal matters, and technical domains like valuation, analytics, and AI.
📊 Evidence-Driven Results
Our work is grounded in transparent methods, rigorous analysis, and real-world applicability—trusted in boardrooms and courtrooms alike.
🤝 Objective & Independent
As an independent advisor, BGLP delivers unbiased insights clients can rely on for high-stakes decisions and dispute resolution.
AI and RAG Advisory
Retrieval-Augmented Generation (RAG) systems are transforming how businesses interact with internal knowledge. BGLP helps clients evaluate whether these systems are appropriate, understand their components, and develop strategies for safe and effective deployment—particularly in regulated or data-sensitive industries.
We advise clients in finance, legal, and manufacturing sectors on how RAG systems can support functions such as internal search, audit trail generation, compliance documentation, and intelligent reporting.
Let’s Explore the Right Strategy Together
Whether you’re modeling or valuing financial assets, analyzing data, supporting litigation, or exploring AI use cases, BGLP brings clarity, depth, and trusted advice.
Summary Descriptions
Internal RAG System: How Companies Enhance AI Product Features
Internal RAG System: How Companies Enhance AI Product Features In the race to build smarter and more responsive digital products, companies are increasingly embracing internal Retrieval-Augmented Generation (RAG) systems. This innovative AI architecture combines large language models (LLMs) with a company’s own internal data sources to deliver faster, more accurate, and personalized user experiences.Unlike standalone […]
Mortgage Industry – Are We Over the Rapids ?
Recent Trends in Mortgage Industry Over the 17 months ranging from March, 2022 to July, 2023, the Federal Reserve (Fed) raised the Fed Funds rates to their highest levels in more than fifteen years. In recent weeks, the markets have been betting that the Fed will hold interest rates unchanged for the near future, and […]
Performance of 30 Yr. Fixed Rate Mortgages in UMBS 2021 – 23
Recent Performance of 30 Yr. Fixed Rate Mortgages Prepayment speeds on mortgages in UMBS securities from all reviewed origination years have varied greatly by vintage over the last 30 months. 2021 and 2022 vintage CPRs have been below 10% the entire time. Older vintages CPRs have been below 10% for six to twelve consecutive months, […]
Metrics on Mortgages in Ginnie Mae Insured Transactions 2021-23
With material rapid increases in loan rates, the aggregate monthly volume of new Ginnie Mae (GNMA) insured mortgages decreased by roughly 80% during the study period. Origination volumes of Fannie Mae and Freddie Mac loans in Uniform Mortgage Backed Securities (UMBS) have also been declining at a steep pace. The rate of decline of GNMA […]
