Dennis Kyalo — Structured Credit

Dennis Kyalo

Structured Credit

ABS Consumer Loans · Whole Loan Trading · Structured Products

I specialize in ABS Consumer Loans, focusing on the analysis, pricing, and trading of consumer loan portfolios. I leverage loan-level analytics, collateral surveillance, cash flow modeling, and credit performance analysis to evaluate investment opportunities and support structured credit trading decisions.

Beyond the trading desk, I am passionate about building AI-powered tools that make financial analysis faster, clearer, and more actionable.

View Featured Work Connect

Professional Highlights

By the Numbers

💰

$1M+

Annual Financing Cost Savings

Improved trading desk workflows through analytics, automation, and portfolio surveillance.

📊

Structured Credit

ABS Consumer Loans

Specialized in the buying, selling, and securitization of consumer loan portfolios.

🤖

AI for Finance

Built an RMBS Analytics Platform

AI-powered platform for mortgage analytics, natural language querying, SQL generation, and interactive dashboards.

📈

Quantitative Analytics

Time Series Forecasting Platform

Built a multi-model forecasting application for macroeconomic and interest rate analysis.

🏛️

FINRA Licensed

Series 7 · Series 63 · SIE

Licensed securities professional with a background in Financial Engineering and Data Science.

My Approach

Discipline Meets Curiosity

I believe success in structured credit comes from combining disciplined credit analysis, market awareness, and sound risk management. Every trading and investment decision begins with understanding the underlying collateral, market dynamics, and relative value. Beyond the trading desk, I enjoy exploring how technology, including AI, can streamline research, uncover deeper insights, and make complex financial analysis more efficient.

Professional Experience

Citigroup Global Markets

Structured Credit · ABS Consumer Loan

New York, NY · Feb 2023 – Present · ● Current

Evaluate, price, and trade consumer loan portfolios and structured credit opportunities using quantitative analysis, cash flow modeling, credit performance data, market comparables, and relative-value frameworks. Support securitization and investment analysis by developing assumptions around yield, prepayments, credit losses, and expected cash flows, while building analytics, monitoring tools, and automated workflows that strengthen portfolio surveillance, risk assessment, pricing, and trading decisions across the ABS market.

The United Nations

Data and Statistics Research Intern

New York, USA · Sep 2022 – Dec 2022

Conducted quantitative and qualitative research using R and Python to analyze large-scale international datasets and support evidence-based policy initiatives. Applied statistical analysis and data visualization to identify meaningful trends, strengthen global development reporting, and improve the accessibility of insights related to the United Nations Sustainable Development Goals. Collaborated with research and policy teams to translate complex findings into clear, data-driven narratives for international audiences. Contributed to major publications, including the Gender Snapshot and the 2022 Sustainable Development Goals Progress Report.

Central Bank of Kenya

Research and Statistics Intern

Nairobi, Kenya · Oct 2019 – Mar 2020

Applied econometric, time-series, and machine-learning techniques to financial data from more than 40 institutions to support inflation analysis, economic policy research, and financial market forecasting. Evaluated large and diverse financial datasets to identify trends, strengthen predictive models, and generate actionable economic insights. Used R to automate statistical reporting and develop interactive R Shiny applications that improved the analysis, visualization, and communication of financial and economic information for senior policymakers.

Featured Work

Structured Products · Mortgage Analytics · AI

RMBS Origination Analytics Platform

An intelligent research and analytics platform that enables structured finance professionals to conduct AI-assisted research, analyze residential mortgage origination data at the loan level, generate interactive visualizations, and answer complex questions through natural language.

Live Demo ↗

RMBS Origination Analytics Platform, AI research interface with featured prompts for mortgage collateral analysis

RMBS Origination Analytics Platform, natural language research and loan-level mortgage analytics.

The Challenge

Residential mortgage origination datasets contain millions of loan-level observations across vintages, sellers, geographies, borrower characteristics, and collateral attributes. Extracting meaningful insights typically requires writing SQL, manually aggregating data, building visualizations, and interpreting results, making research both time-consuming and highly technical.

The Solution

Built an intelligent research and analytics platform that allows structured finance professionals to ask complex questions in natural language. The platform retrieves relevant context, generates SQL automatically, performs loan-level analytics, creates interactive visualizations, and delivers structured research outputs instantly.

Data Coverage

Loan-level residential mortgage origination data spanning multiple origination years, covering seller, vintage, geography, FICO, LTV, CLTV, DTI, interest rate, occupancy, loan purpose, property type, and original balance.

Natural Language Research

Ask complex questions in plain English and instantly retrieve loan-level analysis, interactive visualizations, and structured research insights, without writing SQL.

Loan-Level Analytics

Analyze residential mortgage origination data across seller, vintage, geography, borrower characteristics, and collateral attributes through automatically generated analytical queries.

Vintage & Seller Analysis

Compare origination cohorts and seller performance across FICO, LTV, CLTV, DTI, interest rate, original balance, and other key credit characteristics.

Interactive Visualizations

Generate publication-quality charts and dashboards that help identify portfolio trends, compare collateral characteristics, and support structured finance research.

AI Research Summaries

Automatically generate structured analytical narratives that summarize key findings, explain trends, and present insights in a format familiar to structured finance professionals.

Time Series Forecasting · Macroeconomics

Economic & Interest Rate Forecasting Platform

An interactive time series forecasting platform for analyzing and predicting U.S. economic and interest rate trends using multiple statistical forecasting models.

Live Demo ↗

Economic Rates Forecasting Platform, interactive R Shiny dashboard showing U.S. Inflation Rate forecast with Auto ARIMA model and confidence intervals

Interactive dashboard for forecasting U.S. economic and interest rate series using multiple statistical forecasting models.

The Challenge

Economic and interest rate forecasting often requires evaluating multiple statistical models to determine which performs best for a given time series. Comparing model performance, visualizing forecasts, and interpreting results can be time-consuming without a unified analytical workflow.

The Solution

Built an interactive forecasting platform that compares multiple time series models, evaluates forecasting accuracy using standard performance metrics, and visualizes historical data alongside future projections to support economic analysis and decision-making.

Auto-ARIMA

Automatic ARIMA model selection. Optimal for stationary and near-stationary rate series with autocorrelation structure.

ETS

Error, Trend, Seasonality decomposition. Handles trend and seasonal patterns in rate data with state-space smoothing.

Prophet

Decomposable time series forecasting model designed for business and economic data with changing trends, seasonality, and missing observations.

TBATS

Handles complex seasonality. Particularly effective for series with multiple seasonal patterns and irregular cycles.

Forecast Accuracy Metrics

RMSE

Root Mean Squared Error

MAE

Mean Absolute Error

MAPE

Mean Absolute Percentage Error

MSE

Mean Squared Error

Rate Series Covered

·10-Year Treasury Yield

·30-Year Mortgage Rate

·Federal Funds Rate

·CPI Inflation

·3-Month Treasury Bill Rate

Multi-Model Comparison

Compare forecasts from Auto-ARIMA, ETS, Prophet, and TBATS side-by-side to identify the best-performing model for each economic time series.

Interactive Forecast Charts

Visualize historical observations, future projections, and confidence intervals through interactive charts with zoom and export capabilities.

Forecast Accuracy Metrics

Compare RMSE, MAE, MAPE, and MSE across forecasting models to evaluate predictive performance and support model selection.

Flexible Forecast Horizons

Generate forecasts across different time horizons to support macroeconomic analysis and planning across different market environments.

Professional Reporting

Generate publication-ready charts and analytical outputs suitable for research presentations, portfolio reviews, and quantitative reports.

Core Expertise

Technical Toolkit

Structured Credit

ABS Consumer Loans Whole Loan Trading Loan Tape Analysis Collateral Analysis Cash Flow Modeling Relative Value Analysis Credit Performance Analysis Portfolio Surveillance

Market Platforms

Bloomberg Terminal BQuant Intex Microsoft Excel Microsoft PowerPoint

Programming & Quantitative Analytics

R R Shiny tidyverse ggplot2 highcharter Python Pandas NumPy scikit-learn SQL PostgreSQL LangChain OpenAI API

Education & Certifications

Academic Background

Education

State University of New York at Buffalo

M.S. Engineering Science (Data Science)

Jomo Kenyatta University of Agriculture and Technology

B.S. Financial Engineering

Professional Development

Business Science University

Advanced coursework in R, Python, Machine Learning, AI, and Time Series Forecasting

HarvardX / edX

Professional Certificate in Data Science

Let’s Connect

Get in Touch

I’m always happy to connect with professionals interested in structured credit, securitized products, quantitative analytics, and AI applications in financial markets. Whether you’d like to discuss the markets, exchange ideas, or learn more about my work, I’d be glad to connect.

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