Applied intelligence for financial decisions

Purpose-built models for decisions that matter.

GTP develops bespoke scoring, forecasting, prioritization, and optimization models for financial organizations—supported by the data foundations and systems work required to put them into practice.

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A different kind of AI

Think large mathematical model—not large language model.

Our work is not centered on chatbots or generative text. We build purpose-specific quantitative models for structured financial and operational decisions, including situations where the available dataset is comparatively slim.

InputSlim, relevant data
MethodPurpose-built mathematics
OutputExplainable decisions

Core capabilities

From model design to operational use.

View all capabilities
01

Bespoke scoring and decision models

Purpose-built models for credit, collections, recovery prioritization, counterparty assessment, and operational decisions.

02

Applied data science

Forecasting, anomaly detection, optimization, and quantitative analysis designed around a defined financial decision.

03

Data readiness and foundations

Data models, definitions, lineage, governance, and remediation that make financial data usable for analysis and modeling.

04

AI and model readiness

Use-case definition, data fitness, explainability, governance, validation, and a practical route into operations.

05

Finance technology implementation

Architecture, business analysis, selection, integration, workflow design, testing, and implementation support.

06

Training and capability building

Finance-relevant data, modeling, analytics, and AI education connected to the team’s actual work.

Dense quantitative model output plotted as a blue signal
Quantitative signal, translated into an operational decision.

Implementation matters

A model only creates value when it reaches the decision.

GTP bridges business requirements, data, model design, validation, and system integration. Explainability and defensibility are part of the solution—not documentation added at the end.

  1. Define
  2. Prepare
  3. Model
  4. Validate
  5. Integrate

Client perspective

“We consider them to be trusted advisors to our organization and would not hesitate to recommend them.”
James BryantDirector, Digital Transformation · Stanford Health Care

Ways to begin

Focused engagements

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Bespoke Credit & Collections Scoring

4–10 weeks

Build purpose-specific mathematical models for credit decisions, collections and recovery prioritization, with explainability and operational use designed in.

Practice Area: Bespoke Scoring

Data Readiness Audit for Finance Systems

2–6 weeks

Measure data quality, lineage, and usability for analytics/AI—then define the fastest path to “ready enough” without boiling the ocean.

Practice Area: Data Readiness

AI Readiness Assessment

2–4 weeks

Assess quantitative AI and decision-model opportunities across data fitness, explainability, governance, validation, and operational integration.

Practice Area: AI Readiness

Operational Analytics & Optimization

3–8 weeks

Use focused financial and operational data for forecasting, optimization, anomaly detection, and repeatable decision support.

Practice Area: Applied Data Science

Domain foundation

Built from real financial systems experience.

GTP’s background in treasury consulting, treasury technology, finance systems, forecasting, payments, risk, data integration, testing, and implementation shapes how we approach financial models today. It gives us context for the data, controls, workflows, and operational constraints behind the decision.

Selected case studiesHow GTP evolvedTreasury consulting

Ready to evaluate a use case?

We map the problem, the data, and the implementation path.

Contact GTP