SOLUTION 08
DATA SCIENCE AS A SERVICE
Trapped Between Two Undesirable Choices
Build an In-House Data Science Team
Hire and wait months for scarce data science talent, then wait again for models to reach production.
Rely on Off-the-Shelf GenAI
Adopt generic, topical AI tools that aren’t built for auditable, regulated financial outcomes.
85% of AI projects never reach production, and 80% of project time is spent on data prep alone — leaving business units waiting up to six months for a first model.
Neither path gets financial services firms to reliable, governed predictions fast enough.
In-House Builds Are Slow. Generic AI Is Unreliable.
In-House Data Science Build
- Six-month typical wait for a first model
- 80% of project time spent on data preparation alone
- Six months or more just to hire a data science specialist
- Dependent on a single scarce hire, with no redundancy
Off-the-Shelf GenAI Tools
- Not built for auditable, regulated financial outcomes
- Lacks model versioning, audit trail, and feature visibility
- Topical, but less reliable than proven predictive use cases
- No structural guarantee your data stays within your perimeter
A Predictive ML, Deployed-in-Place Strategy
Xpanse deploys inside your cloud or data centre — connecting directly to your data as a Data Science as a Service platform that turns raw data into governed, production-ready predictive models in days, not months.
Speed to Commercial Value, Not Months of R&D
Business units see outputs the next morning, not after a six-month build. Xpanse automates the data science work that normally consumes 80% of project time.
Models iterate in minutes — toggle variables, adjust for cost and duration, and re-run — so this is a continuously improving capability, not a one-shot project.
Significantly Reduces Delivery Risk
- Deployed inside your cloud or data centre — your data never leaves your perimeter
- Audit trail, model versioning, and feature visibility built in from day one
- Aligned to Consumer Duty, DORA, SMCR, and SS1/23
- Scales across multiple models simultaneously, with no dependency on a scarce data science hire
- Priced as OpEx, not CapEx — easier to approve than a permanent hire
Predictive ML, End to End
From raw data to governed, production-ready predictions inside your own environment.
Your Data
Stays inside your perimeter
Xpanse Predictive ML
Automated, governed data science
Production Models
Auditable, traceable outcomes
Purpose-Built Components, Working as One
Automated Feature Engineering
Automatically designs and tests thousands of features from raw data, removing the manual data-prep bottleneck.
Model Iteration Engine
Toggle variables, adjust for cost and duration, and re-run in minutes — models that keep improving, not a one-shot deliverable.
In-Perimeter Deployment
Runs inside your own cloud or data centre, so sensitive financial data never leaves your environment.
Governance & Audit Trail
Built-in model versioning, audit trail, and feature visibility, aligned to Consumer Duty, DORA, SMCR, and SS1/23.
“Xpanse essentially unclogged Data Science for us. We can see the first iteration of models the next day.”
Martin Graham, Director of Insights & Analytics, Virgin Media Ireland
What the Solution Delivers
Predictive ML in Days
First model within days, not the typical six-month wait.
Proven Financial Use Cases
Investment signal identification, cross-sell/up-sell propensity, fraud and AML pattern detection, credit risk and default prediction, client churn and retention risk.
Auditable, Traceable Outcomes
Every model is versioned and inspectable, built for regulated environments.
Measurable ROI
+250% ROI on cross-sell, 2000% ROI on fraud detection, and €650k a month in retained revenue.
Outcomes That Matter to the Business
Cut Time to First Model from Months to Days
Reduce Data Prep Effort by 80%
Prove ROI: +250% Cross-Sell, 2000% Fraud Detection
Keep Data Inside Your Perimeter, By Design
Scale Predictive ML Without a Permanent Hire
Start with one question: what business outcome do you want to predict?
Talk to a consultant about connecting Xpanse to your environment for a first model within days.
Talk to a consultant
