Data Intelligence · African Finance

Your data is
already telling you
what to do next.

Fundertech builds analytics infrastructure and decision intelligence for banks, insurers, and listed companies across Africa. We turn raw transactional data into measurable competitive advantage.

$ run customer_retention_model --segments=risk_tier
→ 172M rows processed · 115K customers segmented · pipeline healthy
$ deploy churn_intervention --model=T-Learner
→ 15% profit uplift identified · "sleeping dog" cohort flagged · executive report generated
$ run portfolio_concentration_check --top=20
→ Exposure heatmap ready · 3 concentration alerts · board deck updated
$
Live data architecture · medallion pipeline
SRC
Sources
FLEXCUBE
Life · Credit
AgroLAS · Digital
BRZ
Bronze
Raw ingest
Watermark
versioning
SLV
Silver
Validated
Clean
Versioned
GLD
Gold
Enriched
Aggregated
Scored
INT
Intelligence
AI Models
Scorecards
Decisions
Proven outcomes
172M
Rows processed · live production
Pipeline throughput · relative volume
End-to-end ETL pipeline built across five core banking systems — FlexCube, Life, Credit, AgroLAS, and Digital — with watermark-managed incremental loads and schema versioning.
15%
Profit uplift · causal inference
Control vs treatment · profit index
Control
72
Treatment
87 +15%
T-Learner uplift model over traditional credit scoring. Identified customers harmed by credit limit increases — the "sleeping dog" effect — before costly intervention.
115K
Customers segmented · RFM model
Segment distribution · risk tier
High value
At-risk
Sleeping dog
Dormant
Recency, frequency, and monetary segmentation across the retail book. Risk-tiered cohorts fed directly into the next-product-to-buy prediction engine.
0$
External budget · self-funded build
Value delivered · phase by phase
Pipeline
Scorecard
AI Engine
Three-phase analytics platform — data pipeline, executive scorecard, and AI prediction engine — delivered without a dedicated budget or formal mandate. Results first.
What we build
01
Data Infrastructure
Foundation layer

Most financial institutions are sitting on a decade of transactional data they cannot query. We build the pipelines, data marts, and medallion architectures that make that data usable — today, not in 18 months.

  • ETL & ELT pipeline design
  • Bronze / silver / gold architecture
  • Oracle FLEXCUBE integration
  • PostgreSQL replica reconciliation
  • Schema discovery & lineage tracing
02
Executive Intelligence
Decision layer

Boards and executives need clarity, not dashboards. We design scorecard systems and concentration risk tools that translate raw numbers into decisions, with the right metrics for each audience.

  • Board & MD-level scorecards
  • Top 20 depositor / exposure views
  • Portfolio concentration alerts
  • SLA breach prediction
  • Power BI & DAX implementation
03
Predictive Analytics
Intelligence layer

Churn prediction. Next-product-to-buy models. Causal inference on credit interventions. We build AI systems that improve with every transaction — and explain their outputs to the humans who act on them.

  • Churn risk modelling
  • T-Learner causal inference
  • RFM & behavioural segmentation
  • Monte Carlo simulation
  • Retention agent design
04
Analytics Strategy
Leadership layer

We help institutions define what a modern analytics function looks like — the mandate, the team structure, the vendor decisions, and the roadmap — without the consulting overhead that slows everything down.

  • Analytics function design
  • Data readiness assessment
  • Vendor & platform selection
  • 90-day activation roadmaps
  • Board briefings & pitch support
Who we serve
Commercial Banks
Retail, SME, and corporate banking data challenges. FLEXCUBE-native implementations. Regulatory reporting and credit book analytics.
Insurance & Life
Policy lapse prediction, claims concentration analysis, and customer lifetime value modelling across multi-product portfolios.
ZSE-Listed Companies
Investor-grade analytics, operational dashboards, and data-backed narrative for listed companies navigating scrutiny and growth simultaneously.
MFIs & Agri-Lenders
Smallholder portfolio risk, scheme-level loan book analysis, and disbursement-to-collection tracing at scale.
How we work

Build first.
Invoice second.

Every engagement starts with a working prototype — not a proposal. We connect to your data environment, identify the highest-value signal, and demonstrate output before we discuss scope or cost. That's how trust is built between data practitioners and financial institutions.

01
Diagnose

We audit your source systems, query your schema, and map the gap between the data you have and the decisions you need to make. No assumptions.

02
Build the foundation

Pipelines before dashboards. We establish clean, versioned data flows from source systems before building any analytical layer on top.

03
Surface intelligence

Scorecards, models, and prediction engines built to your institution's specific decisions — not generic templates dropped into your environment.

04
Transfer and embed

We document, train, and hand over. The goal is a team that owns its analytics function — not a dependency on an external vendor.

Let's look at your data together.

If you run a financial institution or ZSE-listed company in Zimbabwe or across Southern Africa, and you suspect your data could be working harder — reach out. The first conversation is always free, and usually revealing.

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