“BI Is Easy and Cheap”: the Myth That Becomes Expensive in Wealth Management

“We already have Power BI / Qlik, so we have BI (Business Intelligence).”

This statement is common. And in Wealth Management, it is rarely true.

In reality, many organizations do not have integrated BI, but a fragile stack:

• multiple data extractions,
• intermediate files,
• manual corrections,
• competing versions of the truth,
• and an IT team acting as a support desk.

The result is predictable: the BI promise exists, but the value does not.

When every business request becomes a mini-project

The pattern is well known:

Business teams ask for “a small report”.

IT delivers:

• an additional data flow,
• a specific extract,
• a temporary patch.

Each new KPI turns into a standalone project.

The consequences are immediate:

• a saturated IT roadmap,
• uneven adoption by business users,
• and eventually… everything falls back into Excel.

BI exists on paper, but performance management remains manual.

What changes when analytics is truly integrated with Core Banking

The breakthrough does not come from adding another BI tool.

It happens when analytics is structurally integrated into the Core Banking environment.

At that point, you move away from the model:

ticket → extract → Excel file

And enter an industrialized approach:

• a stable reference for clients, portfolios, and transactions,
• consistent modeling of movements and revenues,
• shared, documented, and governed KPIs.

Analytics becomes a structural asset, not an accumulation of requests.

Business autonomy without shadow IT

Well-integrated analytics restores business autonomy without creating shadow IT.

Users can analyze, segment, and explore:

• within a governed framework,
• fully auditable,
• and controlled by the organization.

Figures remain traceable, rules are shared, and credibility is preserved.

The real value is not in the BI tool

The value is not in Power BI, Qlik, or any other visualization tool.

It lies in:

• the integration layer around Core Banking systems,
• data and KPI governance,
• business models that structure analytics.

Without these foundations, BI may be easy to buy… but very expensive to operate.