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Kidbrooke: why scattered product data puts trust at risk

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Kidbrooke: why scattered product data puts trust at risk

Ask three teams inside a financial institution to describe the same savings product, and according to Kidbrooke, you may well get three subtly different answers.

Pricing lives in one spreadsheet, contribution and tax rules sit in a policy document, and the customer projection is tucked inside whichever calculation engine was available when the journey was built. Each version may be accurate in isolation, but over time they diverge, and someone has to catch the discrepancy before a customer does.

In the latest instalment of its series on KidbrookeONE, the WealthTech firm turns to the first stage of its platform lifecycle: design. Before a customer buys a product or an adviser recommends one, Kidbrooke argues, an institution needs a single trustworthy definition of the product, the local pension and tax rules that govern it, and a projection engine set up to show where it could lead.

The challenge is consistency. Product universes, risk profiling, fees, contribution rules and projection assumptions must align across every channel and partner interface. When they are scattered across disconnected tools, every change has to be copied by hand, and each copy is another opportunity for versions to split apart.

Kidbrooke identifies two areas where the hardest problems typically sit. Pension and tax rules vary by market and errors are expensive, while projections are only valuable if customers believe the numbers. KidbrookeONE addresses both natively, through a rules engine encoding genuine local logic and a simulation engine that turns a product definition into thousands of possible future scenarios.


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