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"I was looking for a tool capable of forecasting cash taxes for large groups of companies across multiple years. It needed to be sophisticated enough to manage:  

• Multiple group relief or consortium groups 

• Multiple Corporate Interest Restriction groups 

• Thin capitalisation and anti-hybrid adjustments 

• High value capital allowances 

• Non-coterminous accounting periods

I was asked if I would like to participate in a case study involving Deep Tax, a system that uses AI technology to optimise the tax position for groups of companies within a single or multiyear timeframe.  This was of significant interest, and I was naturally keen to take part.
 

In our use of Deep Tax, I was extremely impressed that the system was able to handle the above complexities and propose an optimised mix of claims and reliefs (loss reliefs, group relief (current and brought forward losses), capital allowances, CIR allocations, etc.) that ​minimise CT liabilities and optimise other attributes e.g. losses and TWDV carried forward.  

Deep Tax used AI to find optimal outcomes without relying on a uniform approach to variables such as group relief, CIR allocations, etc, as our in-house forecasting models had required. In my review of the results, I did not discover any instances where I thought a “wrong” decision had been made by Deep Tax.  I considered the report's output to be a helpful balance between being comprehensive and being readable.  

Overall, Deep Tax offered us a powerful solution within a complex group with very impressive capability and results."

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Alex Clayton

Group Tax Manager

Bioenergy Infrastructure Group