Case Study - Loss Prevention
In an average American socio economic demographic:
1 year post installation of AIShop Facial Recognition solution, the average American loss results are as follows:
53% reduction in loss;
Shelf sweeps have ceased (previously, multiple categories were swept on a weekly basis)
Loss prevention staff numbers reduced by 0.5 Full Time Position
Theft by armed robbery reduce to Nil, whilst 2 competing stores within 4 blocks experienced armed robbery
"Shelf sweeps that happened frequently are now extremely rare.”
In a poor American socio economic demographic:
Benchmark Starting Scenario:
Loss rates are 3 – 10 x Average American socio economic area
~15 repeat thieves per week / Average loss $50 - $300 per thief
Regular shelf sweeps include: batteries, watches, razor blades, electronics, cough/cold and ladies toiletries
90 days later:
Repeat persons rarely revisit
Theft rate dramatically reduced; case preparation/prosecution not required
"We have trained the evil 20 to go somewhere else.”
"Retail in Realtime is fundamentally changing our processes and dramatically impacting the business’ bottom line”
Head of Security
Case Study - Anti Armed-Robbery
Preventive Strategy to Combat Armed Robberies
Between the hours of 10:00 p.m. and 6:00 a.m. all customers must have their face clearly scanned before the door is opened
If the face is not acceptable (due to customer wearing a mask or the face is obscured or wearing a helmet etc. then access will be denied
Reduction in the robbery rate in Chicago and Baltimore by 60%.
Robberies occurring earlier before mandatory face recognition being turned on.
Next strategy is to extend the period of mandatory face scanning.
Case Study - Shopping Mall BI
Shanghai incity Vanke mall opened 26/10/2018. There are around 400K population within 3km circle.
Face capture camera installation
BI-F5 face capture cameras install locations