Either [FINandREs] or [FinREa] can be used with the new SIP data, and have about 92% overlap.

FINwithRE: pref(if(trbc2.s=55!60,1,0),if(sector.s=7,1,if(incd.s=933,1,0)))
FINwithRE2024: pref(if(trbc2.s=40!60,1,0),FINwithRE)
FINandREs: if(ord(1)>=26081,FINwithRE2024,FINwithRE)

FinREa: if(fincd12.a=11,1,0)

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Details:

TopLineFirst posted a field to handle the 2018 SIP industry change:
FINwithRE: pref(if(trbc2.s=55!60,1,0),if(sector.s=7,1,if(incd.s=933,1,0)))
http://www.datahelper.com/mi/search.phtml?nofool=y...

After the 20241001 SIP industry change, the Finance and Real Estate Sectors are trbc2.s=40!60. New fields to handle this change:

FINwithRE2024: pref(if(trbc2.s=40!60,1,0),FINwithRE)
FINandREs: if(ord(1)>=26081,FinanceRE2024,FINwithRE)

The ordinal date of Tuesday 20241001 is 26079, but Thursday 26081 gives smoother stock counts.
The number of S&P 1500 stocks in the Finance and Real Estate sectors increased from 217 to 343 in the last 20 years (using SIP data), and jumped to 368 with the new SIP data.

[fincd12.a] can also be used to find Finance and Real Estate stocks. Note that [fincd12.a]=11 includes most Real Estate stocks (styp.a=18!48):
FinREa: if(fincd12.a=11,1,0)

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The screen {FINandRE2024} compares the 2 lists of stocks created by the fields [FINandREs] and [FinREa]. Stocks passing step2 are the union of the 2 lists. Stocks passing step3 are the intersection of the 2 lists. The Jaccard Index (intersection size over union size) is also calculated.

Define {FINandRE2024}
Create [sumFlags]: [[FINandREs] + [FinREa]]
Create [JaccardIndex]: [[# Eligible at step4]/[# Eligible at step3]]
step0: [S&P 1500 Member] == 1
step1: [Max([SI Sales Q1], [SI Sales Y1])] > 0
step2: [sumFlags] >= 1
step3: [sumFlags] == 2
step4: [JaccardIndex] != -987
gtr1.net: GTR1 Backtester - FINandRE2024

The Jaccard Index (IoU) using [FINandREs] and [FinREa] is about 90%.

                      IoU      IoU
  From       To     Average  StdDev
19970902  20011009    88%      4%
20011010  20140126    93%      2%
20140127  20181028    86%      1%
20181029  20241006    91%      1%
20241007  20241205    88%      0%