SQL Server 2022

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create table mytable (
   Id int,
   CustomerNumber int,
   Payment_installments int,
   Date date
);

insert into mytable values
( 1, 2, 0, '2022-01-02'),
( 2, 2, 0, '2022-02-10'),
( 3, 2, 1, '2022-04-05'),
( 4, 3, 0, '2022-06-01'),
( 5, 2, 0, '2022-06-08'),
( 6, 2, 0, '2022-08-22'),
( 7, 2, 1, '2022-10-03'),
( 8, 3, 0, '2022-11-04'),
( 9, 2, 0, '2023-01-04');
9 rows affected

with cte as (
  select *, lag(Payment_installments, 1, 0) over (partition by CustomerNumber order by Date) as previous_installement
  from mytable
)
select *
from cte


Id
CustomerNumber
Payment_installments
Date
previous_installement


1
2
0
2022-01-02
0

2
2
0
2022-02-10
0

3
2
1
2022-04-05
0

5
2
0
2022-06-08
1

6
2
0
2022-08-22
0

7
2
1
2022-10-03
0

9
2
0
2023-01-04
1

4
3
0
2022-06-01
0

8
3
0
2022-11-04
0


with cte as (
  select *, lag(Payment_installments, 1, 0) over (partition by CustomerNumber order by Date) as previous_installement
  from mytable
)
select *, sum(previous_installement) over (partition by CustomerNumber order by Id) as sm
from cte


Id
CustomerNumber
Payment_installments
Date
previous_installement
sm


1
2
0
2022-01-02
0
0

2
2
0
2022-02-10
0
0

3
2
1
2022-04-05
0
0

5
2
0
2022-06-08
1
1

6
2
0
2022-08-22
0
1

7
2
1
2022-10-03
0
1

9
2
0
2023-01-04
1
2

4
3
0
2022-06-01
0
0

8
3
0
2022-11-04
0
0


with cte as (
  select *, lag(Payment_installments, 1, 0) over (partition by CustomerNumber order by Date) as previous_installement
  from mytable
),
cte2 as (
  select *, sum(previous_installement) over (partition by CustomerNumber order by Id) as sm
  from cte
)
select Id, CustomerNumber, Payment_installments, Date, case when sm > 0 then 1 else 0 end as HasInstallmentPaymentInThePast
from cte2
order by Id


Id
CustomerNumber
Payment_installments
Date
HasInstallmentPaymentInThePast


1
2
0
2022-01-02
0

2
2
0
2022-02-10
0

3
2
1
2022-04-05
0

4
3
0
2022-06-01
0

5
2
0
2022-06-08
1

6
2
0
2022-08-22
1

7
2
1
2022-10-03
1

8
3
0
2022-11-04
0

9
2
0
2023-01-04
1

Id	CustomerNumber	Payment_installments	Date	previous_installement
1	2	0	2022-01-02	0
2	2	0	2022-02-10	0
3	2	1	2022-04-05	0
5	2	0	2022-06-08	1
6	2	0	2022-08-22	0
7	2	1	2022-10-03	0
9	2	0	2023-01-04	1
4	3	0	2022-06-01	0
8	3	0	2022-11-04	0