The given SQL statement is using a CTE (Common Table Expression) to find customers who rented in the last month but not in the current month. Here's the formatted SQL statement:

WITH
  last_month_rentals AS (
    SELECT DISTINCT
      customer_id
    FROM
      rental
    WHERE
      rental_date >= date_trunc('month', current_date - interval '1 month')
      AND rental_date < date_trunc('month', current_date)
  ),
  this_month_rentals AS (
    SELECT DISTINCT
      customer_id
    FROM
      rental
    WHERE
      rental_date >= date_trunc('month', current_date)
      AND rental_date < date_trunc('month', current_date + interval '1 month')
  )
SELECT
  c.*
FROM
  customer c
  JOIN last_month_rentals lmr ON c.customer_id = lmr.customer_id
  LEFT JOIN this_month_rentals tmr ON c.customer_id = tmr.customer_id
WHERE
  tmr.customer_id IS NULL;

Here are some suggestions to optimize the SQL statement for a Postgres database:

1. Use EXISTS and NOT EXISTS instead of JOIN and LEFT JOIN:

SELECT
  c.*
FROM
  customer c
WHERE
  EXISTS (
    SELECT 1
    FROM rental
    WHERE
      customer_id = c.customer_id
      AND rental_date >= date_trunc('month', current_date - interval '1 month')
      AND rental_date < date_trunc('month', current_date)
  )
  AND NOT EXISTS (
    SELECT 1
    FROM rental
    WHERE
      customer_id = c.customer_id
      AND rental_date >= date_trunc('month', current_date)
      AND rental_date < date_trunc('month', current_date + interval '1 month')
  );

1. Create an index on the rental table for the customer_id and rental_date columns to speed up the query:

CREATE INDEX idx_rental_customer_id_rental_date ON rental (customer_id, rental_date);

1. Analyze the rental and customer tables to ensure the query planner has up-to-date statistics:

ANALYZE rental;
ANALYZE customer;

These optimizations should help improve the performance of the SQL statement on a Postgres database.