feat(statements+analytics): normalise statement_type; fix analytics scoping

Groundwork for importing bank and loan statements alongside credit cards.

statement_type was whatever free text Gemini put in account_type ('Credit Card',
'credit card', 'credit_card', 'Business Card', 'ACCESS ADVANTAGE',
'multi-currency account'). The UI coped only by doing .includes("card"), which
breaks as soon as bank and loan statements arrive.

- Migration 0013 adds normalize_statement_type() + a BEFORE INSERT/UPDATE
  trigger and a CHECK constraint over credit_card|transaction|savings|loan|
  offset|investment|other. The trigger means the N8N workflow keeps working
  unchanged while it still sends free text. Raw value stays in account_type.
  Backfilled 99 existing rows.
- src/lib/statement-types.ts mirrors the vocabulary for the UI; statements page
  now filters by the real types and headlines balance vs amount due per type.

Analytics were scoped with INNER JOIN statements + s.owner_id, which silently
dropped all 180 manual/CSV transactions (statement_id IS NULL) from every
report. Switched all six routes to LEFT JOIN + COALESCE(t.owner_id, s.owner_id)
via shared fragments in src/lib/analytics-sql.ts, so the transfers/investment
exclusion that stops card-payment double counting stays consistent. Also
extended that exclusion to trip analytics, which had none.

Drive-by: /api/analytics/subscriptions was returning 500 on an unserialisable
BigInt from COUNT(*) + 1.

Verified against the live DB: monthly spend picks up the previously invisible
manual transactions (Apr 9,849.91 -> 14,286.70) and all four analytics
endpoints return 200.

src/app/api/analytics/monthly/route.ts

@@ -1,6 +1,12 @@
 import { NextRequest, NextResponse } from "next/server";
 import { getCurrentUser } from "@/lib/auth";
 import { queryRaw } from "@/lib/db";
+import {
+  OWNER_SCOPE,
+  STATEMENTS_JOIN,
+  EFFECTIVE_CATEGORY,
+  EXCLUDE_NON_SPEND,
+} from "@/lib/analytics-sql";
 
 export async function GET(req: NextRequest) {
   const user = await getCurrentUser(req);
@@ -25,7 +31,7 @@ export async function GET(req: NextRequest) {
   }>(
     `SELECT
       TO_CHAR(DATE_TRUNC('month', t.transaction_date::date), 'YYYY-MM') as month,
-      COALESCE(o.category_override, t.category) as category,
+      ${EFFECTIVE_CATEGORY} as category,
       SUM(
         CASE
           WHEN ts.share_percent IS NOT NULL THEN COALESCE(t.amount_aud, t.amount) * ts.share_percent / 100
@@ -37,10 +43,10 @@ export async function GET(req: NextRequest) {
     FROM transactions t
     LEFT JOIN transaction_overrides o ON o.transaction_id = t.id
     LEFT JOIN transaction_splits ts ON ts.transaction_id = t.id AND ts.participant_id = $1
-    JOIN statements s ON s.id = t.statement_id
-    WHERE s.owner_id = $1
+    ${STATEMENTS_JOIN}
+    WHERE ${OWNER_SCOPE} = $1
       AND t.transaction_type IN ('debit', 'fee', 'interest')
-      AND COALESCE(o.category_override, t.category) NOT IN ('transfers', 'investment')
+      AND ${EXCLUDE_NON_SPEND}
       AND t.transaction_date >= $2
       AND t.transaction_date < $3
     GROUP BY 1, 2
@@ -60,10 +66,10 @@ export async function GET(req: NextRequest) {
       COUNT(*)::int as transaction_count
     FROM transactions t
     LEFT JOIN transaction_overrides o ON o.transaction_id = t.id
-    JOIN statements s ON s.id = t.statement_id
-    WHERE s.owner_id = $1
+    ${STATEMENTS_JOIN}
+    WHERE ${OWNER_SCOPE} = $1
       AND t.transaction_type IN ('credit', 'payment')
-      AND COALESCE(o.category_override, t.category) = 'income'
+      AND ${EFFECTIVE_CATEGORY} = 'income'
       AND t.transaction_date >= $2
       AND t.transaction_date < $3
     GROUP BY 1
@@ -83,9 +89,9 @@ export async function GET(req: NextRequest) {
       COUNT(*)::int as transaction_count
     FROM transactions t
     LEFT JOIN transaction_overrides o ON o.transaction_id = t.id
-    JOIN statements s ON s.id = t.statement_id
-    WHERE s.owner_id = $1
-      AND COALESCE(o.category_override, t.category) = 'investment'
+    ${STATEMENTS_JOIN}
+    WHERE ${OWNER_SCOPE} = $1
+      AND ${EFFECTIVE_CATEGORY} = 'investment'
       AND t.transaction_date >= $2
       AND t.transaction_date < $3
     GROUP BY 1