GH Waiver Campaign Performance

Mar 17 – Apr 10, 2026 · Source: ml.loan_info_tbl, LOAN_ACCOUNT_HISTORY, COLLECTION_DAILY, INFOBIP_SMS

Overall Summary

Total Loans

7,930

Fully Paid (discount applied)
481
6.1% conversion

Total Collected

GHS 4.68M

all 7,930 loans incl. partial

Original Debt Exposed

GHS 44.5M

Due After Discount

GHS 21.4M

min repayment to qualify

Yield vs. Original Debt

10.5%

collected / total_due_amount

Structural problem: 4,934 loans (62% of campaign) had never paid on the loan before the campaign. They generated only GHS 366K on GHS 26.4M original debt — 1.4% yield. The 830 loans that paid within 30 days before the campaign generated GHS 2.05M — 5.6× more from 17% of the volume.

Performance by DPD

DPD Band	Loans	Fully Paid	Conversion	Collected	Original Debt	Yield
30–59	2,939	372	12.7%	GHS 2,688K	GHS 17,121K	15.7%
60–89	1,721	66	3.8%	GHS 745K	GHS 9,350K	8.0%
90–119	1,903	33	1.7%	GHS 831K	GHS 10,575K	7.9%
120+	1,367	10	0.7%	GHS 421K	GHS 7,434K	5.7%

DPD 120+: GHS 4.55M discount offered, GHS 421K collected. For every GHS 1 collected, ~GHS 10.8 in discount was ignored.

As expected, the conversion rate for DPD 30–59 was the highest. This aligns with expectations, as this group was exposed to the discount for the first time during this campaign.

Performance by Segment (Prior Payment × DPD)

Payment History	DPD	Loans	Paid	Conversion	Collected	Original Debt	Yield
Paid on campaign day	30–59	82	42	51.2%	GHS 257K	GHS 538K	47.7%
Paid 1–7 days before	30–59	304	89	29.3%	GHS 734K	GHS 1,992K	36.9%
Paid 1–7 days before	60–89	59	14	23.7%	GHS 134K	GHS 345K	38.8%
Paid 1–7 days before	90–119	35	4	11.4%	GHS 56K	GHS 187K	29.8%
Paid 8–30 days before	30–59	526	140	26.6%	GHS 1,061K	GHS 3,225K	32.9%
Paid 8–30 days before	60–89	196	15	7.7%	GHS 255K	GHS 1,162K	22.0%
Paid 8–30 days before	90–119	114	7	6.1%	GHS 195K	GHS 709K	27.5%
Paid 31d+ before	30–59	385	30	7.8%	GHS 390K	GHS 2,424K	16.1%
Paid 31d+ before	60–89	329	19	5.8%	GHS 283K	GHS 1,914K	14.8%
Paid 31d+ before	90–119	537	10	1.9%	GHS 532K	GHS 3,111K	17.1%
Never paid	30–59	1,642	71	4.3%	GHS 247K	GHS 8,941K	2.8%
Never paid	60–89	1,133	16	1.4%	GHS 62K	GHS 5,900K	1.0%
Never paid	90–119	1,212	12	1.0%	GHS 39K	GHS 6,549K	0.6%
Never paid	120+	947	2	0.2%	GHS 18K	GHS 4,992K	0.4%

The conversion rate was highest across all DPD groups for those who had paid within the last 1–7 days.

On the other hand, 62% of the campaign (almost 5,000 loans) had never paid before. They generated GHS 366K — we can assume that without the campaign, these loans would not pay.

Additional Signals

By Balance Size (Due After Discount)

Balance Band (GHS)	Loans	Fully Paid	Conversion
<500	33	11	33.3%
500–1K	344	55	16.0%
1K–2K	2,848	206	7.2%
2K–5K	4,067	202	5.0%
5K+	638	7	1.1%

Achievable amount drives action. Loans under GHS 1K converted at 16–33% — 3–6× the campaign average. Loans over GHS 2K (71% of volume) converted at ≤5%. High balance is the primary friction point: borrowers willing but unable to pay lump sum. Strongest case for tiered instalment offers at 2K+.

By LN Group

LN	Loans	Paid	Rate
4–6	316	9	2.8%
7–10	1,994	74	3.7%
11–15	2,381	126	5.3%
16–20	1,325	85	6.4%
21+	1,914	187	9.8%

By Collection Call Response

Segment	Loans	Paid	Rate
Queue answered	2,333	259	11.1%
IVR only	1,146	89	7.8%
Attempted, no answer	4,450	132	3.0%

All IVR-only loans also had agent attempts — no loans received purely IVR.

SMS Response (INFOBIP_SMS — 6 discount batches)

SMS Batch	SMS Sent	Loans Paid Within 1 Day
Mar 18 — "Second chance"	7,916	100
Mar 20 — "Discount active"	7,814	32
Mar 27 — "Discount reminder"	7,694	37
Apr 1	7,044	36
Apr 6 — Easter SMS	6,311	23
Apr 10 — Last day	6,228	57
Total unique (any batch)	—	285 of 481 (59%)

59% of fully paid loans paid within 1 day of an SMS. First batch (Mar 18) drove the most — borrowers waiting for the offer. Last-day urgency (Apr 10) was second. The first SMS is the highest-leverage send.

What Worked & What Didn't

✓ Worked

DPD 30–59 + paid recently: 27–51% conversion — discount caught active repayers and closed loans
LN 21+: 9.8% overall, 18% at DPD 30-59 — loyal borrowers respond to relationship + offer
First SMS batch: 100 loans paid within 1 day — strongest single channel action
Agent calls: queue-answered loans converted at 11.1% — 3.7× unanswered
Small balances (<GHS 1K due): 16–33% conversion (<500 = 33.3%, 500–1K = 16.0%) — achievable amount drives action; 3–6× campaign average

✗ Didn't Work

Never paid + DPD 60+: 0.4–1.0% yield — discount wasted on 3,292 loans
DPD 120+: 0.7% conversion — GHS 10.8 discount ignored per GHS 1 collected
LN 4–6 + DPD 60+: near-zero — no relationship equity, no response
4,450 unanswered loans: 56% of campaign never got agent contact — massive unrealised upside
Flat 50% discount for high-intent borrowers: recent payers (27–51% conversion) don't need the full 50% to close — Tiers 1+2 can be served at 15–35% with similar conversion, recovering GHS 400–500K more per campaign

Strategy for Next Campaign

Tier 1 — Active repayers

Paid ≤7 days before campaign — all DPD bands

20–35%

Recent payment signal dominates DPD — strong conversion across all bands:
DPD 30–59: 29.3% → 20% discount · DPD 60–89: 23.7% → 25% discount · DPD 90–119: 11.4% → 35% discount
Current rule misses 94 high-intent loans (DPD 60–119) who receive 50% unnecessarily.

Tier 2 — Recent payers

Paid 8–30 days before — DPD 30–59 and DPD 60–89 only

30–40%

Recency signal holds through DPD 60–89 but fades at 90+:
DPD 30–59: 26.6% → 30–35% discount · DPD 60–89: 7.7% → 40% discount
LN 21+ already captured here via recency. LN 21+ with last payment 31d+ ago = 8.5% / 7.0% — only marginally above campaign average, not enough to pull out of Tier 3.

Tier 3 — Everyone else

Never paid · paid 8–30d + DPD 90–119 · paid 31d+ · DPD 120+

50%

Stay in campaign with current 50% discount. Covers cold starters (4–8% conversion), deep delinquent (1–2%), and segments where payment recency signal is lost. Low conversion expected — 50% is the floor offer needed to extract any recovery.

Financial impact estimate: Tiers 1+2 cover ~1,120 loans (Tier 1: 304+59+35=398 · Tier 2: 526+196=722). Reducing average discount from 50% to ~30% (Tier 1 weighted ~22%, Tier 2 weighted ~34%) with conservative 15% conversion loss → +GHS 400–500K incremental recovery per campaign. Tier 3 (6,810 loans, majority of portfolio) unchanged at 50%. No exclusions — everyone stays in campaign.

Decision logic for next campaign

      -- Tier 1: paid within 7 days (all DPD)

      IF last_pmt ≤ 7d AND dpd 30–59  → 20% discount

      IF last_pmt ≤ 7d AND dpd 60–89  → 25% discount

      IF last_pmt ≤ 7d AND dpd 90–119 → 35% discount

      -- Tier 2: recent payers (DPD ≤89) OR loyal borrowers (DPD ≤89)

      IF last_pmt 8–30d AND dpd 30–59 → 30–35% discount

      IF last_pmt 8–30d AND dpd 60–89 → 40% discount

      -- Tier 3: everyone else

      ELSE → 50% discount (current campaign standard)

Database: GHANA_PROD · Campaign cohort filter: loan_discount_start_date::date = '2026-03-17' · Fully paid: loan_discount_amount IS NOT NULL

Methodology notes: Use loan_discount_start_date (not end_date) for cohort — gives 7,930 loans matching LAH exactly. · Prior payment recency must use LAST_REPAYMENT_DATE from LAH at PERIOD = '2026-03-17', not from loan_info_tbl (post-campaign field updated on settlement). · Do not join INFOBIP_SMS + MANUAL_CALLS_PRIORITY_DAILY in same query — triggers MCP false write-detection. Use date-based matching instead.

1 — Overall Summary

SELECT COUNT(DISTINCT loan_id) AS total_loans, COUNT(DISTINCT CASE WHEN loan_discount_amount IS NOT NULL THEN loan_id END) AS fully_paid_loans, ROUND(100.0 * COUNT(DISTINCT CASE WHEN loan_discount_amount IS NOT NULL THEN loan_id END) / COUNT(DISTINCT loan_id), 1) AS conversion_pct, ROUND(SUM(total_due_amount), 0) AS due_before_discount, ROUND(SUM(loan_discount_min_repayment_amount), 0) AS due_after_discount, ROUND(SUM(total_repayment_amount), 0) AS total_collected, ROUND(100.0 * SUM(total_repayment_amount) / NULLIF(SUM(total_due_amount), 0), 1) AS yield_pct FROM GHANA_PROD.ml.loan_info_tbl WHERE loan_discount_start_date::date = '2026-03-17'

2 — Performance by DPD Band

SELECT CASE WHEN lah.DAYS_LATE < 60 THEN '30-59' WHEN lah.DAYS_LATE < 90 THEN '60-89' WHEN lah.DAYS_LATE < 120 THEN '90-119' ELSE '120+' END AS dpd_band, COUNT(*) AS total_loans, COUNT(CASE WHEN lit.loan_discount_amount IS NOT NULL THEN 1 END) AS fully_paid, ROUND(100.0 * COUNT(CASE WHEN lit.loan_discount_amount IS NOT NULL THEN 1 END) / COUNT(*), 1) AS conversion_pct, ROUND(SUM(lit.total_repayment_amount), 0) AS total_collected, ROUND(SUM(lit.total_due_amount), 0) AS original_debt, ROUND(100.0 * SUM(lit.total_repayment_amount) / NULLIF(SUM(lit.total_due_amount), 0), 1) AS yield_pct FROM GHANA_PROD.ml.loan_info_tbl lit LEFT JOIN GHANA_PROD.SEMANTIC_LAYER.LOAN_ACCOUNT_HISTORY lah ON lit.loan_id = lah.LOAN_ID AND lah.PERIOD = '2026-03-17' AND lah.LOAN_DISCOUNT_START_DATE = '2026-03-17' WHERE lit.loan_discount_start_date::date = '2026-03-17' GROUP BY 1 ORDER BY MIN(lah.DAYS_LATE)

3 — Performance by Segment (Prior Payment Recency × DPD)

SELECT CASE WHEN DATEDIFF('day', lah.LAST_REPAYMENT_DATE::DATE, '2026-03-17'::DATE) IS NULL THEN 'D_never_paid' WHEN DATEDIFF('day', lah.LAST_REPAYMENT_DATE::DATE, '2026-03-17'::DATE) <= 0 THEN 'A_campaign_day' WHEN DATEDIFF('day', lah.LAST_REPAYMENT_DATE::DATE, '2026-03-17'::DATE) <= 7 THEN 'B_1-7d_before' WHEN DATEDIFF('day', lah.LAST_REPAYMENT_DATE::DATE, '2026-03-17'::DATE) <= 30 THEN 'C_8-30d_before' ELSE 'E_31d+' END AS pmt_seg, CASE WHEN lah.DAYS_LATE < 60 THEN '30-59' WHEN lah.DAYS_LATE < 90 THEN '60-89' WHEN lah.DAYS_LATE < 120 THEN '90-119' ELSE '120+' END AS dpd_band, COUNT(*) AS total_loans, COUNT(CASE WHEN lit.loan_discount_amount IS NOT NULL THEN 1 END) AS fully_paid, ROUND(100.0 * COUNT(CASE WHEN lit.loan_discount_amount IS NOT NULL THEN 1 END) / COUNT(*), 1) AS conversion_pct, ROUND(SUM(lit.total_repayment_amount), 0) AS total_collected, ROUND(SUM(lit.total_due_amount), 0) AS original_debt, ROUND(SUM(lit.loan_discount_min_repayment_amount), 0) AS due_after_discount, ROUND(100.0 * SUM(lit.total_repayment_amount) / NULLIF(SUM(lit.total_due_amount), 0), 1) AS yield_pct FROM GHANA_PROD.ml.loan_info_tbl lit LEFT JOIN GHANA_PROD.SEMANTIC_LAYER.LOAN_ACCOUNT_HISTORY lah ON lit.loan_id = lah.LOAN_ID AND lah.PERIOD = '2026-03-17' AND lah.LOAN_DISCOUNT_START_DATE = '2026-03-17' WHERE lit.loan_discount_start_date::date = '2026-03-17' GROUP BY 1, 2 ORDER BY 1, 2

4 — Performance by LN Group

SELECT CASE WHEN lit.LN BETWEEN 4 AND 6 THEN 'LN_4-6' WHEN lit.LN BETWEEN 7 AND 10 THEN 'LN_7-10' WHEN lit.LN BETWEEN 11 AND 15 THEN 'LN_11-15' WHEN lit.LN BETWEEN 16 AND 20 THEN 'LN_16-20' ELSE 'LN_21+' END AS ln_band, COUNT(*) AS total_loans, SUM(CASE WHEN lit.loan_discount_amount IS NOT NULL THEN 1 ELSE 0 END) AS fully_paid, ROUND(100.0 * SUM(CASE WHEN lit.loan_discount_amount IS NOT NULL THEN 1 ELSE 0 END) / COUNT(*), 1) AS conversion_pct, ROUND(SUM(lit.total_repayment_amount), 0) AS total_collected, ROUND(SUM(lit.total_due_amount), 0) AS due_before_discount, ROUND(100.0 * SUM(lit.total_repayment_amount) / NULLIF(SUM(lit.total_due_amount), 0), 1) AS yield_pct FROM GHANA_PROD.ml.loan_info_tbl lit WHERE lit.loan_discount_start_date::date = '2026-03-17' GROUP BY 1 ORDER BY MIN(lit.LN)

5 — Performance by Collection Call Response

WITH base AS ( SELECT lit.loan_id, CASE WHEN lit.loan_discount_amount IS NOT NULL THEN 1 ELSE 0 END AS fully_paid, lit.total_repayment_amount AS collected, lit.total_due_amount AS due_before_discount FROM GHANA_PROD.ml.loan_info_tbl lit WHERE lit.loan_discount_start_date::date = '2026-03-17' ), calls AS ( SELECT LOAN_ID, SUM(NUM_QUEUE_ANSWERED) AS queue_ans, SUM(NUM_IVR_ANSWERED) AS ivr_ans, SUM(NUM_QUEUE_ATTEMPTS) AS queue_att, SUM(NUM_IVR_ATTEMPTS) AS ivr_att FROM GHANA_PROD.SEMANTIC_LAYER.COLLECTION_DAILY WHERE "Date" BETWEEN '2026-03-17' AND '2026-04-10' GROUP BY LOAN_ID ) SELECT CASE WHEN COALESCE(c.queue_ans, 0) > 0 THEN 'QUEUE_ANSWERED' WHEN COALESCE(c.ivr_ans, 0) > 0 THEN 'IVR_ONLY' WHEN (COALESCE(c.queue_att, 0) + COALESCE(c.ivr_att, 0)) > 0 THEN 'ATTEMPTED_NO_ANSWER' ELSE 'NO_CONTACT' END AS call_segment, COUNT(*) AS total_loans, SUM(b.fully_paid) AS fully_paid, ROUND(100.0 * SUM(b.fully_paid) / COUNT(*), 1) AS conversion_pct, ROUND(SUM(b.collected), 0) AS total_collected, ROUND(100.0 * SUM(b.collected) / NULLIF(SUM(b.due_before_discount), 0), 1) AS yield_pct FROM base b LEFT JOIN calls c ON b.loan_id = c.LOAN_ID GROUP BY 1 ORDER BY conversion_pct DESC

6 — SMS Batch Dates

SELECT SENT_AT::date AS sms_date, COUNT(*) AS sms_sent FROM GHANA_PROD.DATA.INFOBIP_SMS WHERE SENT_AT::date BETWEEN '2026-03-17' AND '2026-04-10' AND (LOWER(TEXT) LIKE '%discount%' OR LOWER(TEXT) LIKE '%waiver%') GROUP BY 1 ORDER BY 1

7 — SMS Attribution (Paid Within 1 Day of Any Batch)

WITH sms_dates AS ( SELECT SENT_AT::date AS sms_date FROM GHANA_PROD.DATA.INFOBIP_SMS WHERE SENT_AT::date BETWEEN '2026-03-17' AND '2026-04-10' AND (LOWER(TEXT) LIKE '%discount%' OR LOWER(TEXT) LIKE '%waiver%') GROUP BY 1 ), paid_loans AS ( SELECT loan_id, LAST_REPAYMENT_DATE::date AS repaid_dt FROM GHANA_PROD.ml.loan_info_tbl WHERE loan_discount_start_date::date = '2026-03-17' AND loan_discount_amount IS NOT NULL AND LAST_REPAYMENT_DATE IS NOT NULL ) SELECT COUNT(DISTINCT p.loan_id) AS paid_within_1d_any_sms, (SELECT COUNT(*) FROM paid_loans) AS total_fully_paid FROM paid_loans p JOIN sms_dates s ON DATEDIFF('day', s.sms_date, p.repaid_dt) BETWEEN 0 AND 1