9,212 applications with at least one DIP in 2025. Of these, 44% pass first time, 22% fail but recover, and 34% fail terminally.
Classification
Every application classified by comparing first DIP outcome to latest.
A third of all DIP'd applications (34%) fail or are referred terminally — low-complexity cases that never progress beyond mortgage-in-principle.
Scene setting
Volume ramps from ~700 in Q1 to 959 in October, then drops seasonally.
The mix is remarkably stable. Terminal failure rate ticked up in H2, peaking at 36.6% in November.
The surprise
Cases that initially fail but recover are nine percentage points more likely to reach offer. The initial failure filters out tyre-kickers, leaving committed applicants.
Full breakdown
| DIP Journey | DIPs | Application Rate | Offer Rate |
|---|---|---|---|
| Clean Pass | 4,023 | 39.3% | 31.1% |
| Fail Recovered | 1,627 | 52.7% | 39.2% |
| Refer Recovered | 419 | 53.9% | 40.1% |
| Failed (terminal) | 2,878 | 0.1% | 0.0% |
| Referred (terminal) | 265 | 0.4% | 0.0% |
+14pp packaging rate, +9pp offer rate for recovered vs clean pass. Both fail-recovered and refer-recovered convert at essentially the same rate once they've passed.
Why?
Cases that retry after failure are more committed. The initial DIP failure filters out tyre-kickers — only serious buyers come back.
Recovered cases score 3.4 vs 2.9 on complexity. More complex = more real: a genuine buyer with a real property.
Brokers actively fix applications — adjusting income, restructuring deposits, removing problematic applicants. Deliberate, skilled work.
Complexity
| Journey | Avg Score | Median |
|---|---|---|
| Refer Recovered | 3.49 | 3.2 |
| Fail Recovered | 3.39 | 3.1 |
| Clean Pass | 2.93 | 2.7 |
| Referred (terminal) | 2.52 | 2.5 |
| Failed (terminal) | 2.29 | 2.1 |
Terminal failures are the simplest cases — fundamentally unviable applications, likely home hunters or early-stage enquiries.
Recovered cases are ~0.5 points higher — roughly a third of a standard deviation. Real complexity, real commitment.
Initial failure reasons
Credit quality is #1 by a wide margin. The next cluster is income and employment (sole traders, gross income, LTI, limited companies, employment status) — collectively ~23%.
Broker intervention
Comparing first (failed) vs latest (passed) DIP inputs. Threshold: >5% change.
Nearly 1 in 3 fail-recovered cases had income change by >5%.
Affordability is the dominant blocker — 53% of first-DIP failures start with affordability not met.
The quality signal
This is the most important table in the analysis.
Instant retries = brute force. Medium recovery (days to weeks) = thoughtful broker work = best outcomes. Over a month = case went cold.
Interpretation
Recovery speed is a proxy for broker quality. The broker who takes a few days to fix a case produces the best outcome.
Deep dive
| Fail Category | Median Days | <1hr Rate | Offer Rate |
|---|---|---|---|
| Other | 2.0 | 30.0% | 39.1% |
| Income / LTI | 2.2 | 29.4% | 44.5% |
| Property | 2.8 | 27.0% | 36.5% |
| Employment Type | 4.9 | 24.3% | 47.0% |
| Credit Quality | 7.7 | 17.2% | 32.3% |
Credit quality takes the longest (7.7 days) and converts the worst (32%).
Employment type converts the best (47%). Sole traders, limited company directors — takes time but solid cases.
Credit quality recovery
How brokers fix credit fails
| Action | Recovered | Still Failed |
|---|---|---|
| Changed income >5% | 43% | 40% |
| Removed an owner | 10% | 0% |
| LTV changed >5% | 17% | 20% |
Removing a problematic applicant is a real but minority strategy (10%). The dominant fix is income adjustment (43%).
The business case
The conditional funnel: what happens after a case passes its DIP?
| Metric | Clean Pass | Fail Recovered | Refer Recovered |
|---|---|---|---|
| Cases (passed DIP) | 4,023 | 1,627 | 419 |
| Submit app (packaging rate) | 39.3% | 52.7% | 53.9% |
| Get offer (of those who submitted) | 79.1% | 74.4% | 74.3% |
| Overall offer rate | 31.1% | 39.2% | 40.1% |
Recovered cases submit apps at 53% vs 39% and convert app→offer at the same rate (~74% vs 79%). The recovery process is a second quality gate — only committed borrowers come back.
The full funnel
Starting from every first DIP — where does each cohort leak?
| Funnel Step | Clean Pass | First Fail | First Refer |
|---|---|---|---|
| Total cases | 4,023 | 4,530 | 659 |
| Step 1: Pass a DIP | 100% | 35.9% | 63.6% |
| Step 2: Submit app (of passed) | 39.3% | 52.7% | 53.9% |
| Step 3: Get offer (of submitted) | 79.1% | 74.4% | 74.3% |
| End-to-end offer rate | 31.1% | 14.1% | 25.5% |
Refers: highest ROI per case. 64% recover, 40% offer rate once recovered. For every 4 refers reviewed, ~1 reaches offer. Help underwriters clear these fast.
Fails: triage, not blanket effort. 62% never retry (zero cost). The 38% who retry convert at 37%. Target employment type (47%) and income/LTI (44.5%).
Where to focus
The central insight: recovery is a quality signal, not a red flag. The initial DIP failure filters out tyre-kickers. Once past that gate, recovered cases outperform clean passes at every step. Spend more time helping refers recover and less time worrying about the fail pool — the serious ones self-select back in.