The funding story, reconciled line by line.
Source of funds fails audits when the numbers do not add up and nobody noticed. ConveySure treats the funding story as arithmetic first: declared contributions are calculated by code, compared against observed evidence, and any gap is surfaced as a named, unresolved amount.
Every purchase reduces to one equation.
The funds calculator starts from the purchase price and subtracts each declared source. Whatever remains is not a vague concern — it is a specific figure the file must explain before exchange.
The calculation is deterministic and code-owned. AI never invents or adjusts a number; it only helps explain what the numbers show.
Illustrative fictional matter. The unresolved difference appears on the matter as a blocker until it is evidenced or explained.
Credits are grouped before they are judged.
Statement analysis sorts incoming funds into categories that map to source-of-funds reasoning — so a fee earner reviews a structured picture, not four hundred raw rows.
Highlighted categories attract additional scrutiny by default; firm risk-appetite settings control the thresholds.
Different funding stories need different evidence.
Select a scenario to see what the system expects, requests and checks in each case.
Salary and savings
Expected evidence: three to six months of bank statements plus payslips or a P60.
What is checked: salary credits match declared income; the savings balance is consistent with accumulation over time rather than appearing suddenly; the deposit can plausibly come from earnings.
Typical outcome: a clean reconciliation, or a question about a balance jump the earnings history does not explain.
Gifted deposit
Expected evidence: signed gift letter, giftor identity, and the credit arriving in the client account.
What is checked: letter amount versus declared gift versus observed credit; non-repayable wording; whether firm policy requires the giftor's own source of funds.
Typical outcome: a three-way match — or an escalation when the observed gift differs from the declared one.
Sale proceeds
Expected evidence: completion statement from the related sale and the matching credit from the acting solicitor.
What is checked: net proceeds against the declared contribution; the payer is the named firm; timing is consistent with the sale.
Typical outcome: a directly traceable credit — the strongest form of funding evidence when the chain matches.
Investment disposal
Expected evidence: platform statements showing the holding, the disposal and the withdrawal to the client bank account.
What is checked: account ownership, disposal proceeds against the arriving credit, and whether the original investment itself needs sourcing under firm policy.
Typical outcome: a traceable path from platform to bank — or a question about where the invested capital originated.
Crypto proceeds
Expected evidence: exchange account records, disposal history and the fiat withdrawal reaching the named bank account.
What is checked: exchange account ownership, the conversion-to-fiat trail, and consistency between disposal amounts and arriving credits. Gaps in the trail are flagged rather than assumed away.
Typical outcome: a documented trail, or an early MLRO referral where the origin of the crypto cannot be evidenced.
Overseas funds
Expected evidence: overseas account statements, transfer records and an explanation of how the funds were originally accumulated.
What is checked: the sending account belongs to the client or a declared party, jurisdictional risk factors, and the underlying accumulation story. Overseas transfers raise the review threshold automatically.
Typical outcome: a documented international trail with recorded reasoning — or an EDD escalation.
Company / director funding
Expected evidence: company accounts or filings, evidence of the director's entitlement (dividends, loan account), and the corporate-to-personal transfer.
What is checked: declared directorships against filed records, whether corporate payments match a legitimate entitlement, and separation between company money and personal contribution.
Typical outcome: a reconciled corporate trail — or exactly the kind of undeclared corporate credit that appears in the example below.
Four columns decide whether the story stands up.
| Source | Client declared | Calculator expects | Evidence shows | Position |
|---|---|---|---|---|
| Mortgage | £280,000 | £280,000 | Offer for £280,000 | Reconciled |
| Gift | £45,000 | £45,000 | Letter + credit £45,000 | Reconciled |
| Savings | £100,000 | £100,000 | £87,500 evidenced | £12,500 short |
| Corporate credit | Not declared | — | £24,500 from ABC Holdings | Unexplained |
Illustrative fictional matter. Anything in the last two states blocks readiness until resolved and recorded.
Findings become questions a client can actually answer.
Drafted questions are specific, plain-language and tied to the finding that raised them. The fee earner edits and approves before anything is sent.
“Your June statement shows £24,500 received from ABC Holdings Ltd on 14 June. Could you tell us what this payment relates to, and provide any supporting documents?”
“You told us your savings contribution is £100,000, but the statements provided evidence £87,500. Could you send statements for any other account holding the remaining £12,500?”
“Your gift letter is signed by Mrs A. Okafor. So we can complete our checks, please provide her photo ID and confirm her relationship to you.”
Code calculates. AI explains. People decide.
Code
- Calculates the funding equation.
- Groups statement credits into categories.
- Reconciles declared against observed.
- Compares figures across documents.
AI
- Summarises what the evidence shows.
- Identifies contextual issues worth a look.
- Drafts client questions from findings.
Human
- Reviews every finding and summary.
- Challenges what does not stand up.
- Approves the conclusion on the record.
Next: when the funding story needs a second pair of eyes.
Unresolved amounts and high-risk scenarios flow into the MLRO referral queue with their full context attached.