# Documents in lending ## AI Underwriter ### Every file the same rigor. Every memo drafted in seconds. Every decision yours to sign. Spreads the financials, reads the story behind the numbers, and drafts the memo a senior analyst would write — calibrated to your credit policy. Your team edits and signs. **What it does** Spread · Story · Memo **Source citations** Every claim **Tunable to** Your credit policy **Final decision** Your underwriter **Used across** SME & commercial lending·CDFI underwriting ## A defensible memo, drafted ### A defensible memo, before your team sits down. Kita's AI Underwriter reads every page of every document, models cash flow, and drafts a credit assessment with cited evidence — calibrated to your credit policy. Every number traces back to a source line. Nothing is invented. ### Applicant **Verde Logística S.A. de C.V.** Mexico City · Trucking · 36 employees Requested MXN 16M Term 36 mo Purpose Fleet expansion (12 trucks) **Recommendation · APPROVE** MXN 14.4M · 36 mo · 16.5% APR Approve below requested. Cash flow supports debt service at 1.42× DSCR over the trailing 12 months. Counter at 80% of ask given concentration in two contract counterparties (61% of receipts). ### Cash flow Trailing 12-mo operating cash flow MXN 8.1M / yr. Margin holding at 14.6% across 73 monthly statements reviewed across BBVA and Santander. ### Debt service Existing obligations MXN 1.6M / yr. Pro-forma debt service with this facility MXN 5.7M / yr, leaving DSCR 1.42× at base case, 1.19× at -15% revenue stress. ### Risk notes Counterparty concentration: top two clients drive 61% of receipts. One late SAT filing in Q2 2025, since cured. Tax compliance current per constancia de situación fiscal. Drafted by Kita AI Underwriter · 17 sources · 2.4s **Policy check** SME Term Loan · MX-2026-Q2 5 / 6 pass DSCR ≥ 1.25 1.42 30-day arrears = 0 Yes Tax compliance current Yes Operating tenure ≥ 24 mo 8.2 yr Margin ≥ 8% 14.6% Concentration < 50% 61% Final approval is always a human at your institution. ## The problem ### Credit assessment is uneven. 1. **Inconsistent decisions** Different analysts apply different standards. Portfolio risk compounds when underwriting quality varies across your team. 2. **Generic models don't fit your book** Off-the-shelf credit scores weren't built for your borrower profile. They miss the signals that actually predict repayment in your portfolio. 3. **No feedback loop** You generate outcomes data with every loan, but your underwriting logic never learns from it. The same blind spots repeat. 4. **Speed vs. quality tradeoff** Scaling volume means either hiring more analysts or accepting lower-quality decisions. Neither is sustainable. ## What it does ### An analyst, in your stack. Not a black-box score. Kita does the same three things a senior credit analyst does — spreads the financials, reads the story behind the numbers, and drafts the memo. Faster, and at scale. i. **Financial spreading** Pulls statements, GLs, and bank data into a normalized period-over-period spread. DSCR, margin, debt service, trend — all computed in one pass. ii. **Story behind the numbers** Reads the qualitative narrative the spread alone won't tell you — why margins moved, what concentration risk looks like, what an arrears spike actually signals. iii. **Drafts the memo** Produces the credit memo a senior analyst would write — recommendation, evidence, risk notes — every claim cited to a source line. Your team edits, signs, sends. ## Capabilities ### More than a model. Kita does the work an analyst does — spreads the financials, reads the story behind them, and drafts the memo. Calibrated to your credit policy. Every number traces back to a source line. Nothing is invented. - Financial spreading — Pulls financials and bank data into a clean period-over-period spread. Ratios, trend, debt service modeled out of the box. - Reads the narrative — Picks up the qualitative story behind the numbers — concentration risk, seasonality, why margins moved, what late filings imply. - Drafts the memo — Produces the credit memo your senior underwriter would write. Recommendation, evidence, risk notes, ready to edit. - Cited to source — Every claim in the assessment links back to the document line that produced it. Audit in one click. - Calibrated to your policy — Tune the decisioning criteria that matter to your book. Not locked into a generic credit score. - Adaptive — Recommendation quality improves loan cycle over loan cycle as your portfolio grows. ## Why it matters 1. **Designed for volume** Hundreds or hundreds of thousands of applications per month. Scales without adding operational overhead. 2. **Outcome-driven** Traditional scorecards are static. Kita learns from what actually happens in your portfolio. 3. **Wires into your stack** API-first. Integrates into your existing LOS, credit engine, or custom workflow. ## Underwrite more borrowers. Faster. With cleaner data.