Softpiper Solutions

Banking and financial services · Documents and back office

KYC review and credit-memo drafting

Extract and cross-check KYC and financial documents with citations, flag discrepancies and draft credit memos inside your own cloud boundary, while analysts decide.

  • ClaudeAnthropic
  • Typical timeline: 8–12 weeks

The problem

KYC and credit analysis mean reading stacks of statements, financials and IDs under strict audit requirements.

  • Analysts spend hours extracting figures before any analysis starts.
  • Discrepancies across documents are easy to miss.
  • Every conclusion has to be explainable to auditors.

How we solve it

Claude extracts and cross-checks fields across documents with citations, flags discrepancies and drafts the credit memo inside your cloud boundary; a human analyst makes every decision.

It plugs into Core banking / LOS exports, Snowflake or BigQuery, SharePoint and Salesforce, so nothing you rely on today is replaced. The architecture below shows each step and which model does the work.

Architecture

From your stack, through the AI layer, to numbers you can track

Each step names the model or system doing the work. Writes to your systems wait for a person to approve them.
KYC review and credit-memo drafting. Your systems (Core banking / LOS exports, Snowflake or BigQuery, SharePoint and Salesforce) connect to Softpiper's AI layer, which runs these steps: Collect documents (LOS exports · SharePoint); Extract with citations (Claude Opus · citations); Cross-check (Snowflake / BigQuery); Draft the memo (Claude Opus); Analyst decision (Review workflow); Inside your boundary (Bedrock · Google Cloud · Foundry). Outcomes are measured as memo preparation time, analyst throughput, discrepancy catch rate and audit findings.

Your stack

  • Core banking / LOS exports
  • Snowflake or BigQuery
  • SharePoint
  • Salesforce

AI layer

Softpiper AI layer

  • Claude
  1. Collect documents, using LOS exports · SharePoint

    Statements, financials and ID documents are collected per application.

  2. Extract with citations, using Claude Opus · citations

    Fields are extracted with citations to the page they came from.

  3. Cross-check, using Snowflake / BigQuery

    Figures are reconciled across documents and against your data warehouse; discrepancies are flagged.

  4. Draft the memo, using Claude Opus

    A credit memo is drafted in your template, with every figure cited.

  5. Analyst decision, using Review workflow

    An analyst reviews, edits and decides; the model never approves or declines.

  6. Inside your boundary, using Bedrock · Google Cloud · Foundry

    Everything runs in your chosen cloud with your logging and access controls.

Outcomes you measure

  • Memo preparation time
  • Analyst throughput
  • Discrepancy catch rate
  • Audit findings

Why this model

Why Claude

We choose per task on capability, cost and where your data must stay. Final versions are picked at kickoff.
ClaudeAnthropic

Claude extracts and reconciles figures with citations, so every number in the memo traces back to a document. It runs where your data must stay: Amazon Bedrock (which AWS operates with no Anthropic operator access), Google Cloud, or Microsoft Foundry's US Data Zone.

Standardised on Google? Gemini Enterprise advertises KYC-analysis skills and financial-services connectors that can sit alongside this workflow for staff research.

Delivery

What you get, how long it takes, and how we keep it safe

Guardrails

  • No autonomous credit decisions.
  • Model-risk governance and documented evaluation before rollout.
  • Explainability through citations on every figure.
  • Data residency set to your regulator's requirements.

Plus the guardrails on every build: facts from your systems, approvals for writes and money, a human one step away, audit logs and evals. See all

Deliverables

  • Extraction and cross-check pipeline
  • Memo template and drafting workflow
  • Analyst review screen
  • Deployment in your cloud
  • Model-risk documentation

Typical timeline

  1. Build, including model-risk and security review8–12 weeks

A planning range for a first production release. We confirm scope, price and dates in a tailored proposal.

KPIs to track

  • Memo preparation time
  • Analyst throughput
  • Discrepancy catch rate
  • Audit findings
  • Turnaround time to decision

Goals we agree with you and measure from a baseline. They are what we track, not results we promise.

Related services

The services behind this playbook

More playbooks

Related playbooks

All playbooks

Pip · Softpiper's AI

Ask Pip about this playbook

Ask Pip how this would work for you

Pip is Softpiper's AI. Tell it what you run today and it will walk through how this playbook fits, what we would build first and a tailored price range. Or book a call with the team.

Book a call