Finance & Reporting
Contract data extraction
Extract key commercial terms from supplier and customer contracts — payment terms, renewal dates, liability caps, exclusivity clauses — into structured records.
70–85%
reduction in contract review time
Opportunity assessment
Minor improvement. Small efficiency gain with limited effect on overall turnover or bottom line.
Relatively straightforward. Off-the-shelf tools handle the core task. Implementation is well-understood with good examples to follow.
Light data requirements. Uses straightforward inputs — documents, product descriptions, customer records — that are usually accessible with minimal prep.
Moderate risk. Some customer or external exposure. Errors create rework or reputational impact but are recoverable.
Light people impact. A new tool slots into an existing workflow. Minimal training needed. Most people will adapt quickly.
Tooling required
Things to consider
JPMorgan Chase's COIN platform reduced 360,000 hours of annual lawyer and loan officer work to seconds, extracting 150 attributes from 12,000 commercial credit agreements with compliance errors reduced approximately 80% (Bloomberg).
Define the extraction schema first — what specific fields do you need from every contract? The AI extracts what you ask for.
Contract language is deliberately complex: for high-value or unusual contracts, legal review of the extracted data remains important.
The biggest value is in the ongoing management use case — renewal date alerts, auto-flagging of contracts approaching expiry or with unusual terms.
Start with a contract type where the schema is well-defined and relatively consistent — standard supply agreements or NDAs — rather than bespoke commercial contracts where language varies significantly.
Experiment starter: Select 30 supplier contracts of the same type. Define the 8–10 fields you need to extract. Run the extraction and manually verify against the originals. If accuracy on key commercial fields (payment terms, renewal dates, exclusivity clauses) exceeds 90%, proceed to bulk extraction.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — The Experimentation FrameworkThis is an augmentation opportunity — see the relevant playbook section for how to approach it.More in Finance & Reporting
Period-end commentary drafting
Convert financial data into narrative commentary for management accounts. Finance team reviews and adjusts. Eliminates the blank-page problem at month end.
Invoice exception identification
Flag invoices with missing PO references, duplicate submissions, price variances, or unusual payment terms before they reach approval.
Variance analysis narrative
Draft plain-language explanations of budget versus actual variances from structured data. Provides first-draft reasoning that analysts review and validate.
AI Transformation Playbook
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