https://drive.google.com/file/d/1ppJ1SP6ISzKVa_Vu5K1BNVPfC4yQZxYZ/view?usp=share_link

Accounting is a last remaining hurdle enterprises face on their journeys to become fully data-centric. Instead of relying on centuries-old artifacts such as journals, ledgers, debits and credits, Data-Centric Accounting is a radical rethink that asks what our systems could look like designed from first principles. This session summarizes lessons learned from a 2-year project implementing knowledge graphs and ontologies applied to accounting, and a book written in parallel - “The Future of Accounting”. Highlights include:

Accounting is transformed from backward-looking historical record-keeping into forward-looking strategic decision support.
Commitments are captured and classified by those who make commitments for the enterprise, yielding a more complete and accurate economic story, with valuation and recognition automatically and consistently determined from machine readable accounting policy.
Meaningful reporting is available over any time interval (daily, weekly etc.), not just for pre-defined accounting periods.
An immutable audit trail extends from financial reports back to the initiating events and accounting policy applied
The books are always automatically closed, eliminating the need for flash reports, as the accounting system is as current as any other system in the enterprise.
Some may wonder ""can't we just do this with GenAI and LLMs?"" While those will certainly play a role, integrating them with ontology and knowledge graphs is crucial for them to be effective.
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