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Can AI Bring an End to Paper Receipts? – Part 1

Digitisation processes and the introduction of new technologies go hand in hand with the challenge of ridding organizations from administrative burden such as processing paper receipts. To date, we have seen financial teams making good progress in streamlining and automating processes such as payable accounts and processing invoices.

Paper-Receipts

For example, Artificial Intelligence (AI)-based technologies can already recognize important information contained in documents–invoice or PO numbers, total cost of invoice, payee, date, and if the invoice is on time or overdue. This is certainly set to continue, and the financial teams are increasingly looking at how they can free up time spent on repetitive activities. Management of employee expenses is ripe for this type of transformation as much time has to be spent on managing reimbursements when the real value for accountants and financial professionals lies in managing policy controls and interpreting data.

Digitising Processes

There is an increasing movement towards digital systems and HMRC’s Making Tax Digital (MTD) will come into effect in a few months ‘ time–ending the traditional tax return and requiring organizations to submit digital tax returns using MTD-compatible software. The introduction of MTD will also help to increase the security and reliability of the financial protocol.

Given the latest results from last month’s YouGov poll, Senior Finance and Accounting Decision Makers admitted that they were not the best to keep receipts, and 65 percent admitted that they had been lost in the past. Digitizing these processes within finance will help prevent loss of receipts and improve efficiency with the automatic online backup of these data for future access. This is not the only type of digitisation we see when it comes to digital paper translation. The use of AI-based technology is increasingly transforming the way in which data is gathered and analyzed.

For example, OCR technology can convert typed or handwritten text, whether from a scanned document or a photo. The technology can essentially help fund teams and accountants process data volumes like paper and e-receipts without increasing headcount. This not only saves finance professionals from manually transferring information from paper receipts into expense reports from the drudgery but also harnesses AI engine storage capabilities.

Machine learning algorithms can identify trends and patterns of expenditure and determine future projections as accountants and finance professionals file expenditure claims. This provides better visibility and control of real-time expenditure while also harnessing machine learning capabilities to increase efficiency, quality, and new ways of cost reduction.

The technology can also be used to help prevent fraudulent claims as policy controls can be incorporated into software for expenditure management. As policy validation is automated, this also increases compliance rates, which in turn means that approver intervention is minimal. Such features are invaluable for smaller organizations that may not have dedicated funding teams.

Keep watching this space for more.

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