2. • Introduction
• What is Intelligent Document Processing (IDP)?
• Benefits of IDP
• IDP Driven Efficiency Increases in:
• Claims (Deductions) Processing
• Cash Application
• Credit Control
• Accounts Payable
• Customer Success Story
• Conclusion
• Your Questions
Agenda
3. 3
Introduction
Financial documents are numerous, vary widely in format (unstructured),
and contain lots of information, making data extraction difficult.
It is estimated by Gartner that 80% of financial data arrives in an
unstructured form.
Key Tasks in Processing Unstructured Data:
a. understand the context and use of the data
b. extract all and only the required data (even from handwritten documents)
c. combine the context with the data
d. input (keypunch) into correct ERP application for further processing
Historically, processing unstructured data required human intelligence to
cope with the wide variation. It included a high volume of repetitious data
entry.
IDP automates the handling of unstructured data.
4. 4
What is Intelligent Document Processing?
Intelligent Document Processing (IDP) extracts & converts unstructured data into a
usable structured, format for the next step in processing that data. It extracts all and only
the required data.
It utilizes cognitive Artificial Intelligence (AI) and other related technologies such as
Machine Learning, Natural Language Processing, and Robotic Processing Automation
(RPA).
Source documents are scanned & data is extracted:
• The documents are stored digitally
• The data is available to authorized users anywhere in the world, 24/7/365 in digital form.
Cognitive AI data extraction is faster, cheaper and more accurate than having humans read
documents. Even Robotic Process Automation (RPA) doesn’t work as well with multiple
unknown document formats.
IDP accommodates multiple languages and currencies & delivers substantial
increases in speed, accuracy and productivity
5. 5
Benefits of IDP in AR and AP Operations
Substantially Increased Employee Productivity
Lower staff attrition thru job enrichment
Increased accuracy and quality of operations
Faster response to Customers
Speed, Productivity and Accuracy
Improved Customer
Experience/Satisfaction
Increased
Productivity
Lower Cost Increased Revenue
& Profit
6. 6
IDP Driven Efficiency Increases in
Deductions Processing
• Extracts required data from Vendor or EIPP Portal, Remit
advice, email, debit memo, etc. and automatically create
deductions to be routed for resolution
• Key data includes customer number, invoice # & value,
payment # & value, deduction value, dates, reason code, etc.)
• Data arrayed in CSV file and fed into downstream processing
• Establishes unique record for every individual deduction
• Stores digital images of all documents
7. Extracts remittance data from multiple customer sources with varying
formats, such as:
• Customer Vendor Portals & your own EIPP Portal
• Remittance Advice contained in Excel spreadsheets, PDF/tiff (tagged image file
format), email attachments
• Checks and check stub images and bank statement PDF’s
• Lockbox image files in PDF, tiff, gif (graphics interchange format), other formats
• Lockbox Data files in Excel, MT940, EDI 820 formats or BAI2
7
Constructs file (CSV or other formats) for input into auto-cash engine
to apply receipts to correct invoices
• Integrates with bank lockboxes, your own AR and Collection modules and ERP
• Auto-Cash engine can yield 85 – 95% hit rate
• Outperforms RPA when dealing with multiple unknown document formats
IDP Driven Efficiency Increases in
Cash Application
8. 8
IDP Driven Efficiency Increases in Credit Control
• Extracts required data to conduct a credit investigation
from the credit application (company legal name,
address, tax ID, etc) submitted via Fax, email (including
pdf files), postal mail, etc.
• Automatically checks business licenses, OFAC list, credit
bureau data, etc. to enable credit vetting
• Establishes credit file for the individual company
• Data arrayed in client specified format to facilitate review
• Calculate a credit score and credit limit
9. 9
IDP Driven Efficiency Increases in Accounts Payable
• Extracts required data from invoices delivered via Vendor
Portal, EDI, email, postal mail, etc.
• Automatically extracts data required to approve & pay an
invoice (vendor name & number, PO #, invoice # & value,
payment due date, prompt payment discount, etc.)
• Retrieves applicable receiving document and PO
• Establishes unique record for every individual vendor
invoice
• Data arrayed in CSV file and fed into AP system
10. IDP Feeds RPA & AI
• Vendor Portals
• EIPP Portals
• Excel files
• PDF/tiff/gif files
• E-mail
• Fax
• Paper/hard copy
• Lockbox data & files
• MT940, EDI 820, BAI2
Trans.
• Bank Statements
• Credit Applications
• Orders, Remits, Deductions
CUSTOMERS, BANKS,
CREDIT BUREAUS, ETC.
Extracts & Converts
unstructured data into
structured data in a
CSV File
IDP
• Accepts data.
• Basic processing with ERP
• Emulates human interaction with ERP.
• Best with simple, repetitive, high
volume operations
RPA
• Retrieve Credit info
• Compute credit score and limit
• Collections emails with dialogue
• Auto-cash & small balance W/O
• Routes deductions, etc., etc.
AI DIGITAL ASSISTANTS
(If needed)
FURTHER
PROCESSING
(If needed)
FURTHER
PROCESSING
90 + % Automation
90 + % Automation
70 - 90 % Automation
11. 11
Challenge:
Operates in 45 countries, 15 languages, 16 bank accounts
Established in-house SSC while embarking on digitization of OTC
Solution:
Emagia IDP executed by AI Powered Digital Assistants for Claims,
Cash Application, and Collections modules
Customer Value Achieved:
Cash Application: Auto-cash hit rate increased from:
a. 10% to 80% in Australia
b. 70% to 95% in France
c. 50% to 80% overall
Deductions: Resolution time decreased from several weeks to < one week
Customer Success Story – Global Medical
Products Supplier
12. Conclusion
IDP in AR and AP Financial Operations:
• Are used by many leading companies TODAY !!
• Can increase productivity by 70 - 90% for manual operations
• Enable faster response to customers
• Improve the accuracy of transaction processing
• Enriches jobs by reducing data entry, enabling more work on
varied analytical and problem solving tasks. This will reduce
attrition, the cost of hiring, and learning curve inefficiencies of
replacement employees