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1
A RESOURCE FOR THE FINANCE INDUSTRY
Quality Data Processing for the
Finance Industry (and Why It Matters)
Without Quality,
What’s the Point?
2
When it comes to data
processing practices in the
financial services industry,
quality
is not
optional.
	By quality, we mean…
•	Accuracy: Those trailing decimal points matter.
•	Speed: Your customers demand responsiveness;
it’s up to your processors to deliver it.
•	Value: Why pay for poor quality?
	
Our 4-part Quality Management Framework delivers
more accurate, faster, and higher-value data processing.
3
3
PART 1
Plan It!
Create a Quality
Management Plan
to set standards for how
you want data managed,
and to empower data
analysts and managers.
At a minimum, your
plan should include:
•	Descriptions of processing tasks
•	Instructions for analysts
•	Processing objectives
•	Processing workflow model
•	Measurement tools
•	Lessons learned
4
PART 2
QA It!
Did you know? Quality
assurance (QA) delivers
confidence—confidence
for management,
clients, regulators,
and stakeholders.
We use one of three QA methods.
METHOD BEST FOR EXAMPLES
Single Pass Simple, objective
use cases
Data classification,
verification, or
enrichment
Review
and Improve
Tasks where
some processor
subjectivity is at play
Receipt or image
transcription
Consensus Highly subjective
tasks where accuracy
is paramount
Invoice transcription,
data categorization
5
5
PART 3
QC It!
QA prevents errors, but QC,
or quality control, warns you
of quality issues in advance,
like a car alert warning you
that your brake pads are
wearing thin.
Implement QC for…
•	An ongoing measurement
of accuracy
•	Better visibility into quality
•	Proactive feedback
6
PART 4
Improve It!
Continuous Improvement (CI),
the last part of the framework,
protects and builds upon all
your hard work.
Our favorite CI approaches?
•	The Plan-Do-Check-Act Cycle
•	Root Cause Analysis
These approaches help you
perpetually monitor, evaluate,
and improve your operations.
P
L
AN
D
O
C
H
E
C
K
A
C
T
CI
7
7
QA QC CI
+ +
High accuracy,
speed, and value
With expertise in data processing
for the finance industry,
CloudFactory
has solved
the Quality
Equation.
=
8
For clients in the finance industry,
CloudFactory
delivers
real results
•	99+% accuracy
•	2x receipt processing capacity
•	Lower cost per document
•	85% reduction in processing time
•	80% faster turnaround time
•	100x processing capacity increase,
to 1M+ invoices per month
9
9
This paper is for you if you:
•	 Hold an operational role in a financial
technology or services company
•	 Need to find better, faster, lower-cost
ways of working
•	 Want an agile, efficient way to optimize
business operations
•	 Are thinking about bringing in a partner
to power your data processing operations
•	 Care about quality data processing
Learn
more
in our white paper,
Outsourced Data
Processing: A Quality
Management Framework
for the Finance Industry.
DOWNLOAD THE WHITE PAPER >>

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Without Quality, What's the Point?

  • 1. 1 1 A RESOURCE FOR THE FINANCE INDUSTRY Quality Data Processing for the Finance Industry (and Why It Matters) Without Quality, What’s the Point?
  • 2. 2 When it comes to data processing practices in the financial services industry, quality is not optional. By quality, we mean… • Accuracy: Those trailing decimal points matter. • Speed: Your customers demand responsiveness; it’s up to your processors to deliver it. • Value: Why pay for poor quality? Our 4-part Quality Management Framework delivers more accurate, faster, and higher-value data processing.
  • 3. 3 3 PART 1 Plan It! Create a Quality Management Plan to set standards for how you want data managed, and to empower data analysts and managers. At a minimum, your plan should include: • Descriptions of processing tasks • Instructions for analysts • Processing objectives • Processing workflow model • Measurement tools • Lessons learned
  • 4. 4 PART 2 QA It! Did you know? Quality assurance (QA) delivers confidence—confidence for management, clients, regulators, and stakeholders. We use one of three QA methods. METHOD BEST FOR EXAMPLES Single Pass Simple, objective use cases Data classification, verification, or enrichment Review and Improve Tasks where some processor subjectivity is at play Receipt or image transcription Consensus Highly subjective tasks where accuracy is paramount Invoice transcription, data categorization
  • 5. 5 5 PART 3 QC It! QA prevents errors, but QC, or quality control, warns you of quality issues in advance, like a car alert warning you that your brake pads are wearing thin. Implement QC for… • An ongoing measurement of accuracy • Better visibility into quality • Proactive feedback
  • 6. 6 PART 4 Improve It! Continuous Improvement (CI), the last part of the framework, protects and builds upon all your hard work. Our favorite CI approaches? • The Plan-Do-Check-Act Cycle • Root Cause Analysis These approaches help you perpetually monitor, evaluate, and improve your operations. P L AN D O C H E C K A C T CI
  • 7. 7 7 QA QC CI + + High accuracy, speed, and value With expertise in data processing for the finance industry, CloudFactory has solved the Quality Equation. =
  • 8. 8 For clients in the finance industry, CloudFactory delivers real results • 99+% accuracy • 2x receipt processing capacity • Lower cost per document • 85% reduction in processing time • 80% faster turnaround time • 100x processing capacity increase, to 1M+ invoices per month
  • 9. 9 9 This paper is for you if you: • Hold an operational role in a financial technology or services company • Need to find better, faster, lower-cost ways of working • Want an agile, efficient way to optimize business operations • Are thinking about bringing in a partner to power your data processing operations • Care about quality data processing Learn more in our white paper, Outsourced Data Processing: A Quality Management Framework for the Finance Industry. DOWNLOAD THE WHITE PAPER >>