Thought Leadership
23 Jul 2024

Not All Accounting Data Extraction Tools are Created Equal: A Guide for Auditing Firms

The race to deliver a data-driven audit is well underway.

In today's fast-paced business environment, auditing firms globally are embracing technology that enables them to deliver a superior, higher-quality customer experience. One Accounting Today survey revealed that 73% of firms reported an "urgency" for tech adoption. This widespread recognition of technology's importance underscores the need for firms to evaluate their current practices and consider upgrades. 

But the key to success lies in choosing technology to fit your specific firm needs. Every firm is different, and auditors must do their own research. For many firms the first goal on the agenda is; get the data right. This guide aims to equip auditors with the knowledge to assess accounting data extraction tools effectively. By the end, you'll understand the key features to look for, questions to ask potential providers, and how these tools can transform your audit process.  

5 key features to look for in data extraction tools

1. Data Depth & Breadth
  • Why it’s important: Access to granular financial data, enabling more thorough and efficient audits. 
  • What to expect: Comprehensive extraction of all ERP data, including sub-ledger details.
  • Questions to ask: 
    • "Do you extract the sub-ledgers?"
    • "What accounting packages do you support?" 
2. Data Reliability
  • Why it’s important: Standardized data reduces formatting time and errors, speeding up the audit process.
  • What to expect: Consistent data provision across packages with a single common data model.
  • Questions to ask:
    • "Do all packages have the same data outputs?"
    • "Is the data output consistent across ERPs?"
3. Modern Technology Stack
  • Why it’s important: Seamless integration with other tools, future-proofs your tech investments.
  • What to expect: Cloud-based solutions with frequent upgrades and API enablement.
  • Questions to ask:
    • "How do you perform the data extraction?" 
    • "How can I integrate the data into my existing tech stack?"
4. Ease of Implementation
  • Why it’s important: Rapid deployment and scalability across client portfolios.
  • What to expect: Low-code/no-code setup with a single, one-off configuration for all ERP connections.
  • Questions to ask:
    • "How quickly can it go live?"
    • "How long does it take to add a new accounting package or connector?" 
5. User-Friendliness
  • Why it’s important: Improved client relationships and reduced troubleshooting time for customers and greater job satisfaction for your team.
  • What to expect: Simple customer data sharing, with the option to white label for a seamless journey, and dedicated support when needed. Your team also needs access to well-designed data displays in order to easily assess data and identify anomalies.
  • Questions to ask:
    • "What does the customer journey look like?"
    • "What happens if something goes wrong?"
    • “How do I assess the quality of the data?” 

 

The ripple effect: How quality data extraction transforms the audit process

The right accounting data extraction tool doesn't just streamline one aspect of auditing; it creates a ripple effect that transforms the entire audit process from planning to reporting. 

Audit Planning
  • Easy data requests via a simple client journey
  • Initial upload provides first look at client's financial year
  • Top-level analytics enable more strategic planning sessions
Audit Execution
  • Standardized data saves time for General Ledger (GL), Accounts Receivables (AR) & Accounts Payables (AP) testing
  • Multiple GL report formats allow easy comparison and analysis
  • AR & AP provides necessary schedules in minutes: control, detailed aging, and movement
Audit Reporting
  • Auto-generation of the most common workpapers
  • Standardized workpapers across all engagements – regardless of accounting system
  • Consistent GL and TB reports for every client 
Third-Party Tool Integration
  • One-time integration setup
  • Improved efficiency with consistent data formats by eliminating silos 

 

The foundation for AI and automation: Everything starts with data

As auditing firms look to implement AI, machine learning, and automation within their audit processes, the importance of quality data cannot be overstated. AI systems rely heavily on data for training and decision-making, making high-quality, reliable, and complete data crucial for accurate models. Poor or biased data can lead to inaccurate or biased AI models, potentially compromising audit integrity.

Common data issues that firms need to address include incomplete data, inconsistent data formats, and data errors and outliers. By implementing tools that provide standardized, high-quality data from clients and ensuring rigorous testing of AI model outputs, firms can lay a solid foundation for advanced analytics and automation.

 

Conclusion: Elevate your audit practice with superior data extraction

By choosing the right accounting data extraction tool, auditing firms can dramatically improve efficiency, accuracy, and client satisfaction. As you evaluate providers, focus on data depth, reliability, modern technology, ease of implementation, and user-friendliness. Remember, not all tools are created equal – and the right choice can transform your audit practice for the better.

The future of auditing is data-driven, and it starts with superior data extraction. By embracing these technologies, your firm can stay competitive and deliver enhanced value to your clients. Validis is one such provider, and their award-winning solution is built to power other market-leading technologies, such as Alteryx, DAS, Datasnipper, Suralink, Trullion and Valid8 (to name a few). Reach out to the Validis team to find out how they’re helping over 100 leading Audit firms (including 15 of the largest) transform their processes.

 

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