EQ Data Extraction Is The Future

Is Your Data Strategy Leaving You Behind The Pack?

17 June 2021

In this article Mark Watkins, Director at EQ Riskfactor, discusses how the receivables finance industry must quickly improve its approach to data extraction and its wider use during the lending cycle.

Within receivables finance, many are seeing the benefits of data extraction. As part of the onboarding process, it is essential to carry out a thorough assessment of each prospect. Traditionally this can be a time consuming process and a burden for the prospect. Data extraction can ease the process and benefit both prospect and lender. It helps make the onboarding and ‘in-life’ management (of prospects and existing clients) more efficient, more accurate, and more transparent.

What Information Is Available To Lenders?

A wide range of data is available for lenders from a variety of sources, such as:

  • Financial data – balance sheet information, P&L data, calculated ratios.
  • Open Banking – bank statement data/ transaction level detail.
  • Debtor, creditor, and item level transactional data.
  • Credit Reference data.
  • Nominal activity and audit trail data, from entity account packages.
  • Financial health information about the company.

Benefit 1 - Speed of onboarding

Prospective clients consistently advise us that speed of decision (followed by advance level and cost) is the primary driver in deciding which lender they select. Data extraction is the number one tool to speed up the onboarding process and helps the lender to make faster decisions. This results in a better outcome for the new customer and the lender can gain a competitive advantage in the market. Lenders using data extraction for credit decision-making are in a strong position from the outset. Why? They have the potential to develop positive relationships with their client base.

The lender receives more accurate and in-depth information from the start of the relationship and the prospect achieves the same reward with less effort. 

Traditional Receivables Finance Lenders utilising data extraction will be able to compete with the more agile Fintech players coming into the market.

Benefit 2 - Improved Customer/Prospect Experience

Data extraction lets the customer/prospect be in control and feel empowered. With push technology, the prospect can steer and set the pace for the onboarding process. This makes it a less intrusive and disruptive process than before.

Building on this, there is opportunity in improving the link between relationship management and customer experience. In conjunction with using EQ Riskfactor, lenders can pro-actively identify clients with tight cash cycles. The relationship manager can then quickly pre-approve facility uplifts.

What’s great is that customers and prospects benefit from quicker response times on funding requirements and the lender has greater visibility for a swift approval process. In addition, internal costs of manually operating a receivables finance facility, are eliminated or reduced.

Benefit 3 - Data Accuracy And Transparency

Data accuracy is a key benefit to extraction. When data is fed directly from a borrower’s accounting package, human error is reduced and data accuracy is improved. Acceptance and use of data extraction lets the borrower access a wider range of lending products, whilst the lender is more confident as they have a thorough picture of the borrower’s financial health.

Extracting data into a ‘single source of truth’ system, such as EQ Riskfactor, can help explore this data further to make informed decisions. For example, EQ Riskfactor gives historical trend analysis, consistent template version control, and drives a proactive risk-based approach across the facility and lender’s portfolio.

Benefit 4 - Reduce Customer Acquisition Cost

Data extraction reduces the overall cost of gaining customers. How? With faster decisions and less manual processing. This all helps to reduce the cycle time; from first meeting, through onboarding, to ongoing monitoring and control of facilities. It will also help you get to a decline conclusion (where appropriate) more quickly reducing the less frequently tracked measure of ‘cost per decline’.

Building on the lender’s needs of ongoing risk monitoring, resource is utilised more effectively and efficiently across portfolio monitoring requirements. If using EQ Riskfactor, lenders can even view prospects as if they were a customer; creating a full historical risk analysis and gaining expected benchmarking data of key measures.

This additional data lets lenders target prospects who are most likely to meet their criteria and credit profile. With the extracted data, it also provides comfort to lenders in providing facilities to higher-risk clients. This enhanced data analysis is available from the start; to help set correct operational and risk conditions throughout.

Contact Our Expert Team

To find out more about data extraction and EQ Riskfactor, please contact us. We are here to answer any questions and demonstrate the software.

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