Nuance of Consumption of Data for SME Lenders in the UK

Small and Medium Enterprises (SMEs) form the backbone of the UK economy, contributing significantly to employment and economic growth. However, SME lending has historically been a challenging sector for financial institutions due to the diverse risk profiles and limited financial history of many small businesses. With the evolution of data-driven decision-making, SME lenders are now leveraging various forms of data to streamline underwriting processes, assess creditworthiness, and enhance their risk management frameworks.

This blog explores how SME lenders in the UK consume data, the different types of data they rely on, the alternative and emerging data sources being used by the lenders today and how this is changing the SME Lending landscape today.

The Shift to Data-Driven Lending

Traditionally, SME lending decisions were largely based on manual assessments of financial statements, collateral, and business owner experience. While these factors remain important, the rise of digitisation of finance has introduced new data sources that offer deeper insights into an SME’s financial health and repayment ability.

Sources of Data Consumed by SME Lenders traditionally

Traditionally, SME lenders have relied on multiple data sources to enhance their decision making. Below are the key types of data they consume:

1. Traditional and Credit Bureau Data

Traditional data remain a core component of SME lending decisions which includes balance sheets, bank statements, management accounts, and cash flow statements to determine an SME’s financial stability. In addition, credit bureau reports from agencies like Experian, Equifax, and TransUnion provide insights into the credit history, past repayment behaviour, and existing financial obligations.

2. Data from Open Banking

With Open Banking regulations enabling businesses to share their banking data securely, SME lenders can now access real-time transaction histories, income patterns, and cash flow trends. This data helps lenders assess a business’s financial health beyond static financial statements offering a dynamic view of income and expenditure trends.

3. Data Sources from Government and other documents

• • Government records (Companies House): Companies House provides key business information that helps lenders assess an SME’s financial health and stability. Financial statements reveal profitability and liquidity, while director and shareholder details offer insights into governance. Lenders also review charges, liabilities, and insolvency records to gauge existing financial obligations and potential risks. Frequent director changes or dissolution warnings can signal instability, making this data a useful supplement to traditional credit assessments.
• • Supply chain and trade data: : Information on supplier payments, invoice records, and procurement transactions can indicate the financial strength of an SME.

4. Income and employment verification

Requesting payslips to assess borrowers’ income stability. Payroll information like regular wage payments indicates stability in business. For example, work report by many credit bureaus provides digital employment and income verification service for lenders.

Alternative and emerging sources of data being used today

We see that the lending landscape today is more risk-averse and more digital and lenders want faster, dynamic and forward-looking indicators – not just historical data. So, some of the new data sources being used by lenders frequently these days are as follows:

1. Digital and Payment Data

• SMEs are increasingly using digital payment platforms like, POS, e-commerce platforms to analyse transaction data for insights on revenue streams, customer demographics and seasonality in business performance

2. Social media and online presence

• This is growing in relevance for micro-SMEs and sole traders

• Lenders may check consumer engagement or sentiment for new-age business. They may check sites like Trustpilot, Feefo to gauge consumer sentiments

3. ESG and Sustainability disclosures

• Increasing relevance due to regulatory pressure and stakeholder interest. Lenders are looking at carbon emissions, energy consumption

• Some lenders are beginning to incorporate ESG scores in their decisioning models

4. Cloud accounting software

• This can give access to invoice, payroll, expense categorisation and VAT data

5. Supplementary data points

• Supplementary data points include court judgements, insolvency information, sales data, number of full-time employees and regular contractors

Importance of Alternative and emerging data sources

Combined with traditional forms of data, the newer forms of data will help lenders in:

• 1. Real-time visibility: Alternate and emerging data sources like digital and payment data offer up to date financial insights, enabling faster and more accurate lending decisions.
• 2. Enhanced risk assessment: : Lenders can gain deep understanding of SMEs financial health by analysing dynamic and contextual data like categorised transactions beyond credit reports
• 3. Expanded Inclusion: : SMEs like sole traders and ecommerce can be assessed fairly and this can improve their access to credit
• 4. Support for automation and scale: Rich, structured data feeds AI-driven underwriting models, allowing lenders to automate decisions and serve more SMEs efficiently

A changing SME lending landscape

According Centre for Finance Innovation and Technology-SME-Finance-Taskforce report the SME lending ecosystem is undergoing a major shift. Several key trends are shaping up this transformation:

• 1. Rise of Smart Data: : Beyond Open Banking, there is growing momentum around Smart Data which is the ability to securely share broader datasets (e.g., cloud accounting, VAT returns, Companies House records) with lenders, with SME consent.
• 2. Aggregator and Marketplace Models: Lenders increasingly rely on data aggregators to pull and structure data from multiple sources, allowing them to automate underwriting and scale faster. In parallel, marketplace models are gaining traction, enabling SMEs to share data once and receive multiple loan offers.
• 3. APIs and Digital Infrastructure: : Lenders are shifting towards real-time API integrations across accounting platforms, CRAs, and government data sources (e.g., HMRC, Companies House) to streamline affordability analysis and reduce fraud.
• 4. Data Verification Is Now Key: It's no longer just about having data verified, machine-readable, and standardized data is becoming essential for automation and to reduce processing friction.

What does this mean for UK SMEs

The shifts in SME lending landscape will have significant implications SMEs in UK. As the lending ecosystem becomes more data-driven and digitally connected, UK SMEs stand to benefit from faster, more transparent, and more inclusive access to finance. By embracing digital tools such as cloud accounting, Open Banking, and e-invoicing, SMEs can reduce the administrative burden of loan applications and improve their chances of approval. The shift enables more tailored and competitive lending offers, especially for smaller or digitally native businesses, while encouraging a broader base of SMEs to participate in the formal credit markets.

Conclusion

UK SME lending is evolving from slow, paperwork led processes to real-time, API driven decisioning powered by various data sources. From open banking to ESG metrics and social media, lenders are moving beyond static documents, to more holistic and inclusive approach. Centre for Finance Innovation and Technology-SME-Finance-Taskforce report highlighted in their report that enhancing accessibility of data by moving to more up-to-date digital format and verification using alternative sources could lead to greater levels of automation making it easier for SMEs to go through loan application, and lead to better decision by the lenders.

The future of SME lending holds immense potential for more inclusive and efficient lending models, ultimately fostering the growth and success of UK SMEs.

Author: Akshat Dev, Partnership Development Strategy at Digilytics AI

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