With a raft of SME data now available, the challenge is in being able to access it quickly and efficiently to make it fit for purpose
In our last blog, we talked about the lending journeys experienced by both small businesses and the lenders they rely on. With the advent of digitalisation and a proliferation of accounting software solutions flooding the market, lenders now have a raft of data available to them that can help them meet demand and minimise risk.
But in an increasingly competitive landscape and with time an important factor for businesses looking for loans, how can lenders best utilise this data to make fast, accurate decisions?
Data strategy is an important consideration. Lenders will need to assess the digital efficiency gain in extracting different types of data. They will also need to be able to manage the collection and analysis of that data and find a way of integrating it seamlessly into their workflow.
Increasingly, the challenge is around pushing the boundaries of automation and achieving an effective balance between technical solutions and human underwriting processes, while maintaining and building a physical relationship that engenders trust.
In this blog, we will look at the different types of SME data that is typically available to lenders, and the ways they can use that data to make optimised lending decisions.
Traditional data
Banks and other lenders have traditionally used core data-sets to establish the credit risk of a small or medium sized business. This data is widely accepted to provide an accurate snap-shot of an organisation’s financial viability.
These traditional data-sets include:
- Credit data (loans and suppliers)
- Company descriptions
- Financial statements
- Collateral and guarantees
- Owners and director details
- Late payment history
Retrieving and analysing this data requires a relatively low level of automation, meaning credit risk teams can make informed decisions without forensic examinations. But small businesses can be complex and unpredictable – particularly in their first few years of operation and relying solely on this high-level data can be problematic.
Often, extra levels of granularity can bring clearer insight into the true financial health of a small business, and it is worth exploring ways of gaining access to additional data that can provide more clarity.
‘New’ data and the importance of management accounts
Most SMEs have an online footprint that can add colour to their financial performance. User reviews, social media sentiment and digital journey data can all be used by lenders to identify their long-term viability.
And with open banking now available, it has also become possible to drill down into transactional data to get a definitive view of your prospective client’s income and expenditure.
But, in isolation, open banking data only tells part of the story. The real value is often found in a business’s management accounts.
Useful management account data-sets include:
- P&L
- Balance sheet
- Creditors debtors
- Cash flow
- Bank transactions
This comprehensive, granular view of a company’s financial health has been under-utilised by lenders in the past due to automation issues. Often, they have had to use manual processes to access it, which has prohibitively increased the cost of service.
However, if you can succeed in automating the extraction and analysis of management account data, it will add several extra layers to the picture.
Benefits of using management accounts in lending decisions
A company’s management accounts can actually provide vital context to open banking data. Instead of just seeing cash flowing in and out of the business, you will be able to build detailed profiles of an SME’s client base or uncover inconsistencies in payment structures or book-keeping.
There is an important transparency element, too, which can create a streamlined journey for the client and help to build trust in the relationship. With a clearer view of their financial position, you can tailor additional solutions for the customer and drive greater engagement and loyalty.
The ultimate goal for most lenders – particularly with their SME clients – is to improve their capital allocation. Access to management accounts data helps them do that, and it has the added value of helping them understand their clients better and make more informed lending decisions.
Automation the ultimate goal for lenders
While the end goal is to be able to fully automate the credit risk process and be able to make instant, data-led decisions, currently the vast majority of lenders still use human quality assurance at the end of the process.
That is probably a situation most lenders are keen to preserve, so the key is to able to support this human element with fast, automated data access, thereby improving insights and reducing the cost of service of their high-volume, low-value SME client base.
Ultimately, by extracting the right information – and utilising both open banking and management accounts data-sets – lenders will be able to maximise confidence in their credit risk function and maintain a real-time view of their clients’ financial health.
Intelligent accounting integrations
Validis has developed a comprehensive suite of intelligent accounting integrations that help lenders access the right financial data in real-time when making a loan decision.
Get in touch if you are currently reviewing your digital lending strategy and considering what data points you need to optimise your lending process.
