Analytics and decisioning: How to climb the credit maturity curve

Many businesses still rely on manual credit assessment methods, often leading to sub-optimal decisions, missed opportunities and inconsistencies. Automated credit decisioning can be a way to address these issues, ultimately delivering more streamlined operations. 

Full automation can happen in one swift step or through a more gradual approach. Here's how you can climb the credit maturity curve using intelligent data analytics and decisioning.

Understanding automation and the credit maturity curve 

The credit maturity curve is a framework for helping finance teams understand and improve their credit risk management processes through automation. Climbing it means evolving from manual credit judgements to adopting advanced data processing and analytics.

Simply collecting data isn’t enough. The true value lies in how you manage, analyse and leverage it to evaluate customer risk profiles more effectively to gain a competitive edge.

Each decisioning stage is characterised by different levels of automation and integration with business processes. 

• Manual credit decisioning – uses manual underwriting teams, with decisions relying heavily on individual expertise. Processing times are slower, data is often fragmented, and errors can occur. 

• Partial automation – specific tasks are digitised, including customer onboarding with some reliance on credit scoring models. However, a good proportion of higher value tasks are still manual.

• Full automation – end-to-end credit evaluation processes leverage advanced analytics and AI. Initial set-up may be expensive but investment can and should be justified with a strong return on investment.  

As you move along the maturity curve, you can unlock increasingly sophisticated levels of data utilisation, from descriptive analytics based on past patterns of behaviour to prescriptive analytics that recommend actionable next steps. 

Benefits of climbing the maturity curve

• Operational efficiency – faster decisions, streamlined workflows, reduced manual tasks and training. 

• Cost savings – reduced labour costs and overheads, plus lower credit losses from human error.

• Optimised decision making – deploying champion and challenger strategies helps finance functions to test, learn and optimise credit decisions.

• Improved compliance – regulatory requirements automatically integrated into the decision-making process, ensuring legal compliance. 

• Better customer experience – fast, real-time credit decisions tailored to customer profiles. 

With each step, your credit strategy becomes more focused, adaptive and aligned with your business goals.

Why data is the foundation of digital finance transformation

Just as a house needs solid foundations, so does digital finance transformation – but with high-quality data rather than bricks and mortar. 

Yet many finance functions still rely on fragmented processes, outdated reporting cycles and high levels of manual work. Too many businesses are hampered by missing data, badly formatted data or a lack of data history altogether and may need to look at starting a project to transform credit risk operations.

A good first step toward maturity is data cleansing. This involves reviewing and removing inaccurate, incomplete or irrelevant data from your records. 

With tools like Dun & Bradstreet’s Master Data service, you can turn existing data into a valuable asset to drive performance across your organisation. Surfacing the right data means you’re no longer working in the dark and your credit decisions are supported by the most relevant insights.

Building a decisioning engine to climb the maturity curve

A credit decisioning engine that uses algorithms to assess a customer’s creditworthiness can help you make quicker and more accurate decisions. 

When implementing credit risk software into your tech stack, you have the option to buy a pre-built solution, build an in-house system or partner with a specialist vendor. The approach you choose will depend on several factors, including:

Budget

Look at ongoing costs, not just initial expenses. Consider whether maintenance and upgrades will be carried out internally or externally. And what would happen if your solution was no longer fit for purpose in a few years’ time?

Resources

Think about what resources you’ll need to complete the project, and whether you currently have the necessary skills for it in-house. If not, you’ll need to factor in training, recruitment and full-time employment costs. Could it be more cost-effective to outsource?

Time

How quickly do you want to get your decisioning engine off the ground? Pre-built platforms offer fast turnaround but may lack customisation. A bespoke build ensures flexibility but can delay the launch date, affecting ROI.

What climbing the maturity curve could look like for your business

To successfully climb the maturity curve, you first need to understand where you are on the curve and where you want to be. Ask yourself these questions:

• What is my main goal? (e.g. growth, customer satisfaction, cost reduction)

• What does it take to get to the next stage?

• How long will it take? (e.g. is it a one-year or a five-year plan?) 

• What resources do I have to get there? 

By having a clear idea of timelines and key objectives, you’ll be better placed to automate with a purpose. After learning how well new tools work it becomes easier to make a business case for rolling them out further. 

Once you’ve launched your day one credit strategy, it doesn’t stop there. Customer behaviour, market conditions and external pressures are continually changing, so you’ll be able to monitor your decisions and adapt to avoid significant credit losses. 

If you don’t want the stress of handling it yourself, our experts can provide tailored solutions through D&B Finance Analytics to help minimise bad debt and operational costs. 

Are you considering data analytics solutions to transform your credit decisioning processes? Get in touch with us today.

Solutions to accelerate your business

Credit Accelerate is built on a powerful back bone of Dun & Bradstreet solutions and platforms, designing to help you make smarter, faster credit decisions no matter your size of business or location.