A strategic approach to cost reduction for banks and fintechs

 As we enter a downturn, credit providers are confronted by a landscape that looks and feels very different from before. The real risk of global and national recessions means that net interest margins are wafer-thin.

At the same time business as usual (BAU) costs are unusually high for banks and fintechs.

From IT investments to the cost of utilities – credit providers must respond to the steady rise in operating costs.

In short, many traditional and non-traditional players face the challenge of thriving in an uncertain environment with shrinking margins, increasing competition, and demanding consumers.

This makes it even more imperative to bring costs down. 

The search for significant savings 

Given how difficult it will be to increase revenue in the current environment, the real opportunities for improving margins lie in cost reduction. 

There are many factors increasing operating costs right now, from an expected higher level of arrears and collections to increased multi-sourcing of suppliers and higher fraud costs. 

If firms increase automation and digitisation they may be able to offset some of these increases. But these savings may not be sufficient to cover the cost increases elsewhere.

That’s why we expect firms to be looking for significant cost savings. 💰

“Significant strides had already been made by many financial institutions with cost optimisation – but the downturn has now shifted the game and significantly raised the requirement.” 

Essentially, everything will be under review: people, property, technology, and external services.

But how can lenders take a strategic approach to cost reduction? 

One little-known quick win is your purchased data. 

In short, you can make huge savings by negotiating the right price and the right contracts for data from the credit bureaux.

Additionally, firms now need contracts with more flexibility to allow them to fill gaps in credit data to ensure they’re not paying more than their competitors for the same products. 

To become more innovative, credit risk teams are looking to partner with credit bureaus that offer transparency and the best available data at the best price for credit risk and affordability assessments, ensuring they are competitive in the market.

And this is where data benchmarking comes in. 

What is data benchmarking? 

Put simply, benchmarking is the process of evaluating something in comparison with a standard measure (a benchmark). 

It’s made up of three elements: the metric, the benchmark value and the comparison group.

Essentially, this provides a way for credit risk and procurement teams to find the best terms for their organisation, measured against industry peers.

And, it can save hundreds of thousands of pounds.

On average, benchmarking delivers an additional 25-50% of savings compared to an RFP approach or a simple renewal negotiation. 

Benchmarking will compare the pricing being offered by the same provider to customers with a similar footprint, as well as a competitive view. 

This process is much quicker and less resource intensive – plus, the fully transparent and data-based comparisons allow for better results.

Moreover, if you couple the price comparison results of data benchmarking with data quality assessment, you can input the best data available for credit risk programmes, helping to plug gaps in credit data information.

Combined, you can reduce costs, improve business efficiencies – and make more informed credit risk assessments.

You might be wondering that this all sounds great, but what is the impact?

The impact of data benchmarking

In short, data benchmarking can provide a 25-50% reduction in costs for an organisation, increased volume allowances, improved commercial terms and stronger client-vendor relationships. 

All of these elements help procurement teams to add value for the credit risk team and the organisation as a whole.

Whether for credit risk or procurement teams, developing a full understanding of performance, price, and accuracy is crucial and benchmarking is an integral part of this process. 

This comprehensive analysis allows teams to see how they measure up and use the information to achieve fair pricing and access to the correct data.

Wrap up

With margins set to be squeezed, bad debt provisions rising, and cost bases enlarged – nothing should be off the table. 

The current macroeconomic climate has created an opportunity to re-engineer contracts and data supply – bold thinking is needed. 

There must be absolute clarity on data costs. You can start achieving this clarity through data benchmarking – it can make at least 25-50% difference. Move on to embedding contract flexibility afterwards.