Drive efficiency in Financial Service

In financial services, data is the lifeblood that powers every decision. However the current landscape is riddled with challenges, most prominent among them being the lack of transparency in data pricing.

Opaque pricing models and disparate costs can throw a spanner in the most well-oiled procurement teams. But the significance of efficiency in this industry is paramount. 

Enter: Strategic data procurement. The process of comparing and measuring data against industry standards not only provides valuable insights but also pinpoints areas of improvement in data procurement.

Let’s take a closer look. 👇

The importance of data in Financial Services

High-quality data brings clarity, reduces risks, and ensures accurate decision-making. It is the difference between approving a credit request that will default and one that will bring in returns.

But every search and every data point procured carries a price tag. While the benefits are numerous, it’s essential to understand the importance of saving money on data and searches for improved efficiency. 

And that’s where strategic data procurement guided by data benchmarking steps in, providing a roadmap for cost-efficient, high-quality data acquisition.🗺️

Enter data benchmarking

Data benchmarking is a strategic process that compares your data procurement processes, cost, quality, and accuracy against industry standards and best practices. It’s not just about understanding where you stand. It’s about shining a light on the path forward
and providing actionable insights to elevate your strategies. And make significant savings.💸 

Given the sector’s reliance on data for credit decisions, regulatory compliance, and strategic planning, having a comprehensive understanding of how your data practices compare to industry peers is critical. 

It ensures you are not just keeping pace with the industry, but actively seeking to enhance your data practices.

Leveraging data benchmarking

Data benchmarking is not just about ensuring you are on par with industry standards. It’s a tool that can actively drive cost savings and improve data accuracy. It provides a granular understanding of data costs, shedding light on areas of overspending.
This enables you to negotiate better contracts with data bureaux, and ensures you get the best value for your investment. 

Improving data accuracy is another key reason to leverage data benchmarking. By comparing your data’s accuracy against industry norms, you can identify gaps in your data quality and take steps to solve them. This translates into better credit decisions,
risk assessments, and overall operational efficiency.

The importance of data accuracy was further underscored by the FCA’s credit information report, which highlighted discrepancies in data held between bureaux. These disparities can lead to inconsistencies in credit decisions and pose a substantial risk for
financial service providers. Data benchmarking can help identify such discrepancies and drive efforts towards ensuring data uniformity across different bureaux.

In a nutshell, data benchmarking isn’t just a measure of where you stand – it leads to improved efficiency, cost-effectiveness, and data accuracy in the financial services sector.

Nothing explains it better than real-life results. So let’s look at a real-life example to illustrate the power of data benchmarking.

Data benchmarking real-life results 

PurplePatch worked with a major player in the UK financial sector, which was grappling with escalating data procurement costs. Their lack of insight into market rates led to unnecessary expenditure and compromised data quality.

Upon implementing data benchmarking with PurplePatch’s expertise, they were able to analyse and compare their data procurement processes against the best in the industry. This gave the bank a clear understanding of their position relative to their peers
and an insight into areas where they were overspending or underspending.

This holistic benchmarking process identified several opportunities for cost-saving, including areas of duplicative data purchase and suboptimal contract terms with their data bureau. 

As a result, the bank managed to reduce its data procurement costs by a substantial 30% in the first year of implementation. Moreover, the benchmarking process brought to light gaps in their data quality, driving improvements in data accuracy and thereby
enhancing their credit decisioning process. 

The impact was substantial – fewer bad debts, improved regulatory compliance, and overall, a more efficient operation.

With this in mind, let’s take a look at how you can put this into practice too. 

Implementing data benchmarking in your organisation: A Step-by-Step Guide

Integrating data benchmarking into your organisation may seem daunting at first, but with the right approach, it can be seamlessly integrated into your existing processes. 

Here’s a step-by-step guide to implementing data benchmarking for data procurement in your organisation:

  1. Understand your current position: The first step in any benchmarking process is understanding where you stand currently. Specialist experts can analyse your data procurement processes, costs, quality, and accuracy in depth. This sheds light
    on any inefficiencies, discrepancies, or areas of improvement.

  2. Identify key metrics: Benchmarking is all about measuring performance. This is where firms identify the key metrics that are crucial to your data procurement process. These might include cost per data point, data accuracy, data completeness,
    and so on.

  3. Leverage industry standards: To compare your performance, you need to know what the industry standards or best practices are. Here, you need to leverage information about the average data costs, the expected data accuracy levels, and other
    relevant metrics in your industry.

  4. Compare and analyse: Next up, it’s time to compare your performance with the industry standards. This will give you a clear picture of where you stand and highlight areas where you are excelling or lagging.

  5. Identify opportunities for improvement: Data benchmarking isn’t just about knowing where you stand; it’s about identifying opportunities for improvement. You can use your comparison analysis to pinpoint areas where you can save costs or
    improve data quality.

  6. Implement changes: Based on your analysis, implement the necessary changes in your data procurement process. This might involve renegotiating contracts with data bureaux, investing in new data or technology, or refining your data procurement

  7. Monitor and adjust: Benchmarking is an ongoing process. After implementing changes, you should continuously monitor your performance and adjust your strategies as needed.

Remember, the goal of data benchmarking is to drive efficiency and cost-effectiveness in your data procurement process. 

However, if you’re going it alone, the process can be time-consuming and complex. 

Working with a data benchmarking expert can simplify this process and ensure accurate and useful results. We can help you understand your current position, provide insights into industry standards, and guide you in implementing effective improvements.

Armed with benchmarking, procurement teams can:

  • Renegotiate inflated contracts based on true market pricing

  • Pinpoint areas for improved data quality and coverage

  • Make informed investments aligned to business priorities

  • Develop competitive procurement strategies

Ultimately, benchmarking allows you to evolve procurement from a cost centre into a value driver. 



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This post originally appeared on TechToday.