In fintech lending, automated decision-making and underwriting logic have been essential tools for years. But the way leaders make decisions has evolved for the better. Today, experience and expertise are coupled with data-driven insights that either confirm or challenge traditional thinking.
While “big data” seems to dominate the headlines of tech publications, I think data democratisation is just as important. This approach makes large datasets accessible to everyone, turning raw numbers into insights that help businesses make better decisions. It allows teams across an organisation to act on data instead of relying solely on specialists to interpret it.
Turning insights into impact
For many people, raw data can feel intimidating. When it comes to decision-making, the trick is to simplify it into something digestible.
There are several ways you can do this. At Fleximize, we started by focusing on the basics. We created visual tools to show key metrics, like loan performance, and spot outliers. These tools helped our teams understand trends and make data-driven decisions with confidence. Over time, we developed a full reporting system that provides real-time insights in a way everyone can use.
For example, our dashboards show seasonal repayment patterns and trends linked to the economy. This allows us to adjust lending strategies before issues arise. Similarly, by spotting unusual patterns in applications, we can detect fraud early, protecting both our business and our customers.
Put the power in everyone’s hands
Traditional reporting methods often fall short in fast-paced industries like fintech. Static reports, built to answer specific questions, can’t keep up with the evolving needs of leadership.
To fix this, we built a flexible reporting tool. It lets users create their own reports in minutes – no developers required. The tool works quickly by using indexed tables so teams can explore trends, find issues, and act fast.
For example, if a business leader asks why conversion rates have suddenly dropped, the tool helps teams quickly investigate. Is it due to changing customer demographics, operational issues, or external factors? By answering these questions quickly, the right solution is often just a few clicks away.
Our tool also encourages experimentation. Marketing teams can see how campaigns affect application volumes, while operations teams can spot and fix bottlenecks. This kind of collaboration embeds data-driven decision-making into daily operations.
A roadmap to data democratisation
Making data accessible doesn’t happen overnight. Based on my experience, taking small, deliberate steps works best:
- Start with what you know
Begin with the common fields your business uses every day, like application statuses and key dates. Moving from static lists to dynamic dashboards can help your team see trends and get actionable insights right away.
- Make it transparent
Focus on the data that drives calculations, automated decisions, or algorithms in your processes. Unlike the “black box” model – where algorithms produce results without revealing how they work – making data visible ensures you can understand why automations produce certain outcomes and ensure they’re working as intended. Without this transparency, errors or biases can go unnoticed, leading to flawed decision-making.
- Value unstructured data
While structured data is important for automation, unstructured data provides context. For example, while a bank’s algorithm might answer “Does this customer have any CCJs?” with a yes or no response, unstructured data can help you understand the why. This can allow for more thoughtful decisions than algorithms alone might suggest.
- Take advantage of API integrations
APIs are powerful tools that often go underused as they can feel overwhelming. By mapping API responses into easy-to-read reports, businesses can create valuable resources.
- Visualise
Tables are useful, but visual tools like graphs can uncover trends that might go unnoticed in raw numbers. For example, tracking application trends over time can highlight seasonal changes or economic impacts. Visualising this data allows teams to act quickly.
Go forth and advocate
Even the best tools won’t work without team buy-in. Leaders must encourage a culture where data supports expertise, not replaces it. Regular training, open communication, and opportunities to experiment help teams become confident in using data tools.
At Fleximize, we’ve seen firsthand how empowering teams to explore data drives innovation. When employees see how their insights improve outcomes, it motivates them to keep learning and experimenting. From fine-tuning lending strategies to enhancing customer experiences, it allows us to work smarter and adapt faster. In a competitive industry, data democratisation isn’t just an advantage – it’s essential.
