From data to decisions: empowering insurers through data intelligence

Data is the lifeblood of capital markets - but for many buy-side institutions, especially insurers, the journey from data to action remains manual and slow. In one recent project, Elenjical encountered a familiar problem: qualified professionals at a leading South African insurance company were spending up to three hours each morning assembling Excel-based risk and P&L reports.

“These were experts whose time should be spent analysing risk, not stitching together spreadsheets,” says Bella Berti, Senior Consultant at Elenjical. “They were doing vital reporting, but the process was slow, inconsistent, and rooted in legacy systems.”

What emerged from the project was more than a report - it was a platform: one that replaced flat, tabular outputs with dynamic visualisations, one that aligned trading and risk functions, and one that cut the time spent on daily reporting.

The client had approached Elenjical to replace their outdated process with an automated solution, built around existing infrastructure and presented through an intuitive Power BI dashboard. The brief: deliver a consolidated, enterprise-grade view of market, credit, and liquidity risk and P&L-scalable from analyst level to C-suite. But the challenge wasn’t only technical. It was cultural, structural, and tied to how data was handled across the organisation.

“We had to understand how the existing reports were built,” says Analyst Jade Penning. “Processes had evolved organically, and some of the original rationale had been lost. Our role was to untangle that complexity and translate it into something cleaner and more robust.”

Why insurers struggle with reporting

The insurance industry sits at the intersection of long-term investment and short-term risk sensitivity. Unlike many sell-side institutions, insurers often operate with lean teams and legacy-heavy infrastructure-factors that hinder digital transformation.

“Manual reporting is still extremely common,” says Berti. “Even when the appetite for automation exists, teams are stretched. They don’t have the bandwidth to step back and rearchitect their reporting approach-so the status quo continues.”

This is where external expertise becomes critical. Elenjical’s role was not only to build a dashboard, but to create a long-term, scalable data model that brought coherence across departments and surfaced insight teams did not have before.

“Using Python and SQL, we extracted and transformed data from multiple sources to create a clean, structured model behind the scenes,” says Penning. “With the right data foundation in place, we were able to fully leverage Power BI’s capabilities-delivering fast, meaningful insight through a dynamic and intuitive front-end.”

Why one source of truth matters

A core issue was the absence of a unified data source. Different teams were pulling from different systems, leading to discrepancies in reported figures. “One team would show a certain exposure,” says Berti, “but another would have something different-because they were referencing different versions of the same data.”

To solve this, Elenjical built a centralised data model to serve all relevant departments. That meant deep stakeholder engagement, careful architectural planning, and a forward-thinking approach to scalability. “You can’t build a model for just five users and expect it to scale,” says Penning. “We designed it so future teams could plug in without starting from scratch.”

The project ran over six months from start to finish, reflecting the complexity of the challenge and the ambition of the solution. The result: a report that runs automatically each morning, accessible across the business, and flexible enough to evolve.

Dispelling the Power BI myth

One takeaway from the project was how misleading BI tool marketing can be. “There’s a perception that Power BI is user-friendly out of the box,” Berti notes. “But when you’re dealing with capital markets data-complex, multi-dimensional, and high-stakes-you need specialists.”

Insurers, in particular, must balance actuarial insight, investment strategy, compliance, and internal risk frameworks. A simple drag-and-drop solution won’t suffice. “Without the right data structure underneath,” says Penning, “the front-end is meaningless. Once we restructured the model, the visualisation came to life-teams could compare data points they’d never seen side by side before.”

The ROI of automation

The transformation wasn’t only technical or visual. The time savings were immediate: reports that once took three hours now appear each morning. That time gets reinvested into analysis and decision-making. “This is the real value,” says Berti. “You’re not just speeding up reporting. You’re giving your smartest people more time to think.”

A message to the industry

Manual reporting isn’t only inefficient-it’s a waste of talent. And for insurers, the opportunity cost of delaying investment in data intelligence keeps growing. “Every firm should have a five- to ten-year data strategy,” says Berti. “Whether you take it department by department or tackle it company-wide, the key is to build solid architecture and commit to change.”

In a world of escalating regulatory pressure and exploding data volumes, that change is no longer optional. Automation isn’t only about efficiency-it’s about enabling better decisions, faster. At Elenjical, that’s what data intelligence means.

Original Article posted: AfricaBusinessOnline & Financial Fortune