An analyst, Ms. Esther Makandah, has come up with innovations which would help to prevent fraud in the healthcare system and these are through advanced Artificial Intelligence (AI) and analytics.

Esther is a seasoned analyst specializing in finance systems and advanced analytics, with a track record of applying data-driven innovations to enhance operational workflows and strategic decision-making.

With dual Master’s degrees in Applied Business Analytics and Business Administration (Data Analytics Concentration) from the University of West Georgia, Ms. Esther blends deep academic training with hands-on experience in automation,artificial intelligence,business intelligence and machine learning.

In Africa, healthcare and retail sectors face significant challenges from financial fraud, exacerbated by limited regulatory capacity, fragmented data systems, and constrained resources. Kenya alone loses billions annually to fraud in these sectors, threatening the sustainability of essential services.

Against this backdrop, Ms. Esther has developed an open-source project the AI-Powered Fraud Detection System in Retail and Healthcare, a software platform aimed at combating financial fraud by using advanced AI and analytics.

“My motivation for developing this system,” she explains, “stems from the urgent need to protect vulnerable sectors like healthcare and retail from financial losses, while promoting transparency and accountability. By harnessing advanced analytics and machine learning, the goal was to create tools that detect fraud and enable institutions to respond proactively.”

The system integrates cutting-edge technologies including machine learning, geospatial analytics, and natural language processing to deliver real-time fraud scoring, transaction visualization, and explainable AI outputs. This is particularly relevant in African contexts where digital infrastructure is often inconsistent and data is scattered across multiple sources, making fraud detection complex.

Ms. Esther highlights the platform’s focus on accessibility: “This platform was created with usability at its core. Whether for technical experts or frontline analysts, the interactive dashboards and AI-driven conversational assistants allow users with varying expertise to interpret complex data and make informed decisions quickly.”

The platform’s features from fraud heatmaps to case management and predictive analytics reflect a shift towards fraud prevention strategies that prioritize speed, transparency, and adaptability, qualities necessary for institutions working under constrained conditions.

Her professional background includes roles in financial analytics and automation. She has optimized reporting and workflows at Lowe’s Companies, Inc., and contributed to academic research on data-driven economics and performance excellence.

Ms. Esther has received multiple recognitions for her work, including several CEO and SVP awards and induction into the prestigious Beta Gamma Sigma honor society.

Looking ahead, Ms. Esther notes, “The AI-Powered Fraud Detection System is identifying emerging fraud patterns in real time, which helps reduce financial losses and strengthen regulatory oversight. Deploying such technology supports broader efforts to enhance digital resilience and rebuild public trust within healthcare and retail industries.”

In the context of Africa’s rapidly evolving digital landscape marked by both technological opportunity and systemic challenges Ms. Esther’s work represents an important effort to harness data science and AI for social and economic good. Her efforts in healthcare innovation and cybersecurity underline the potential of advanced analytics to improve resource allocation, reduce losses, and foster greater transparency in public services.

Her journey highlights the intersection of analytics, automation, and social impact in Africa. By developing AI-powered fraud prevention tools and promoting data-driven operational excellence, she contributes to the continent’s ongoing transformation toward smarter, more secure, and efficient healthcare systems.