ACCELERATE YOUR DATA SCIENCE AND AUTOMATION JOURNEY WITH NEXT GENERATION AI

/ By Bryan McLachlan, Managing Director: Africa at CyborgIntell /

Financial institutions (FIs) in Africa are turning towards artificial intelligence (AI) as a solution to some of the most urgent challenges they face in a volatile world. Whether it’s modelling insurance claims or credit card fraud, improving the customer experience to remain relevant in the face of digital competition, assessing creditworthiness or pricing insurance cover, AI is an enabler for better performance.

Most FIs struggle to achieve the full ROI they were hoping for and that it is significantly more difficult than anticipated. Across industries, AI initiatives are expensive and complex projects that take three to six months to complete, with an 85% failure rate. Lack of talent and time are perhaps two reasons FIs find AI success more elusive than expected.

Building a team that spans the data science/machine learning (DSML) lifecycle is expensive and difficult. The time generally taken in developing, deploying and operationalising machine learning (ML) models often mean the data that an AI system was trained on is out of date before it’s ready for deployment. Since FIs operate in a highly regulated sector, issues of risk, trust and governance are high on the agenda. FIs need to be able to explain how an algorithm decides someone is a fraud risk or why a loan application was refused. They need to be able to assess and mitigate the risk of AI failure, plus have a governance framework to regulate development, deployment, monitoring, and managing of models.

Somewhat ironically, the common factor behind so many of these challenges is that so little of the work that goes into building an AI system is automated. From data selection and modelling, operationalising AI to managing risk and governance, AI projects still depend heavily on slow, repetitive, manual work done by scarce talent.

This trend is changing fast with our next-generation approach to AI, which offers a one-stop, zero-code solution for rapidly developing, deploying and operationalising AI applications at scale. This approach slices the time to deploying AI projects from between two to six weeks, while helping to reduce risks and enhance ROI.

Our solution reduces the time required to develop accurate, production-ready models to a few hours without writing any code. The scalable AI platform can address a variety of use cases for every enterprise in various industries. Furthermore, it enables FIs to interpret, explain, and trust ML models. It understands, mitigates bias, and continuously improves performance, ensuring AI adoption.

The components of our solution include:

iTuring Open Data Accelerator (ODA), which processes, collates and cleans data from diverse datasets, leveraging more than 7000 pre-configured data features and feature store;

iTuring AutoML+, a fully automated ML platform to build and test best-in-class machine learning models;

iTuring MLOps for automating the deployment of ML models;

iTuring MRM for automating model lifecycle management, model control, process and technology risk management, and risk classification and governance; and

iTuring Decision AI to enable frontline workers to augment ML predictions with feedback based on the business realities and combine predictions of several AI models.