Fraud detection stands as one of the most pivotal challenges within the financial sector, where the rapid evolution of technology both facilitates new methods of committing fraud and, fortunately, new strategies to combat it.
In our latest case study, we delve into how our AI consulting company harnessed the power of machine learning to not only identify but also predict fraudulent transactions, setting a new benchmark in security and trust for our clients.
This journey into the realm of AI-driven fraud detection reveals the significant impact of advanced analytics and machine learning algorithms in safeguarding assets and enhancing operational integrity.
The approach
Our client was a startup that wanted to create an AI fraud detection engine to provide it is a service to other companies.
Our approach was based on multiple steps.
We started off with an AI Roadmap. The goal of the AI roadmap was to identify the best possible ways forward, while understanding the different trade-offs.
The outcome the AI roadmap was twofold. First, we decided to go for a combination of outlier detection methods. The reason is that, due to the complexity of the problem, we felt that an ensemble approach would yield better results.
Secondly, we decided to use data augmentation to improve the dataset. We use a combination of statistical algorithms in order to enhance the dataset to a size, such that our algorithms could improve their performance.
All this led to the development of the fraud detection engine. The engine was based upon an ensemble model that combined machine learning and statistical techniques.
Deployment and real world testing
The engine was deployed in the real world and we ran a pilot test with a client. The client was a financial services company that was dealing with a large number of intermediaries, and they knew that fraud was a serious problem.
We worked closely with this client, in order to identify when the predictions of the AI engine were accurate and when they were not. We then went through subsequent rounds of multiple improvements in order to make sure the predictions match more closely with the ground truth.
The AI engine was successful in predicting some well known cases of fraud, but also discovering some new ones.
Our client is now working on raising another investment round based upon the success of these efforts.
AI in Finance
Getting started with AI can be a daunting task for any company. That is why having a trusted ally that can help you succeed is the way to go.
This is what Tesseract Consulting and Advisory can do for you.
If you want to know more what we can do for your business, then make sure to get in touch. We specialise in delivering solutions in AI and data science, but also educating decision makers on topics such as data strategy and data maturity.
