Financial Services

Find out how the application of machine learning to transactional and alternative data sources is driving decision making in the financial sector.

Financial Services

Financial Services in the age of AI

Personal finance technology is becoming increasingly customer-oriented, mobile and real-time. Forecasting models, automatic recommendations and alert systems built using AI are creating huge value for disruptive challenger banks and personal finance apps. At ADSP, we use state of the art machine learning techniques to help financial institutions tackle challenges such as credit risk, portfolio optimisation and money laundering and deliver measurable impact on the bottom line.

Executive opinion

Is machine learning within the financial sector just 'forecasting'?

There is no question that machine learning based forecasting has already impacted decision making in finance, whether at a personal or business level. However, businesses should not view AI as a one-dimensional operator - machine learning can be used to solve a variety of problems centred on prediction and optimisation. How can we identify patterns in transactional data that indicate fraud or money-laundering? How can we maximise long-term term gain of an investment portfolio? These are the bold questions that AI can help us answer.

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David Foster
Founding Partner, ADSP

Financial Services

82% of enterprises adopting machine learning and AI report a positive ROI

Forbes

High value AI projects for Financial Services

Credit Risk

Assessing risk for credit applications is a long standing application of regression based models. We leverage recent advances in machine learning to build more powerful models that result in fewer false positives and greater insight into your customer base.

Intelligent Trading Systems

Algorithms have been orchestrating trading in the stock market for many years, but AI is now disrupting established methods by increasing the accuracy and robustness of predictive models. We leverage state of the art techniques from academia to train machine learning models that provide time-sensitive, accurate price predictions.

Fraud Detection

We leverage historical data and design automated systems that monitor transactions in real-time to anticipate and prevent fraud. Using state-of-the-art deep learning techniques, we reduce false alarms in your detection algorithms and improve customer experience without adverse effects on reliability and cost.

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