Financial Services

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Automating Risk Management

The management of risk has always been at the core of the financial services industry. Consequently machine learning algorithms are able to analyse customers’ transaction history to calculate highly accurate credit scores and set appropriate credit limits.

Fraud Detection

Financial services providers are expected to protect their customers’ assets, consequently fraud detection and prevention is very important. Machine learning techniques bring a lot of advantages to fraud detection. Detection and prevention activities, however, can be annoying to customers. As a result, algorithms that improve over time can only bring benefits. The algorithms seek to understand customer behaviour and hence are able to spot the unusual and, ultimately, the fraudulently unusual.

When trading in stocks or commodities these algorithms can help to spot patterns in the market data that point to illegal market manipulation.

Personalisation and Customer Engagement

Financial service providers look to raise their engagement with customers through highly personalised relationship management. Machine learning can help to predict customer needs and suggest personalised services based on spending history and other demographic data.

Frequently Asked Questions

Do you really make data speak?

Do we make data speak? Well, not literally of course! All data of a certain size has a story to tell. It will have trends, sudden movements, be able to show cause and effect interactions and perhaps explain human behaviour. It is not always easy to discover the stories that the data can tell, but we have over 20 years’ experience in doing exactly that. That is why we say, with confidence, that we make data speak.

If you would like to know some more then read about How JTA The Data Scientists does its work or have a look at some other FAQs.

You could also explore our case studies or whitepapers.

What is Data Science?

In 2012 the Harvard Business Review called it “The sexiest job of the 21st century”. Some claim that it is nothing more than a sexed-up term for statistics and so a lot of confusion reigns. We believe that Data Science is a merger of many traditional disciplines, bringing together statistics, processes, algorithms and machine learning. This means that it can have different interpretations but at its heart data science is the extraction of knowledge from data.

https://en.wikipedia.org/wiki/Data_science

If you would like to know some more then read about How JTA The Data Scientists does its work or have a look at some other FAQs.

You could also explore our case studies or whitepapers.

Related Case Studies

The Adoption of Telemetry

How we help a market research team to start analysing telemetry data and to get over the large cultural change needed to adopt big data.

A Data Science Architecture

This case study describes the architecture that we established for a client, wishing to get the most from the data. They had both internal and external data and they also wanted to marry insights from many different sources.

Our Latest Testimonials

The online solutions provided by JTA are very powerful and dynamic. Working with JTA is always a pleasure and a trouble-free experience. Consequently, our relationship with JTA is very collaborative. JTA always handles any challenges promptly and without stress.

Raymond Piombino, Founder, Bordeaux Consultants International

JTA can be trusted to get the job done right, on budget, and on time. I literally NEVER worry about errors when working with them – they are very thorough, has an excellent eye for details, and are pleasant to work with. I look forward to working with them again in the future.

Jim McDonell, Analyst

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