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Machine Learning as a Service Enters Credit Risk

Machine Learning as a Service Enters the Financial Services and Credit Risk Sectors

The UK is one of the most advanced financial services in the world and business is booming. Across industries, machine learning has boosted productivity and service, yet the financial and credit risk services lag behind. Challenger banks and non-traditional payment sources are disrupting the status quo by ushering in a new era of machine learning.

For many industries, machine learning has arrived and it’s leading to big improvements in service and productivity. Though there is a growing trend to revolutionise technology in banking, many financial services organisations struggle to fill posts. It’s time to ask why and brace for financial decision-making with machine learning at its heart.

In the Age of Machines – A New Era of Robotic Relationships

Technology disruptors within the financial services industry face a two-fold balance of keeping to compliance while at the same time creating user-friendly applications. As business trends change, decision makers are faced with new challenges such as cyber security, fraud prevention, and how best to protect their consumers. Meanwhile, working to ensure greater affordability in an industry ripe with new entrants to the marketplace with technology platforms are the fore.

Virtual banking applications challenge traditional banking systems using AI and predictive analytics for a more refined scoring system. Their technology led endeavors help to automated processes and help to speed up their credit decisions for real-time decision making.

Though the benefits are obvious, financial services have been hesitant to move forward until they can be sure no issues will arise. So, to combat their concerns, businesses are redefining robotic relationships. Using emergent and collective problem solving to gain insights into their customer and the services they may require now and in the future.

In this new era, businesses are integrating humans, machines, and data on a large scale creating ‘social machines’. The intuitive balance and sometimes gut reactions of humans coupled with machines probability and risk to determine impact on a number of issues including, but not limited to, economics, financial, credit risk, and psychology. Machines are learning to learn.

How it Works – Machine Learning Fundamentals

At its most basic level, a machine’s function is to analyse data. In machine learning, it combines data analysis and the relationships that exist within it. This allows a business to know the best product or service at the right time to the right audience. Therefore, improving the customer service, satisfaction, and interaction for confident, repeat business.

However, by their nature, Risk Analysts and Credit Risk professionals are cautious and may be leery of allowing machines to make decisions on the behalf of humans. Yet, all the power to make it work is there -- to incorporate algorithms to probabilities to correct and real-time decisions in the most sensitive environments, such as banking, the direction of travel is fairly clear. In fact, a recent Accenture study, suggests 38% of banks plan to invest in machine learning extensively within the next three years.

Next Steps

Overcoming skepticism is a step to machine learning and realising it already exists in our everyday lives. Already, Amazon and Google have created machine learning systems to improve customer experience. And as machines process and figure out relationships via patterns and trends, services and experiences improve with it. Within credit risk, however, it’s important to include confidence and trust in data quality.

Maintaining confidence is a significant challenge yet to be overcome due to the vastness of scale when it comes to customer data within the financial services industry. However, methods have evolved to combat this issue such as maintaining web infrastructure.

In fact, with the advent of wireless systems, satellites, and mesh networks, web infrastructure offers greater ability to combat these challenges to build social machines which manage risk through transparency and wide engagement.

In a market ripe with opportunities, we’re now faced with an ever-increasing skills shortage within Credit Risk. Want to help bridge the gap? Then check out our current vacancies here.

You can also contact our UK Team at 0208 408 6070 or email to learn more.