How will Artificial Intelligence change the banking industry

  • Written By WHISHWORKS
  • 21/09/2018

WHISHWORKS’ Carlos Somohano discusses the changes AI will bring in the banking industry with Global Banking & Finance Review

Fraud prevention is one of the main areas that banks are investing in. Machine Learning (ML) and Deep Learning (DL), both offsprings of Artificial Intelligence, are being used to improve security by using algorithms to compare vast amounts of data from many different sources and assess the likelihood of a transaction being fraudulent. The difference with the non-AI solutions currently used, is that ML and DL programmes learn and adjust their algorithms according to past outcomes as well as the changing habits of the account owner, achieving higher levels of accuracy.

Graph Analytics is another very important development achieved thanks to AI and increasingly used for fraud prevention. With Graph Analytics banks can analyse data networks and identify activity or relations that may signify the existence of organised crime groups.

AI is also gaining momentum within risk and compliance. With the ever-tightening regulatory environment and directives like MiFID II and Dodd Frank that aim to increase market transparency and investor protection, banks are facing significant fines and reputational damages if they fail to provide evidence. In 2017 alone, these fines amounted to £230 million. AI-based solutions are being used to search and compare both historical and real time data to identify abnormal behaviours and transactions. This way AI solutions act as a prevention mechanism rather than their non-AI counterparts that search only through historical data to produce results after the fact.

Another area where we see increased application of AI solutions by banks is in customer service. Chat bots and conversational interfaces are increasingly used to facilitate the communication process and address simple customer enquiries, reducing customer waiting time to be served, whilst allowing more time for human advisors to deal with complex problems. Even when not used in the front-end of customer service, AI solutions can help financial advisors to make better, more personalised recommendations to customers by weighing previous account activities against current data, significantly reducing the risk of mis-selling.

There are many other tactical processes, where banks are introducing AI-based solutions to optimise processes and reduce risk. Some of the projects we have seen being implemented include Emotion Analytics for Claims Management, Prescriptive Analytics within Management Information Systems, Satellite Analytics for Construction and Property Finance, Document Summarisation for Legal Departments and many more.

Read the rest of the article here

If you would like to find out more about how Big Data and Machine Learning can help you be part of Digital Economy, give us a call at +44 (0)203 475 7980 or email us at

Other useful links:

Survey Report: The State of Big Data in the UK

Banking and The Internet of Things

Big Data Solutions & Services

Latest Insights

WHISHWORKS - MuleSoft API integration for Universities

API-led connectivity for Universities

An architectural approach to API-led connectivity that enables hybrid, multi-modal learning and teaching experiences for universities.

Salesforce FSC - Leads and Referrals

Salesforce FSC – Leads and Referrals

In this blog we look at how Leads and Referrals work in Financial Services Cloud and how they’d make sense within a banking environment.

evented APIs

What are evented APIs?

We can think of an evented APIs as the fabric that binds and integrates all the applications in an event-driven architecture.