Everyday fintech use cases for A.I.

fintech ai

By Noel Peatfield (@noelpeatfield )

Artificial Intelligence is becoming more commonly used in a variety of fintech applications. Not just in identification and authentication but also in communications and complex services like risk analysis and insurance claims. Our infographic highlights how often a financial services customer can interact with A.I. during everyday routines.

It is possible to encounter artificial intelligence in numerous ways while carrying out single tasks, such as using predictive text while talking to a virtual assistant that understands requests and connects with other third party platforms. While customers and employees enjoy increased convenience A.I. is also enabling bank grade security to protect our digital identities and finances.

To access secure accounts many organisations apply 2 factor logins using a password, pin or device with biometrics such as voice and facial recognition. Along with machine learning, artificial intelligence continually improves the speed and accuracy of biometric recognition. This is will become more common later this year when 3D secure becomes standardised in Europe with the arrival of the new SCA requirement in September.

Conversational A.I. applications such as chatbots are used for bank customers who prefer to ask for services rather than navigate fields and menus. They are being integrated into mainstream instant messengers that can direct users to buy now. Insurtech companies have found that A.I. chatbots can deliver end to end insurance enquires with claims being paid in seconds.

Machine learning and artificial intelligence rely on large data sets. Banks have transactional data of customers over years enabling them to offer hyper-targeted financial services using A.I powered recommendation engines. Customer behavioural data can be used to predict the future needs of customers and be able to offer them tailored services in real time including advice on how to spend and save their money.

Computer vision A.I. has advanced quickly in recent years and is now being used by insurance companies to automatically estimate property damage and repair costs from photographs. Using supervised learning with in some cases millions of photographs the range of objects to be assessed by computer vision will increase over time.

The user experience of leading B2C fintech platforms using A.I. offers simple, low friction interfaces while behind the scenes M.L. algorithms work tirelessly to deliver fast and personalised financial services. This growing ecosystem also includes companies that specialise in credit scoring, sentiment analysis and regulatory compliance.

In the future the long awaited arrival of 5G will mean that a lot of the heavy lifting of A.I. can be done on the user’s device rather than the cloud. This will improve latency times with faster responses and also deal with some of the security issues associated with sharing personal data with third parties. Edge computing using 5G will especially enhance the performance of mobile fintech apps that use machine learning and artificial¬† intelligence.

If you would like to know about how your financial organisation could harness the potential of artificial intelligence FINTECH Circle provides corporate accelerator programs, finance and innovation masterclasses. Subscribe to our newsletter to keep up to date with financial digital transformation. The future of finance is fintech. Are you prepared?