There is hardly any industry that has been making such consistent use of Machine Learning services as the financial services sector. High volumes of data & historical records, strict requirement of security, etc., make machine learning the perfect technology for this sector.
Today Machine Learning companies are helping businesses in the financial service market create algorithms for scrutinising and approving loans, detecting frauds, risk assessment, etc., to name only a few. And perhaps this is the reason why this technology has been gaining traction in this market rapidly so much so that Gartner predicts that “25 percent of customer service operations will use virtual customer assistants by 2020.”
Let’s see how it is becoming an enabler for financial services.
How Machine Learning Services Enable Better Financial Services
Sales and Marketing
As customer behaviour evolves by the day, ML in financial services becomes more important than ever. As it helps mimic customer behaviour and offer them solutions that are tailor-made as per their requirements, it drives marketing campaigns in an intelligent and informed manner through social media bots, email automation, and the like.
Customer service, as a part of after sale service, benefits immensely from machine learning in the form of bots that cater to customers in a very convenient and successful manner without casting more burden on the limited skilled human resources.
Security and Compliance
The financial industry, besides healthcare and IT industries, is perhaps one among those which need to adhere strictly to security and data privacy compliance. Machine Learning companies can help detect fraud at very early stages, thus providing a force that makes the industry a secure place and also helps them comply with national and international regulations for data privacy.
Risk Assessment and Fraud Detection
ML has the ability to learn volumes from large sets of data and then establish correlations and patterns within that data. This is what enables ML in the banking sector to assess risk, detect frauds & money laundering, and even better trading as well as customer service. It does all that by way of real-time insights, based on which it can make the best recommendations for well-informed decisions.
Machine Learning services coupled with Artificial Intelligence helps banks and financial services providers to assess the profiles of their clients for risk. In the absence of such technologies, assessments were made on limited data sets since even if the data was there, there were inadequate means to sift and analyse this large pool of data. Machine learning algorithms can read this data better and create risk models, based on which profiles are assessed.
This technology can also detect fraudulent activity like money laundering and payment thefts. The odds of transactional theft can be substantially reduced through ML. With the availability of large volumes of customer data, financial firms are able to train AI neural networks to detect abnormalities in transaction patterns. Any unusual behavior is flagged as suspicious and the risk of frauds and breaches is diminished.
ML in financial services is a concept that is growing day by and is only expected to keep increasing in the future, near and far. It is only a wise call to be open to it.