4 Ways Machine Learning Impacting the FinTech Industry

Modern and rapidly advancing technologies like artificial intelligence, big data analytics, machine learning and blockchain are progressing at impressive rates. More than anything, these technologies have contributed a great deal toward the advancement of the financial sector. Banking procedures have become shortened allowing them to focus on other more intellectually demanding tasks. Machine learning solutions have replaced the functions of entire departments. Whether it is customer services or fraud prevention through ID verification, AI has penetrated banking services completely.

On average, Google receives over 20 queries regarding the financial and banking sector. Developing advanced solutions for the finance industry is not the answer though; banks and financial institutes should be just as keen on transforming their structures digitally. AI and Machine learning is the perfect answer for banks to improve their procedures.

Removing Hurdles for Customers

Previously, client on boarding procedures have been lengthy. However, an increased amount of digitization has allowed banks to make their onboarding procedures faster and more efficient. Machine learning has contributed effectively to developing more efficient processes. Some of the steps that are adopted by banks for an enhanced customer focus include better personalization; a focus on customer values; a multi-channel approach to sales; being proactive rather than reactive; guiding users on every step of the way. Erica, the banking assistant app by Bank of America, is perhaps the best example of this. It is more like a personal assistant for your bank account that guides customers to every banking procedure from funds transfer to wealth management. The assistant also recognises both voice and text prompts.

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Big Data Analytics

More than half the banks in the financial services sector believe that machine learning and big data are among the top trends of the Fintech industry. Such technologies have helped the finance industry to reduce their costs, automate their procedures, mitigate risks and gain reliable insights for marketing. Banks are now able to meet compliance with ID verification, detect fraud through transaction monitoring and analyse customer preferences through AI enabled chatbots. JP Morgan’s Contract Intelligence system was able to check the number of loan agreements in a few seconds that took lawyers around 360,000 hours annually. Banks can verify their clients within seconds using digital ID verification procedures, thus effectively shortening onboarding procedures.

Omnichannel Structures

The consumer market increasingly prefers to make transactions via their smartphones, in addition to purchasing products and services using it. It is therefore imperative that businesses do everything they can to answer questions for customers in a comprehensive yet effective manner, using the channels preferred by the customer. Studies predict that 85% of customer interactions with brands would be automated by the year 2020. Citibank was able to develop a chatbot using Facebook messenger that answered customer queries just as a human assistant would.

Increased Use of APIs

The Fintech industry is largely offering solutions in the form of SaaS (software-as-a-service) products. This is increasing the use of independent APIs (Application Programming Interface). APIs allow for better integration of software solutions in businesses.

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