From managing and analyzing large amounts of data in real-time, to learning from the results and providing valuable insights — there are a myriad of ways that companies in the financial sector can leverage artificial intelligence and machine learning techniques to their benefit. Given the digital ecosystem and the growing number of customers using various financial products and platforms – the adoption of AI and ML can prove particularly advantageous. 

What are these advantages? We take a look at the top Six:

1. Better Security and Fraud Detection

In the US alone, fraudulent wire transfers alone account for an annual loss of $439 million. Add credit card and loan application scams and false insurance claims to the list, we see deceptive financial activity continues across the globe. Artificial Intelligence can help monitor the large number of transactions that happen on a daily basis in real-time, detect anomalies in user’s typical spending behavior’s, take a more structured and quicker approach to frauds, and enable a swifter and more accurate response.

2. Improved Customer Support

Customer expectations are ever evolving. Clients now bank at all hours of the day and are accustomed to quick responses to their queries. Providing answers and facilitating all kinds of transactions then becomes a 24/7 job, leading to a great deal of pressure on customer service teams, not to mention that financial pressure that this imposes on businesses. AI-powered chatbots, virtual helpers, and other AI interfaces can help minimize this workload significantly.

3. Automated Loan Approvals

Given the state of the current economy, financial assistance has continued to soar. And one of the biggest challenges for lenders in the process has been to understand loans and get approval on loan applications. With real-time analysis, AI can automate approvals for low-value loans and assist in the evaluation of larger transactions. The same can be and is being applied to insurance.

4. Improved Algorithmic Trading

AI has made great advances in making algorithmic trading accessible to the masses in the recent years. With consumers now using mobile apps to trade in stocks and shares with the assistance of AI-powered decision-making, the role of AI has become more crucial. And, in a day and age when 70-80 percent of trades are done algorithmically, AI is being used widely by large trading firms and institutional investors to transform the trading desk and help crunch big data points in real-time, reduce risk and drive more informed decision-making, all while learning insights and anomalies that more traditional statistical models could not pick up on.

5. Personalised Banking Services

The large number of customers that financial institutions now serve mean that personalised service is extremely difficult and costly. The intervention of AI-powered technology can help ease both. AI algorithms can collect and analyse consumer information, provide relevant pre-approved product recommendations and personalized financial advice. AI in banking apps can also help clients track individual financial goals and expenses easily. How does all of this help the business? It helps gain the trust of clients and adds to the brand loyalty, leading to long term customer retention and increased referrals.

6. Omnichannel Collections strategy using Propensity to Pay solutions.

Finally, AI algorithms can effectively allow organizations worldwide to benefit from omnichannel communications. An omnichannel debt collection process, powered by propensity to pay data, helps manage customer expectations and ensures that digital channels such as chat, social media, text, email, and interactive voice are fully utilized. With the power of AI, companies can now expect seamless communication to not only connect with debtors but improve their collections.

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