5 Ways AI is Being Used in Fintech Today [Resulting in Happier Customers]

AI in Fintech

The Fintech industry is synonymous with technical innovation. Of course, since it has ‘tech’ in its very name. Taking a step back, what is ‘Fintech’? It is the combination of finance and technology, the delivery of financial services through modern, technical solutions. While the infusion of tech and finance is not very young: we are already used to transacting via phones, purchasing stocks online, creating fund portfolios through an online platform, etc, the introduction of Artificial Intelligence in Finance and Banking is relatively newer.

AI technologies are helping Fintech provide better services, faster. Using Big Data analysis and predictive analytics, for example, a Fintech application can process a loan request much faster than was possible just a few years ago. AI platforms can enable banks to automate services, and seamlessly create experiences without the need for manual intervention.

Here are 5 current applications of AI in Fintech

1. Extract Past Transactions & Reports

AI powered bots can use Natural Language Processing (NLP) to help customers check their past transactions and banking history. The bot can ‘understand’ what the consumer is asking for, and provide exact results, rather than have the customer sift through transaction details to find one entry.

Bank of America’s virtual financial assistant, Erica is a perfect example. Michelle Moore, head of digital banking at Bank of America, gave some insights into what most customers were using Erica for. The most popular use of the bot was to find past transactions, to find exact transactions to be more precise. For example, a customer can tell Erica, Show me all Amazon transactions between the 1st and 3rd of October 2019, and Erica will filter out the details by vendor, date, and type (Debit/Credit). This seems like a simple task, but is a major leap forward if you think about it. I the past, to get the same details, you would have to download transaction details for the time period, then apply filters in an Excel sheet to get the final, desired results. Erica had 1 million users within the first 3 months of the virtual assistant’s roll out.

Virtual assistants, like Erica, can do much more of course, but simplifying the extraction of transaction data is an important feature for exceptional customer service.

2. Automated Claims Processing

Claims processing is a cumbersome process, for both the financial institution and the customer. The usual process, when a customer wants to claim an insurance amount (health, life, vehicle, etc.), is the customer first needs to activate the coverage when the issue occurs (while being hospitalized, for example) and then claim it once all expenditure is made. Both these processes involve a lot of forms, proof, verification, and documentation. An AI powered bot, can simplify the entire claims process for both the company and the customer.

Once the AI bot has access to the company’s database, it will be able to verify claims, look for anomalies, perform fraud detection, scan signatures for authentication, etc and take over the entire claims process. By accessing past data, the bot can autofill most required details and aid the customer in moving the process forward considerably faster.

3. Customer Risk Profiling

Customer risk profiling is an extremely critical task when on-boarding new customers, or providing existing customers with new finance assets. Banks and financial institutions also segregate services depending on potential risks, for example reducing the credit limit for a high risk candidate and vice versa.

Traditionally, this would involve the bank performing rigorous and time consuming background checks. With the power of AI, however, the entire process, or most processes, can be fully automated to save time and increase efficiency.

An AI system can analyse past data to categorize customers into different risk levels, and financial advisers can then provide specific services and assets.

In June 2018, Canadian insurance company Manulife became the first insurance company in Canada to automate underwriting. They launched their new Artificial Intelligence Decision Algorithm which can underwrite using AI. They say it is going to tremendously reduce transaction time.

4. Document Analysis

You might think AI is very powerful when it comes to existing data and newly entered textual data, but what if older (or new) manually filled forms were provided, or images were provided, or a signature had to be scanned?

Optical Character Recognition or OCR, is solution for digitizing any hard copy documents. Artificial Intelligence systems can scan, digitize and also analyze data from hard copy documents via OCR.

AI can considerable reduce the time spent on document and contract analysis, by digitizing them and then analyzing them via AI. JP Morgan, some time in 2017, implemented a program called COIN, which stands for Contract Intelligence. COIN helped lawyers and loan officers review documents, thereby reducing time consumed and also human errors. It apparently completed 360,000 hours of finance work in just a few seconds.

5. Stock Market Predictions

While the market price of a stock cannot be predicted to a dot, it is common knowledge that stock prices often follow a pattern, and continue to follow that pattern barring unexpected or drastic influences.

The New York Stock Market has been around for over 200 years. The Indian BSE has been around for over 100 years. Needless to say, we have an ocean of data at our disposal: historical prices, market influences, spikes, crashes, etc. Studying this data to provide analytical insights and more importantly predictive analytics, is now possible through AI and ML. In fact, the entire trading process can be automated, with users only depositing a sum of money and the AI enabled platform buying and selling stocks based on predictive analytics.

If You’re a Fintech Company, There Definitely is an AI Solution for the Services you Provide

All the examples above, Bank of America’s virtual financial assistant Erica, Manulife’s Artificial Intelligence Decision Algorithm, and JP Morgan’s COIN are clear indicators of leading financial companies shifting towards AI. The reasons are blatantly obvious: AI reduces execution time, reduces errors, and thus increases the efficiency of processes. This leads to quick problem detection, quick solutions, and quick execution, all leading to happier customers.

As a Fintech company, you will have multiple redundant tasks and processes that could benefit immensely from automation and AI. Once identified, an AI solutions company can help you automate them, and boost productivity and efficiency. Fortunately for you, Getafix is an AI solutions provider. If you’re looking for a solution, just drop in a message.

How do we design products for Fintech? Here’s a peek: Designing For FinTech | 4 UI/UX Rules

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