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In both old and new sci-fi movies and TV series, the depiction of total automation usually has a negative connotation. In simpler words, people are still afraid that technology and robots will take their jobs. In reality, though, automation is not something to be scared of. In industries like healthcare and retail, automation has already proven its effectiveness. What about fintech automation?
If you own a fintech startup company, should you be trying to automate both your services and internal processes? Our tip would be to plan your automation right at the beginning of your fintech application or website development process. Let’s learn more about this topic.
Automation in the finance industry
Our team has been creating UX design for fintech for a while, so following trends is part of our everyday workflow. Automation is one of those trends that has been popping up on everyone’s radar lately, but it really took off about a couple of years ago. And like with pretty much any industry today, the global pandemic is to blame.
To survive such unstable conditions, businesses have begun to transform their internal processes into more flexible ones, making their services more sustainable for clients and the environment. Cue the widespread automation to add efficiency and help deal with repetitive tasks, and ideally free more time to deal with much more meaningful tasks.
All in all, fintech automation can be defined as the widespread adoption and rational use of automation tools and software to streamline continuous financial operations. The number one focus of automation is to reduce human error and boost safety and productivity.
For example, such trivial tasks as document scanning or checking numbers for errors that can take a long time for a person to accomplish can be automated using bots or other small programs.
Benefits of automation in fintech
By integrating automation tools into fintech, companies can expect the following advantages:
- Increased speed and accuracy of internal and external processes;
- Fraud reduction;
- Better adjustment to dynamic environments;
- Lower internal operating costs;
- Real-time data processing and valuable insights;
- Faster approval processes in loans, payments, and insurance.
Technologies used in fintech
AI. Adding the power of artificial intelligence into fintech and other financial services helps build more cohesive digital ecosystems. For example, AI-powered biometrics aid in person identification, while intelligent bots deal with customer requests.
ML. Machine learning in fintech is best used to process heavy amounts of data in extensive documentation or to help prevent fraud and automate security practices. The pattern-based work of ML offers more accuracy to cybersecurity teams dealing with fraud forecasts.
Robotic automation. Intelligent robots are a godsend when it comes to automating labor-intensive duties and workflows. Better yet, robotic process automation, or RPA, utilizes automated software for data processing, such as extraction from multiple systems.
Finance automation examples
Fintech automation comes in many different forms. Here are some of the most popular ones today.
First of all, finance automation helps with billing and invoicing by automating inward and outward transfers and other recurring payment operations. Another example is manual processing reduction for bill discounting and financing requests.
Customer communication and support
The best example is customer service bots. From simple operations like checking the balance to helping with everyday transactions, automated customer service software offers 24/7 support for basic stuff, whereas humans are reserved for more advanced and nuanced situations.
One of the standard activities for banks and other financial institutions is compliance report generation listing fraudulent and suspicious transactions. Prior to automation, all information fill-up was manual. Now, thanks to natural language processing, reports have become seamless.
Financial automation paired with machine learning is perfect when dealing with large, structured, or unstructured amounts of raw data. The best example is risk management, where everything depends on your accuracy and clear action plans.
Automating online insurance payments and claims processing can be done through internal platforms or third-party payment tools. Integrating automation also works wonders for tasks like pre-qualification, policy management, underwriting, and regulatory compliance.
KYC and AML
KYC and AML stand for Know Your Customer and Anti-money laundering. These procedures, along with sanction screening, are considered very data-reliant activities that assist the decision-making processes. Automation here helps scan documents using Optical Character Recognition.
Primarily used in SaaS, enterprise automation refers to both data and workflow automation, usually performed by integrating cloud-native solutions using API connections. Such tools help unite employees of all departments, focusing on effectiveness and cost reduction.
Why automate in the first place?
Automation is now an integral part of any modern finance strategy. With automation, fintech companies now have the ability to reduce the number of complicated and monotonous tasks. Basically, if there’s a chance to get rid of hideous repetition, why not take it? Especially if it comes with a productivity boost.
As we’ve established earlier, automation can be applied pretty much anywhere in fintech. And tools like chatbots or verification software are only the beginning. Finance automation helps businesses and organizations in the fintech sector provide better service to their clients at considerably lower costs.
Overall, cost reduction, operational efficiency increase, and an upsurge of satisfied customers are the primary reasons why fintech automates. Yet, a thought-out strategy is most definitely needed to make it work properly for you. Our best advice would be to try out different approaches to see what works for you.
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