Banking and finance are data-reliant, making this an industry that stands to see a significant benefit from AI implementation. Artificial intelligence can make for more efficient data storage, greater organization, elevated security levels and faster analysis capabilities — benefits that are only limited by a bank’s ability to deploy this new technology.
AI implementation in banking can even help overcome limitations with machine learning applications that provide a way for existing tech to utilize its own database, making simple decisions based upon a fixed criteria. The more advanced the language learning model, or LLM, the more fluid the criteria can be, allowing for a wider variety of machine learning technology applications.
To decide whether AI implementation is right for your financial institution, it’s important to understand the following:
Let’s dive into each point to get a better idea of the AI landscape in the banking industry.
Benefits of an AI Implementation in Banking
AI has the potential to provide a scalable benefit to banks and financial institutions, both large and small. The benefits become clearer when you consider the possible applications of AI in banking, which include the following.
AI Application
Description
Automated / Semi-Automated Underwriting
AI tools can store, analyze, and even help with the decision-making process for incoming credit applications based upon a pre-existing criteria. Using a machine learning model that has the ability to self-improve over time can reduce risk and maximize return. This technology can also be configured to auto-trigger manual reviews if certain criteria aren’t met, avoiding costly errors.
Cybersecurity and
Fraud Detection
AI can be programmed to identify key markers indicating possible fraud, learning from manually-reported cases to catch fraudulent transaction attempts almost instantly. It can also improve the security of online assets and transactions, alerting a bank’s security team when suspicious activity is detected.
Risk Management
By tracking and analyzing client information, AI can make recommendations based upon real-time data to help banks properly manage risk as different factors — such as interest rates and default risk — change in the background.
Logistics / Process Automation
Many repeatable tasks, with a consistent set of steps, don’t require a great deal of individual discretion. Many such tasks can benefit from process automation with AI to increase speed and consistency. Leveraging AI-powered automation over traditional automation allows the tool to learn over time and get better at finding the necessary information and using it for basic tasks without direct programming.
Automated Market Research
By enabling a machine learning-powered AI tool to monitor market trends continuously, banks get real-time insights on investment opportunities.
Transaction Data Management
AI can be used to collect and analyze the massive volumes of data that are processed as a financial institution handles countless transactions on a daily basis. This provides a bank with critical insights that can be used to improve and streamline operations.
Customer Experience
AI tools allow customers to access basic banking functions – such as withdrawals, deposits, transfers, and many others – outside of regular banking hours through convenient online interfaces or AI chatbots. Such tools can also be used for account setup and loan originations for well-qualified/simple credit applications.
Regulatory Compliance
AI can assist compliance departments by automating the analysis that’s required to ensure compliance with the many regulations within the banking and finance industry.
The benefits of applying AI to these use cases are fairly straightforward:
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- Faster, more accurate, more cost-efficient administrative work;
- A nimble business model that can react quickly to market changes;
- Lowered risk of human error = higher levels of consistency;
- Greater accessibility to products and services for clients / customers;
- Improved risk management;
- Lower labor costs; and
- Higher productivity for employees supported by AI tools.
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These benefits can present new opportunities for investment, which leads to better returns for financial institutions and the clients and customers who rely upon their ability to provide financing and interest on investments.
The Potential Risks of AI in Banking
Banking is a highly-regulated industry, so AI implementation — which may open institutions to legal liability — is often met with significant hesitation. This is a reasonable concern, as AI tech — specifically generative AI and machine learning — is fairly new, and many novel AI tools are made to fit a wide variety of industries.
This is why AI implementation in banking should be executed with caution. The best way to exercise proper caution is to work with AI partners with a specialty or expertise in the banking industry. Choosing the right partner allows banks to experience all of the above-mentioned benefits of AI without worrying about landing in the crosshairs of regulatory agencies.
Experience the Benefits of AI Implementation With 7T
At 7T, our development team is on the cutting edge of artificial intelligence development. AI implementation in banking can offer greater efficiency, better margins, more accessible services and more manageable employee workloads. For all of these reasons, we pride ourselves on the results that we are able to deliver for our clients in the banking and financial services spaces.
Our world-class team of Dallas AI developers will work to identify challenges within your organization; then, we’ll create a value-generating solution with innovative technologies that align with your business strategy. This problem → solution approach to AI development is the key to our clients’ success.
7T is based in Dallas, with additional locations in Houston, and Charlotte, NC. But our clientele spans the globe. If you’re ready to learn more about RPA implementations and how your organization can harness the power of AI, contact 7T today.
