Artificial intelligence (AI) might sound like something out of a science fiction novel, but it’s becoming a reality faster than you might think. Owing to recent advancements in big data, computational hardware, and machine learning, artificial intelligence is becoming increasingly powerful and useful by the day.

And the technology isn’t going away anytime soon.

Andrew Ng, the founder of the Google Brain project, describes artificial intelligence as the “new electricity.” Major tech and enterprise companies are developing AI products and services (like Siri, for example) designed to make everyday life easier. As a result, AI is poised to disrupt and transform a range of industries, including banking and financial services.

You’ve probably heard a lot about AI in banking and how your bank needs it. But where do you begin? What can you do to prepare your bank?

Implementing this cutting-edge technology at your bank may seem like a daunting task, but it doesn’t have to be. Here are five steps you can take to prepare your bank for AI.

1. Define the desired outcome

Before you can get anywhere with AI, you first have to decide what you want to accomplish with it. AI can be applied to any number of banking tasks — analyzing data, automating back office operations, and handling customer support, to name a few — so the first step is to choose which application(s) your bank should focus on first.

The best way to do this is to balance the cost versus benefit of using AI to handle any given task. Ask yourself: What pain points are hurting your bank’s ROI the most? What tasks could best be handled through automation, freeing up staff to focus on higher-value activities? Could a consumer-facing AI solution help attract new customers or add value for existing ones?

As soon as you’ve answered these questions and determined how an AI solution could best serve your bank, you’ll have a good sense of how to begin implementing the technology.

2. Decide whether to seek an AI vendor partnership

AI is a cutting-edge technology, so naturally, most banks won’t understand the nuts and bolts of how it works, much less have the necessary tools or resources to implement it.

Before launching AI at your bank, you’ll first need to take stock of your company’s resources and staff to determine if you’ll be able to develop an AI solution internally or if you should bring in a team of outside experts.

First, consider your innovation and technology budget. Do you have enough funding to cover the cost of developing, hosting, and maintaining an AI solution internally? What about scaling the technology after its initial release? Is an internal AI solution sustainable in the long term?

Next, think about your staff. Does your team already have engineers capable of developing and maintaining an AI project, or would you have to hire some?

Depending on your answers to these questions, you may want to consider partnering with a third-party AI technology vendor to implement your AI project. Consider all of the budget and staffing factors before deciding what’s best for your business.

3. Consult your core banking and data providers

Developing any kind of AI solution requires a considerable amount of data. Depending on your bank’s infrastructure, you may or may not have direct access to the data you’ll need to develop your AI solution. If you use a core banking or data provider, for instance, they may control your institution’s data.

Whether you decide to develop an AI solution internally or with the help of an external AI vendor, you’ll need access to this data.

Consult your core banking and data service providers to determine what steps must be taken to integrate your institution’s data with an AI solution. First, find out if your vendor partners maintain exclusive access to your data. If they do, find out if they’d be willing to facilitate an integration of your AI solution with your institutional data.

Next, find out what data your institution has collected and how it is structured. Depending on the applications you’ve selected for your AI solution, your institution’s data may need to be restructured before it can be input to your AI’s algorithms.

If you don’t have the resources for an integration or your core service providers won’t permit one, look for alternative solutions. Some third-party AI vendors offer cloud-based solutions that don’t require a core banking integration.

4. Build and structure your innovation team

Regardless of whether you decide to develop your bank’s AI internally or work with a third-party vendor, it’s essential that you establish a clear chain of command to direct it. For your innovation project to succeed, every stakeholder needs to be on the same page about the goals, steps, timeline, and desired outcome of the project.

First, decide which members of your executive team will direct your AI project. Who is in charge and has the decision-making power? Is it a single person or a collective? How will decisions and instructions be communicated to the rest of the team?

Next, determine the structure of your technology team. Is it comprised of existing staff members, third-party vendors, or both? Does your existing technology department have trained data scientists capable of developing and maintaining complex AI algorithms, or will you need to expand it to include new hires or consultants? If you’re outsourcing the development of your AI entirely to an external vendor, who is in charge of liaising with the vendor?

Establishing a clear sense of who is in charge of what will help your innovation team work smoothly and efficiently to implement your AI solution.

5. Develop a clear AI implementation plan

So you’ve laid all the groundwork for your AI project. Now what? Now you need to create a concrete plan for developing your AI, deploying it, and measuring its ROI.

Start by determining the desired timeline of your project and working with stakeholders to establish realistic targets for your project’s development and launch.

Before the project’s launch, determine how you will measure the project’s ROI. Which of your bank’s performance metrics do you anticipate changing as a result of your AI solution? How will you measure these changes?

Delineate a clear project roadmap to ensure the project’s success and see the most return on your AI solution.

Conclusion

AI is coming to banking, and it has the potential to drive new revenue, decrease operational costs, and mitigate risk. The world’s leading financial institutions are already investing in and deploying this technology as they compete for control of the market.

To help your bank reap the benefits of this innovative technology, start planning your AI strategy today.

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Source: Abe AI

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