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The optimal path to AI implementation for financial crime compliance

We talk about why financial institutions implement AI for compliance, and discuss some of the most common implementation pitfalls as well as how to avoid them.

Napier AI
April 12, 2022

The applications of artificial intelligence for financial crime compliance are potentially game-changing and can facilitate unparalleled operational efficiencies and transform your organisation’s compliance function.

This blog highlights some of the reasons why financial institutions may choose to implement AI for their compliance needs, discusses some of the most common implementation pitfalls and how to avoid them.

We recently released a 12-step guide to AI implementation created by our Chief Data Scientist, Dr Janet Bastiman, and FINTRAIL's Managing Director, James Nurse. This comprehensive resource addresses some of the most common challenges financial institutions face in this journey, and assesses the current regulatory landscape around the use of AI.

Access the guide here.

The optimal path to AI implementation for financial crime compliance eBook

Why implement AI into your company’s compliance processes?

There are many reasons your organisation may have decided that AI will alleviate your problems:

  • Desire for automation and digitalisation
  • For business and cost efficiency
  • To keep up with rapid increases in regulations
  • Senior leadership don’t want to risk fines or reputational damage from not detecting criminal activity

There’s huge pressure on financial crime teams to ensure they do a diligent and thorough job. If you’re considering AI, it is likely because you are aware that your processes may not be up to scratch and may have limitations either in the processes themselves or the tools that you have in place

What steps are there to implementing AI systems?

Your company has had a conversation internally and decided to adopt AI into a wider AML framework, or perhaps into one particular function such as transaction monitoring. There initially appear to be three phases in the process of AI implementation:

  1. You decide that adopting AI resolves all your transaction monitoring needs
  2. You skip straight to implementation
  3. Then you go live

It sounds simple, but there are more steps needed to ensure a successful outcome. In this guide, we are going to take you through those steps that we believe will get you from ideation to successful implementation.

AI is growing in popularity in the AML space and is increasingly highlighted by regulatory bodies (like MAS) as a useful tool to improve compliance functions – but it’s not a one-size-fits-all solution or a silver bullet, and if implemented incorrectly you’re unlikely to get the most out of it.

The do’s and don’t’s of implementing AI

When implementing AI into your organisation’s AML function, it’s important not to rush the process or sacrifice crucial steps in the pursuit of a speedy transition.

Although 12 stages may seem extensive, each serves a valuable purpose and informs subsequent stages. Following our suggested path can save you time, conserve resources, and deliver better outcomes by reducing internal and external risk. Adopting a detail-oriented approach to AI implementation will lead to a more sustainable and reliable solution in the long run.

One key takeaway from this suggested approach is the importance of data. The effectiveness of AI-powered financial crime systems is entirely dependent on having good quality data in sufficient volumes and in the correct formats.

You can approach AI implementation with the best intent, performing thorough risk assessments and regulatory checks, but your own data is what will ultimately make or break the project.

Therefore, it is imperative that you invest time and effort into the maturity assessment and data aggregation and assurance stages, using all available internal resources and liaising with relevant teams and data experts.

Going live isn’t the end of new systems implementation

Finally, remember that going live does not mark the end of your AI transformation: ongoing quality assurance and regulatory monitoring are vital to maintaining the efficiency and effectiveness of your new solution.

Implementing AI software is an opportunity to partner with a technology vendor to find or create a product that fits your needs long term. Technology capabilities are not static, so it is important to provide your supplier with regular feedback to help shape and influence model enhancements moving forward. By doing so, your vendors are better able to scale the solution in line with your organisation’s requirements and manage your evolving regulatory obligations.

Discover next-generation financial crime compliance technology

If you are looking to implement AI into your compliance function, download our Maturity Model, book a demo of our solutions, or get in touch to find out how Napier can rapidly strengthen your AML defences and compliance capabilities.

Photo by Shubham Dhage on Unsplash

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