Using gen AI in anti-financial crime is a gamechanger. If you speak with a financial investigator working in financial services, payments, or gambling, they will tell you of their frustrations at having to spend an unequal amount of their time gathering and sorting data when looking for risky customer behaviours.
Of course, they would rather be allocating time to the higher-risk detections from transaction monitoring to understand if the events are standalone, networked or an emerging threat that needs to be looking into further.
Then bring around a table a select group of CROs, heads of fin crime and Anti-Money Laundering Compliance Officers (AMLCOs), representing gaming, banking, payments, and betting - and they will also add to those investigator tones.
They will most probably talk of needing to see consistent investigation process, have certainty on compliance outcomes, and know that they can find the risks that matter.
This was the case during the discussion SymphonyAI held recently in Sydney, with Microsoft in attendance as special guests, where gen AI was introduced into the conversation as one of the

Generative AI in the financial crime investigation process

Taking a look at the Sensa Investigation Hub in action, we can see that using generative AI in anti-financial crime investigations creates opportunity to:

• Make the financial crime investigator experience highly intuitive
  • Investigators can simply ask the questions that they would like to know the answers to. For example: Where has this customer transacted overseas? What is the average value of a transaction between March and May?
• Create new ways for compliance teams to gain insights into the quality of the investigation process
  • What questions did the investigation consider? Did the investigator consider activities of similar customers? What could be done differently in future?

This was the case during the discussion SymphonyAI held recently in Sydney, with Microsoft in attendance as special guests, where gen AI was introduced into the conversation as one of the trending topics for anti-financial crime in 2024. These included:

• Can banks and other financial services fully trust their investigators using gen AI?
• How do financial services teams know the system will provide the right results?
• How can the process be explained to a regulator or auditor?

A new way of thinking about certainty, trust, and compliance

It was fascinating to have Microsoft guide participants at the Sydney session through a new way of thinking about creating certainty, trust, and compliance with gen AI.

• Certainty is in the data you own.
  • Control the data that you query via gen AI to control the scope of the result – not everything on the internet needs to inform a response. Your data sources and reference sets can be used to gather the information that is required. For example, transactions that happened, the customer’s KYC data, etc.
• Trust is asking the right question for the problem.
  • Ask the question to elicit the relevant answer to your enquiry. This means that there should be less of ‘tell me everything about the customer's transaction history’, and more of ‘tell me when the customer previously deposited cash of this amount’. By using precise questions, investigators can streamline and speed up their investigation processes.
• Compliance is digital transparency of every step.
  • By checking the log of activity when gen AI was used to query the data, it is easy to ensure compliance processes are in place. It is possible, for example, to check what questions an investigator has been asking, and the order in which relevant information was included or excluded.

It's clear that with the introduction of gen AI, off-the-shelf AI, and large language models (LLMs), opportunities, uses, and challenges have moved rapidly. Before opportunities are taken and the benefits seen, confidence in a solution is required.
is also a need for predictability in how regulators will approach the use of gen AI in anti-financial crime; this is already developing at a high-level with the likes of the Australian Government's interim response to safe and responsible AI.

The current use of gen AI in fighting financial crime

When thinking about the current use of gen AI in fighting financial crime, there is a lot to consider:

• Regulatory expectation on all sectors to be risk-based and zeroed in on the threats of financial crime;
• Financial pressure on expenses to manage compliance;
• Social expectation to reduce financial crime;
• Scarcity of the resources needed to fulfil financial crime obligations.

SymphonyAI is leading in allowing banks and financial services to trust in adopting the opportunities for efficiency and transparency that gen AI provides.
Using the likes of Sensa Investigation Hub, frustrations of the financial crime investigators can be reduced, while providing increased confidence in compliance with regulatory obligations.
In order to continue this education, it is a must that SymphonyAI will keep the conversation going and bring the right people to the table to further understand the wants, needs, and desires of banks and financial services as we all have the common goal of preventing the impacts of financial crime.
For more information on using gen AI in anti-financial crime, to appreciate its ability in enhancing financial crime investigations, and to gain insight into further developments occurring over the next twelve months, book a demo of Sensa Investigation Hub.