At a glance
By Rosalyn Page
AI is improving finance processes by addressing issues such as financial crime detection and generating risk reports. It can help streamline processes, improve accuracy and offer personalised customer insights.
The technology offers powerful ways to improve the detection and investigation of financial crimes such as fraud, scams, anti-money laundering and sanctions, according to Jonathan Tanner, senior director of financial services and insurance APAC at Pegasystems.
“There are many [areas] it can address, but what we see in the market is that the sweet spot for helping to solve many of the challenges is a combination of both statistical and generative AI, the left brain and right brain working together,” says Tanner.
While the Australian Securities & Investments Commission (ASIC) has flagged the risks of using AI without the appropriate governance and compliance measures in place, here are five ways AI can be utilised in the finance sector.
1. Scam and fraud detection
The volume of scams has grown rapidly and banks, in particular, are facing a tough challenge in managing the risks in the usual way.
“Many existing detection systems are designed for specific types of financial crimes and aren’t integrated in a way that makes it easy for the bank to look at the risk holistically,” notes Tanner.
As scams become more sophisticated and new digital channels emerge, banks are increasingly turning to AI to help manage these risks at an enterprise-scale.
“Predictive and adaptive AI models have been used for a while and can significantly improve the hit rate and reduce the number of false positives by constantly learning and adapting from the data,” he says.
2. Investigating financial crimes
AI is also being used in financial crime investigations, including fraud, anti-money laundering and sanctions, which traditionally requires high degrees of skill on the part of a bank’s human analysts.
A unified workflow and case management, combined with predictive, adaptive and generative AI, can help human analysts to aggregate, rescore and understand alerts, according to Tanner.
“AI simplifies and speeds up the process of investigation, which helps better protect customers and the bank, even as the volume of financial crimes continues to grow,” he says.
3. Creating risk reports
As part of these investigations, generative AI is being used to help assemble relevant information from an investigation into the specific report format required for analysts to review.
“This significantly reduces the level of manual effort to produce [risk reports] and improves accuracy,” says Tanner.
For example, an AI-driven “alert and investigation” system is now being used by an Australian bank to bring multiple applications together into one powerful platform.
The system can process more alerts, identify false positives more effectively and match cases with existing alerts.
“It’s a prime example of how AI can supercharge protecting customers and ensure compliance with regulations,” he says.
4. Financial insights for customers
Customers today expect to have access to rich data about their financial lives – when, where and how much they’ve spent as well as insights about loans and how their investments are tracking, explains Warren Schlipzand, DataStax’s area vice president for Australia, New Zealand and Japan.
By using AI to analyse vast amounts of customer data, finance businesses can gain deep insights into customer behaviour, preferences and intentions. For example, generative AI can allow financial institutions to use natural language queries to provide responses to customers in conversational language, Schlipzand notes.
“Organisations can then design AI-driven tools that not only respond to customer needs in real time, but also anticipate future needs, providing a more seamless, intuitive customer experience,” he says.
AI can also be used to analyse transaction patterns, communication history and market conditions to predict a customer’s financial goals – such as saving for a home or planning for retirement.
“With this insight, financial institutions can offer personalised recommendations and solutions, such as tailored investment options or automated saving plans that align with their customer’s goals,” he notes.
5. Personalisation
Businesses are consistently told that personalisation helps improve customer satisfaction, sales and customer service.
Supercharging personalisation with AI has many applications across the customer life cycle, with a key objective of deepening those relationships, according to Tanner.
AI and geo-location can deliver specific merchant offerings at the point of sale. Within a lending journey, it can help switch from coaching a customer through the process to providing product bundles tailored to their needs, such as insurance.
“Predictive and adaptive real-time AI helps deliver the next-best conversation with customers at any given time and it’s something banks are increasingly adopting,” adds Tanner.
Adding generative AI to the mix helps finance businesses build offers more rapidly and be more responsive to customers.
“A great example of this is National Australia Bank, which is using these technologies in its Customer Brain program to deliver personalised services to improve customer experiences with the bank,” he says.
How to tell if AI is the best option
Many finance problems can be tackled with AI, but the challenge is knowing when it can help and when the process itself needs overhauling. The key is following a process to assess the workflow and the potential benefit of adding AI.
The first step is identifying the problem, then mapping the current process, evaluating it and identifying gaps or limitations. Can process change rectify these? If not, it’s time to consider where current AI solutions may be suitable.
Pilot testing a new AI solution will help assess if it improves the process to help inform a decision that weighs up the cost-benefit of process change versus AI implementation.
Ultimately, the key to integrating AI is a clear understanding of the problem and a strategic approach to applying the technology where it can deliver improvements.
