The transformative potential of advanced analytics is helping financial sector organizations combat sophisticated fraud attempts and challenging regulatory landscapes.
According to one estimate, UK financial institutions spent £34.2bn last year on fighting financial crime – around the same amount as the Ministry of Defence invested in the nation’s defenses.1
Meanwhile fraud associated with Automated Push Payment (APP) alone is estimated to cost UK consumers well over £1bn annually.2
“Banks are concerned about how much they may have to pay out if they don’t have the right systems in place to catch this form of fraud,” says Michael Nicholls, Principal, Financial Services Consulting at EPAM Systems.
Generative AI can also be used by fraudsters to evade biometric identifiers. IDC says: “This means that these legacy biometric protections will need to be augmented in some manner so as to improve the capabilities of detecting the use of GenAI-generated biometric identifiers and use by fraudsters.”3
Increasingly, machine learning will play a key role in identifying these aforementioned synthetic identities, as well as non-obvious relationships and unusual end-user behavior in real-time.4 5
“Much of this data has been available for some time,” says Nicholls. “But now it’s possible to process and analyze it in a timely manner. Indeed, institutions are obliged to detect and report within a very short timescale – which could not be achieved without good technology.”
Compliance challenge
In the domain of compliance, the stakes are rising too.
“The regulators have more teeth and people are noticing it,” says Nicholls. Eight out of 10 compliance professionals (81%) polled by Thomson Reuters in Europe say they believe that the number of senior bankers being held personally liable by regulators will increase.6
Meanwhile, the financial penalties are growing. For example, the EU Artificial Intelligence Act allows for fines of up to 3% (or up to Euro 15m) of global revenues and up to 7% (or up to Euro 35m) for infarctions involving ‘Prohibited AI Systems’.7
Advanced analytics has the potential to assist with compliance workloads. The European Banking Authority, for example, has recently consulted on the use of machine learning for internal measurements internal risk ratings.8
In the case of regulatory changes, AI co-pilots can now accelerate the work of developers by a factor of two or three.
“They can tell you where exactly you need to change your code, making it a very accelerated process,” says Laksmi Jagannathan, Senior Data and Analytics Consultant at EPAM Systems. “The system suggests a change, you review it, you accept it: it’s a co-pilot experience.”
All these techniques rely on integrated data management platforms that create the foundations for advanced analytics, including the ability to:
- liberate data from legacy silos
- manage the diverse datasets required for analytics, AI and ML
- ensure the quality, completeness and lineage of data
- and establish streaming pipelines for real-time analytics
Jagannathan believes that specialist data intelligence platforms like Databricks are using AI to develop the required functionality, reliability and vertical specialization.
“Financial services institutions are looking for platforms that can help prevent fraud and data breaches and react to regulatory change,” she says. “These platforms are becoming an essential part of the solution.”
Learn more about the EPAM and Databricks partnership.
1Lexis-Nexis, UK Financial Services Sector Spending £22k Per Hour Fighting Fraud (March 2023) https://risk.lexisnexis.co.uk/about-us/press-room/press-release/20230301-uk-financial-services-sector-spending
2UK Finance, Criminals steal over half a billion pounds and nearly 80 per cent of App fraud starts online https://www.ukfinance.org.uk/news-and-insight/press-release/over-ps12-billion-stolen-through-fraud-in-2022-nearly-80-cent-app
3IDC Futurescape, Worldwide Banking 2024 Predictions, October 2023, IDC #US51290623 https://www.idc.com/getdoc.jsp?containerId=US51290623
4PwC, Impact of AI on Fraud and Scams (December 2023) https://www.pwc.co.uk/forensic-services/assets/impact-of-ai-on-fraud-and-scams.pdf (see pp12-23)
5Experian, Shining a Spotlight On The Latest Fraud Trends https://images.go.experian.com/Web/ExperianInformationSolutionsInc/%7Bb58b6ad6-6ebc-4f8e-b63f-daaed99a585a%7D_UKI_Annual_Identity_FraudReport2023_FINAL_EM.pdf (see p18)
6Thomson Reuters, Cost of Compliance 2023 (May 2023) https://www.thomsonreuters.com/en-us/posts/investigation-fraud-and-risk/2023-cost-of-compliance-report
7EU AI ACT (April 2024) https://artificialintelligenceact.eu/article/101
8EBA, Follow-Up Report on the Use of Machine Learning for Internal Ratings-Based Models (August 2023) https://www.eba.europa.eu/publications-and-media/press-releases/eba-publishes-follow-report-use-machine-learning-internal