IBM RegTech Innovations

FinTech explosion and faster payments drive faster financial crime in 2020 – how can banks respond?

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Financial crime isn’t going away, rather it is growing

Investment in financial crime prevention solutions for AML, fraud and insurance investigations has been mandated by regulators for decades. But despite the billions already spent, regulatory penalties continue to rise and fraudsters find new ways to steal. In attempts to keep up, financial crimes and fraud staffing continues to grow about 10% each year. At the same time, rapid globalization and innovation in payment services have set off a fintech explosion of sorts, spawning new strains of financial crimes and fraud vectors that financial institutions now have to grapple with.

Ubiquity and speed

The fintech explosion and an expanding array of faster payment options have raised the bar for customer expectations. Whether an individual consumer or an enterprise, customers of today want to experience frictionless, instantaneous payments and financial transactions with quick confirmation and settlement finality. They need a real-time view of liquidity and cash positions. An enhanced customer experience might include new and useful functionality and richer, integrated information. Payers and payees look for security, added-value, simplified processes and perhaps above all, ubiquity.

Customers who can sync, stream and switch seamlessly across devices – at any time – are bringing those expectations of ubiquity and immediacy to their financial transactions. With the uberization of payment services the list of expectations is growing – as is the list of person-to-person mobile payments vendors and industry disruptors offering fast-pay options, such as Google. Today’s customer is coming to expect faster, better, everywhere, anytime payments.

Faster payments equal faster crime

Financial institutions and banks are under immense pressure to supply such real-time, enhanced experiences, and to support multiple new suppliers and service options. In the rapid rise of new payments vendors and identification systems, non-traditional identifiers are being used, for example, personal ID’s (a.k.a. National Identify Card), cellphone numbers or email addresses. Yet non-traditional identifiers and novel functions can facilitate the creation of synthetic identities and fraudulent transactions. While criminals exploit the safety gaps, many incumbent anti-fraud systems can’t pinpoint or prevent the new crime vectors.

All this is exacerbated as some countries require banks to comply with new Real Time Payments standards, for example, the National Payment Platform (NPP) in Australia, The Clearing House in the U.S. and SEPA in the European Union. Such standards are a good thing, but it does mean that regulation can impact a bank’s ability to deliver on the expected customer experience because of regulatory compliance, potential cost or penalties issues. Yet these changes also represent opportunity for banks to serve a new market. But most banks and payment service providers still run their payment processing and financial crimes operations through legacy systems that are not built for the era of immediate payments and rapidly evolving financial crimes and fraud schemes.

Case in point: when Australia launched the NPP real-time payment platform in early 2018, payments services provider Indue partnered with IBM to infuse AI into its payments offering. Indue has over 40 years experience in the payment industry and their stated mission is to be the leading provider of innovative payment solutions.

Driven by the reality that fraudsters are operating nimbly in the faster payments world, Indue leveraged IBM Safer Payments solutions to bring real-time detection and artificial intelligence (AI) to fraud management in its NPP real-time platform. See the case study here.

How banks and financial institutions can respond

In the current payments and transactions environment of evolving security risk, customer expectation, and regulation, approaches based on AI, data science, machine learning (ML) and big data computing have the potential to address new, real threats. Some readers may feel that these advanced technologies sound promising, but wonder how they would actually solve financial crime challenges.

The truth is that financial institutions and banks really can keep pace with new regulatory requirements and emerging crime patterns by using the latest technologies. Here is a brief overview of some of the key technologies and how they are being successfully applied to prevent financial crime:

Data science
  • Data science blends several disciplines in order to organize, optimize and serve all the data and elements needed for running smooth AI, machine learning and similar services.
  • It focuses on building and scaling AI with trust and transparency, while educating users with quick-start tutorials.




  • AI in financial crime and in business applications applies domain expertise to help deliver more accurate detection, insights, decisions and predictions.
  • It speeds, automates and optimizes rules, processes and models for new types of fraud.


Machine learning
  • ML is a highly useful AI-driven service for building, custom training and deploying machine learning models and neural networks.
  • The training process is automated with simplified tools.
  • State-of-the-art ML provides on-site fraud management for on-demand rapid responses – without applying intermittent, ad hoc rules to failing black-box models to handle new fraud attacks.


Big data
  • The AI algorithms that automatically create new fraud prevention models and rules require big data performance.
  • Big data computing uses massive parallel computing for critical computations, and scales rapidly to manage many variables and thousands of data points at once.


Note: Watch my podcast about financial crime prevention with emphasis on the latest trends in customer expectations and the uberization of payments, on the Association of Certified Financial Crime Specialists (ACFCS) site. Click here for podcast details.

IBM’s suite of financial crimes and fraud management solutions are designed to recognize and stop old and new fraud types and suspicious behaviors across multiple channels – while cutting false positive rates. They are also based on open standards, useful for multi-cloud and hybrid environments of today. For more specifics on cognitive solutions and Financial Crimes Insight, see

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