In 2022, there was a 24% increase in digital banking fraud in South Africa compared to the previous year. The same research showed that cybercriminal activity accounted for more than R740 million in company losses.

With banking and financial crime escalating, institutions must reassess how they can use data to improve customer decisioning and mitigate against the risk of fraud, writes Itumeleng Nomlomo, senior business solutions manager at SAS in South Africa.

A customer’s initial onboarding journey is often the most interaction they will ever have with an organisation. This series of touchpoints provides the applicant with their first insight into what being a customer will be like. Unfortunately, unconnected processes often create gaps for customers to fall through or for cybercriminals to exploit.

While this is a significant challenge for incumbents like banks who rely on legacy systems built for traditional branch operations, there has been an emergence of the next generation of banks built on cloud-based technology. According to research, these fintechs leverage advanced technologies such as artificial intelligence (AI) to enable a superior customer experience.

But regardless of the environment, the golden thread tying banks, financial services providers, and companies together is their reliance on data and analytics. By embracing modern technologies, all stakeholders can improve the decision process that links people, data, and processes.

Think of it as a way of making decisions that cover the entire customer life cycle to enhance not only customer experiences but also manage risk better and improve internal efficiencies.

Overcoming the legacy environment

Today’s cybercriminals know how to use AI and technology to compromise organisations and consumers. Organisations with legacy systems will not be able to detect the activities of these smart bad actors. Just consider the potential threats of synthetic identities, more sophisticated scams, and even digitally driven ways of committing fraud.

Bad actors know how to navigate around the systems, and they know the organisations that are still operating with those legacy systems that are vulnerable to new technology and AI.

Banks, like every other business built on a legacy environment, must ensure their data comes together for more informed decision-making. Siloed operations provide cybercriminals with an opportune way of entering an organisation either by compromising a client’s information or through an email scam.

This is where an enterprise decisioning platform becomes invaluable. Harnessing data from multiple internal and external sources, these environments can provide business and technology leaders with the insights necessary to act, drive business growth, mitigate losses and reduce the likelihood of fraud by better understanding their customers.

Technology reinvention

Such a unified decisioning process can be augmented with machine learning (ML) and AI to enhance risk-based decisioning while delivering a low-friction customer experience during onboarding. Of course, this platform must be user-friendly with employees able to deploy analytical models that can be combined with business rules.

This means companies across industry sectors can act in real-time with the right balance of advanced automation and human oversight.

Connected customers want to see results immediately. However, they also want to feel that their data is safe. So, as companies are speeding up to meet customer demand, they must not lose sight of how their decisioning models and rules must evolve to keep up with the rate of change, the availability of modern technologies, and the evolving threat of cybercriminals.

Ultimately, without understanding their data, organisations will not be able to understand the customer journey and unable to differentiate between a legitimate and fraudulent customer interaction.

Doing more with their data, being smarter with their data, and understanding their data require an evaluation and revamp of decisioning models. From there, the deployment and the monitoring of decisioning become key.

The veritable secret sauce in this regard is having a unified platform that enables this.