Financial institutions must turn to new AI, encryption, and web3 storage technologies to keep customer data safe, argues OmniIndex CEO, Simon Bain
Criminals successfully stole over half a billion pounds over a period of just six months in 2023 through fraud, according to new research from UK Finance. The threat of fraud, coupled with the various regulatory demands placed on banks and financial institutions, means protecting customers and their data from outside threats is an increasingly tall challenge.
Ensuring that this sensitive data remains encrypted and protected, while still being able to draw insights from it, is crucial. According to Simon Bain, CEO at OmniIndex, achieving this can help banks and financial institutions unlock huge potential and limit the threat of fraud and other criminal activity.
“Insights from financial data can drive profit and improve customer satisfaction. However, the most valuable data is often encrypted and siloed due to its highly vulnerable and regulated nature and is therefore unavailable to analytics and other productivity solutions,” Bain explains.
“The finance and insurance industries have strict regulatory data compliance needs, as well as stringent security measures. Not only will leaks lead to damage to reputation and customer relationships, but businesses that fail to keep customer data secure will be hit with huge fines.
“Across the market currently, data is stored away from users and criminals with traditional models like in-house servers and hybrid-cloud technology. These systems have meant that it is currently difficult to run queries and analytics on data because it is often compartmentalized and siloed with the most valuable data encrypted and not added to the workflow. What’s more, secure and simple sharing between departments is not always possible as a result, causing a reduction in both long-term data monetization and day to day efficiency with crucial information taking additional time to access
“Through the use of web3 technology and innovative homomorphic encryption, computations can be performed on fully encrypted data, providing actionable insights without exposure. This technology makes it possible to securely and easily add encrypted data to other tools that can use it to create live data visualisations and dashboards. These can then be shared with your team and between colleagues so the insights can be actioned without the source information ever being readable and exposed to anyone at all.
“For example, you can use a Small Language Model (SLM) to perform real-time AI analytics of the fully encrypted data round the clock to identify patterns and anomalies in the data which could reveal potential fraud. As the data remains encrypted at all times, the insights can help combat these threats without the sensitive and confidential information ever being readable or vulnerable to exposure.
“The use of AI is simply impossible with legacy systems because of the regulatory and confidentiality needs of this financial data, however by using the innovative Web3 and fully homomorphic encryption technologies available today businesses can really start to tackle some of the biggest threats to customer data today. “The potential applications of this technology are not limited to fraud detection but also include risk mitigation and regulatory compliance, real-time customer sentiment, quality control, and insight generation including for new product development.”
