Five techniques to redefine financial sector and reduce risks associated with data sharing

The present era is witnessing an overwhelming wave of digitalization across industries and verticals – and it is ushering in a new era of business. After the initial few shocks of digital disruption in banking and financial services – the financial sector is now leading the way in technology adoption for business success. Leveraging the best available technology to attain better operational efficiency is the way of business today.

And while the beckoning of a digital future is a reason to celebrate, reliance on technology carries associated risks – reputational, legal, and financial. In the past few years, as technology integration with financial services continues to rise, the possibility of fraud and the risk of financial crime has risen with it. And therefore, its time for financial institutions to focus on risk management and build a culture of vigilance and compliance with technology.

Banking and financial service sectors are waking up to using technology to alleviate the risk of fraud and improve data protection. Financial institutions lean towards emerging technology such as artificial intelligence, machine learning, automation, and the implementation of data sciences to enhance operational efficiency. But technology can do so much more than that.

In 2019, the World Economic Forum {SOURCE} identified five new technologies known as ‘privacy-enhancing techniques that can change the data sharing game:

• Differential Privacy – Adding noise to a dataset to prevent reverse-engineering of individual inputs
• Federated Analysis – Sharing only insights from data but not the data itself
• Homomorphic Encryption – Encrypting data in such a way that it may be analyzed but not decoded into the original information
• Zero-Knowledge Proofs – Users can prove their knowledge of a value without revealing the value itself
• Secure Multi-Party Computation – Spreading the data analysis across multiple parties such that no individual may see the entire set of inputs

Even though these techniques are not new, their relevance to the financial industry has just come to light. If leveraged correctly, these techniques can redefine the financial sector and significantly reduce the risks associated with data sharing. They have the potential to redefine the dynamics of data sharing in financial services fundamentally. It can enable different players in the financial services sector to work together to prevent illicit financial transactions, identify material risk exposures, and mitigate risk across institutions. Thereby, allowing the financial services industry to offer more personalized services, better financial advice, and products.

The benefits of one technology may easily be used to reinforce the limitations of others. It is imperative for FinTech companies, banks, and NBFCs to figure out the right mix of privacy-enhancing techniques for a targeted combination of privacy, security, and utility.

There are three essential advantages of using technology to navigate financial risk, prevent fraud and unlock new value by sharing data in new ways –

1. Unlocking New Value for Financial Institutions – Protected data sharing by combining Federated analysis, differential privacy, and zero-knowledge proofs can help financial institutions collaborate better. Combining all data sets into one encrypted central database can help catch duplicate claims and prevent fraud in financial services. This central database could also be queried/analyzed directly to arrive at the same insights that a federated analysis model could deliver, using differential privacy to ensure that the confidentiality of individual customers does not leak through the analysis.
2. Becoming a Trustworthy Custodian of Data – Banks, financial institutions, and FinTech companies amass many data about customers’ financial and non-financial attributes. Collaborative data sharing efforts with zero-knowledge proofs could turn the industry into a trusted guardian of customer data.
3. Unlocking New Value for Customers – Differential privacy can be essential in unlocking the value of the cross-institutional dataset that they aggregate. Differential privacy can be used to introduce noise into generating insights and ensure that the privacy of the individuals in the dataset is not breached. This would break the privacy trade-off, allowing individuals to benefit from personalized and specific financial advice while protecting the individual privacy of customers.

Financial firms have been quick to adopt digital technologies to keep their edge. But this disruption is changing the nature of risk and introducing new risks that might not have existed in the recent past. At the same time, digital technologies and processes offer financial institutions the opportunity to redefine business models and transform customer interactions by enabling them to prevent fraud, and also improve the data sharing to reduce financial risk.

Every financial institution needs to question its use of technology for cybersecurity and data protection. And they must strive for collaborative techniques that help build better customer experiences, a more resilient financial services ecosystem, and unlock their true potential to get fit for a digital future. The key lies in proactive technology adoption by the financial sector and successful implementation.

By Pratyush Chandramadhur, Chief Business Officer, Fintelle.