Data Security and Lending: Greenfield Opportunities

Abstract: The Canadian lending sector is rapidly evolving, driven by consumer-driven technologies and the forthcoming adoption of open banking. With the Buy Now, Pay Later (BNPL) market expected to reach US$11.30 billion, financial institutions must leverage digital solutions for competitiveness. Currently, Canada lacks a secure system for sharing financial data, exposing millions to risks. Advanced privacy-enhancing technologies and smarter risk-assessment tools are crucial for improving data security and credit decision processes. Rising mortgage debts and loan delinquencies highlight the need for digital transformation. Innovative tools for automated underwriting, real-time identity verification, and comprehensive risk assessment are essential for mitigating fraud, enhancing credit evaluations, and complying with regulations. Embracing these technologies ensures secure, efficient, and streamlined loan processing.

Canadian lending is transforming at an accelerated pace. With consumer-driven banking, high mortgage debts, and the growing adoption of Buy Now, Pay Later (BNPL) payments, expected to reach a staggering US$11.30 billion this year, there considerable greenfield for lenders, bankers, and fintechs. To capture it, financial service organizations must use digital and consumer-driven technology.

Open banking is on the horizon. Budget 2024 put the framework for what is also known as consumer-driven banking in place. Countries around the globe, from the UK to Australia to India, are already using open banking for its ease, speed, and customer-centric approach. Consumer-driven banking indeed facilitates quick and convenient lending, but it requires heightened data security.

No Secure System to Safely Share Financial Data

Currently, Canada seems to have no secure system to safely share financial data with service providers, and yet approximately 9 million Canadians are entrusting their confidential details to them. They are doing it through screen-scraping, exposing themselves to massive security, liability, and privacy risks.

Canadian bankers and lenders must focus on adopting open-banking best practices from award-winning, next-gen global examples. For instance, the 10th largest bank and lender in the world (in terms of market capitalization and asset size) uses exposed APIs to securely access customer information while preserving privacy during customer credit decision-making processes and approving loans within 10 seconds.

Solutions like this, which maintain privacy, are important, but those that enhance privacy, i.e., ensure there are no leaks to third parties, are even more crucial. The technology used doesn’t merely encrypt the personally identifiable information (PII) data of customers. It also anonymizes and tokenizes the plain text data. Since this is achieved using one-way irreversible polymorphic encryption, the data cannot be decrypted. Such privacy-enhancing technology makes it safer and more secure for Canadians to share financial information.

Adopting Smarter Risk-Assessment Tools

The recent adjustment in consumer loan rates also serves as another reminder to bankers and lenders to adopt smarter risk assessment tools. The ballooning bad loans and non-performing assets (NPAs) signal the urgent need for digitization. More Canadians are struggling with debt payments. Mortgage debt reached $2.14 trillion in August 2023, up 3.4% from a year before. Borrowers with large loans ($400,000+) have shown an increasing trend in mortgage arrears, particularly among borrowers with the largest mortgages ($850,000 and above). Credit card and auto loan delinquencies are also on the rise, even surpassing pre-pandemic levels.

Before it becomes a significant vulnerability, Canada’s banking regulator, the Office of the Superintendent of Financial Institutions (OSFI), has already urged lenders to reassess their mortgage risk management and underwriting guidelines, particularly about:

1. The borrower’s identity and background
2. Income verification
3. The underlying collateral process.

It’s clear: the mortgage market needs change, and regulation tech is ready with the answer. Technology already exists that solves all three, reducing fraud and improving creditworthiness decisions while helping borrowers secure loans from the comfort of their homes.

For instance, a tool that automates the underwriting process can reduce bad loans effectively. It can determine the value of the property being financed based on its exact latitude and longitude. It can accurately verify if the asset, such as a home or vehicle, is already used as collateral in other loans by the same person or by other people.

There are other machine learning ML-powered solutions that help financial service providers adhere to the key pointers that OSFI has emphasized and tap the opportunity present in the evolving lending market.

Enhancing onboarding: Search and match tools can pull customer information from a massive collated data pool in real-time and with accuracy. It becomes the first critical step: checking names and verifying customer identities before passing on the information to a business rule engine (BRE).

Advanced decision-making: These are not just plain vanilla identity checks. The tools perform additional checks to assess creditworthiness, like evaluating both the liabilities and assets of the borrower. Overall exposure is measured, too, to identify the extent of the relationship of lenders in the network of the entity.

Going beyond the current risk qualification mechanism, there is also a need for constant monitoring that has to happen on a large set of data, and that data must be accurate and correct for the customer risk score to be right. And the key to accurate risk scoring is supplementing the AI model of the tool you use with real-time data. Only by incorporating detailed and real-time risk assessments can lenders better ensure the stability and security of their loan portfolios, minimizing potential losses and enhancing overall financial health.

Thin-file consumers: Federated global search is extremely helpful in accurately assessing the creditworthiness of thin-file, new-to-Canada customers. With simple technology, Canadian lenders and bankers can know the history of a customer by requesting the information from their country of origin. They can inquire if the customer has been flagged in another country without breaking privacy localization laws.

From online KYC processes to instant credit decisions, from reduced fraud to guaranteed compliance, consumer-driven technology gives financial organizations teeth. They make smoother sailing for customers and solve the biggest challenges for lenders. Cost-saving, time-efficient, and able to meet the growing demands of Canadian consumers, technology is the vanguard for banks and lenders.

Managing risks like never before, they bolster fraud management, streamline processes, and make loan disbursement and monitoring less resource-intensive.

Author

Saurabh Job is a dynamic leader at the helm of global marketing and expansion efforts at Posidex Technologies, a deep tech pioneer with over two decades of innovation in the BFSI sector. Saurabh specializes in spearheading global growth initiatives and strategizing market entry. His extensive experience across various geographies and leadership roles has equipped him with a unique perspective on solving complex business challenges. With a fervent passion for AI, finance, and technology applications, Saurabh is dedicated to driving innovation and excellence within the industry.