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The New Model for Managing Collateral


In this article co-authored by DigFin, we explore how technology is creating new opportunities for banks in APAC to make lending more customer-friendly, cost-effective, and capital-efficient. We look at how digitization of collateral management and regulatory pressure is driving a new model for managing collateral.

Credit is at the heart of finance, and the key ingredient of credit is collateral: the assets that lenders can seize if a borrower defaults on the loan. Collateral is often an underutilized resource, however.

Going beyond the Day-One loan-approval process, technology is turning this model on its head, creating new opportunities for banks to make lending more customer-friendly, cost-effective, and capital-efficient. Successful banks are elevating collateral to become core to the management of a loan throughout its life.

Two forces are driving this change: digitization of collateral management and regulatory pressure. Authorities are already beginning to improve their powers of supervision by zeroing in on collateral. This trend is not restricted to Western banks: it is coming to bear on Asia Pacific, with regulators in Australia revamping their collateral rules.

“Regulators are moving from looking at loan documentation and reports, to looking at the underlying credit-risk data,” said Luke Nestor, creator of COLLATE, a digital collateral-management platform recently acquired by Broadridge, where he is now business development executive.

Australia Leads the Way

The Australian Prudential Regulation Authority (APRA) promotes the stability of the financial system by surveilling banking, insurance and superannuation. In 2019 it drafted proposals to rethink credit market risk across the entire lifecycle of a loan transaction.

APRA’s proposals put a heavy focus on the collateral taken by deposit-taking institutions. The regulator wants to require the independent valuation of collateral, including the expected time it takes to realize its value, and a measure of the vulnerability of loan collateral to external events such as drought or flood.

Meeting these new reporting standards will require Australian lenders to shift from traditional paper-based credit reporting to a more data-driven, analytics-based approach. While the banking industry is still negotiating with APRA about how to value and classify collateral, the direction has clearly been set for modernizing this aspect of the industry.

This regulatory evolution is accelerating the way in which technology can reimagine lenders’ treatment of capital.

Collateral Gets Complicated

Collateral management has traditionally been a sidebar in loan management. Often handled manually via banks’ core systems, dispersed and disjointed collateral management usually results in inaccurate and gappy data that is not maintained through the life of the loan.

Liquid markets also have an important collateral management aspect, because the underlying values change from moment to moment. Not so for commercial lending, especially if the collateral is illiquid. In this case, collateral might involve titles to lands, or to ships or aircraft, or other assets owned by the company such as intellectual property rights. Loan collateral can be very idiosyncratic, making its management a process requiring specialist skill and technology.

Corporate structures further complicate collateral management, with parent corporations and subsidiaries with multiple balance sheets, cross-guarantees, subsidies, and parent pledges. Large corporations maintain armies of lawyers to keep track of it all. Whenever an arm of the corporation wants to take out a loan, it can take weeks for a bank to work through all of this complexity and distribute funds to its client. Doing so also requires a large, expensive remediation team.

Fragmented and dispersed collateral systems with a heavy manual component makes for a bad customer experience. And it’s already too cumbersome to keep up with regulation. “Regulators want to see a bank’s entire operational risk in taking and perfecting collateral,” Nestor said. “They want to see the data, how it ties to the loan, and use that to understand the relationship between the collateral and the borrower.”

Turning the Model on Its Head

This promises more headaches for banks. Unless they adopt a data-first approach to collateral management. What if, instead of waiting for a loan application driving the collateral due-diligence process, banks could assess a corporate client’s collateral up front, and then work out what kind of products to offer?

“Banks are realizing the strategic imperative to better manage their lending processes,” Nestor said. “Collateral and its perfection is important at the point of origination.” The role of collateral goes beyond that day-one scenario, though, and requires management through the life of the loan.

The strategic value to the bank is clear: in terms of reduced risk-weighted assets (RWA), availability of granular data sets for a range of regulatory reporting, and easier transaction management and monitoring, from payout to collection.

Automating this process end-to-end with a platform like COLLATE helps lenders legally secure transactions, ensure lifetime environmental risk assessment, and maintain collateral valuations – even without manual inputs from appraisal companies, since big-data indexes can deliver the same service automatically.

COLLATE is not just processing software: it connects to multiple data sources to bring a holistic, lifecycle view of collateral to the fore. “We supply the automation and data for rigorous collateral management through the life of the loan,” Nestor said. “Our system delivers the data integrity that supports risk analytics and reporting in the loan book.”

The biggest benefit for banks is in the cost of capital. Maintaining remediation teams to manually manage loan data so it can be reported is expensive and repetitive. Poor-quality loan data negatively impacts a lender’s cost of capital, its risk-weighted assets, reserves and loan-book management.

“Straight-through collateral-data processing means less need for big remediation teams,” Nestor said. “Banks can confirm the collateral data early, maintain it automatically, and save on capital” as a byproduct of automation.

A data-first approach makes the lending process efficient, which means funds can be disbursed to clients faster, costs are reduced, and the entire trail is ready to audit. COLLATE enables banks to offer quick decisions to clients while also bringing down their cost of capital and making regulatory reporting easier and more robust.

This article was published in DigFin on 9 September 2020.

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