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Case study

Increased efficiencies through automation of loan operations processes

A leading global investment management firm with over $50 billion of assets under management (AUM) uses Eigen to more efficiently onboard and manage new loans.

The challenge

An increased volume of deals over the last couple of years had made continuing with manual processes unsustainable for the operations team at this leading global investment management firm. The bespoke nature of the loan agreements married with a rigorous internal review due diligence procedure meant that a single transaction could take many hours to process manually and involve several people. This time-consuming manual process was proving particularly challenging at each month-end close.

The Head of Operations needed a solution to scale-up onboarding and improve efficiency to cope with the increased demand on the team without compromising on accuracy rates. The solution requirements included integrations with existing downstream systems, so functions other than operations and treasury could also reap the efficiency benefits.

The solution

Having heard about Eigen from an industry contact, the Head of Operations requested
a custom demo of the platform. Impressed by how easy it appeared to upload credit agreements, label the fields and train the machine learning model to pull out the correct key terms, he signed up for a trial. During the trial period, the model created by Eigen was trained by the operations team to extract 40-50 key terms from 100 legacy loan agreements.

To determine accuracy, the team compared the data extracted using Eigen to the information they compiled manually. After further labeling and training within the platform, Eigen achieved accuracy rates on a par with those attained through manual processing. The operations team have found the platform to be user-friendly, and with the support of the Eigen team, have gone into full production within their desired timeframe.

“I would recommend Eigen to lending institutions with similar goals to ourselves, who are looking for easy-to-use technology to help them automate processes involving large numbers of complex documents. We’ve been able to achieve our goals without needing machine learning experience or support from our IT team, which has been great.”

Managing Director and Head of Operations – Global investment group

The results

The efficiency gains using Eigen have been significant, reducing the average loan transaction processing time down from three hours to one hour while maintaining the necessary accuracy rates. The Eigen platform has enabled the firm to automate several document analyses, data re-keying and cross-checking processes and eliminated the need for duplicate approval steps. Downstream efficiencies have been achieved via the platform API integrations that send data to other systems where it’s used and enriched by users in other functions.

Having successfully automated and accelerated loan onboarding and operations using Eigen, the firm is now using the platform to process derivatives contracts and is experiencing similar efficiencies. They have also used Eigen to reduce the cost and time required to identify contracts impacted by a change in standards and compile the data necessary to perform the remediation work. They plan on using Eigen to overcome other process and data challenges in the future.

66% Reduction in loan transaction processing time
50 Agreement terms automatically processed per loan
1:1 Data accuracy compared to manual processing