4 minute read 1 Jun 2018
colleagues working together laptop cafe

How AI, blockchain can overhaul middle office

By

Lesley Keefe

Ernst & Young LLP Wealth and Asset Management Executive Director and EY Americas Asset Management Advisory Leader

Transformation thought leader in asset management. Innovator of new approaches to operating model strategies and designs. Team builder. Mentor.

4 minute read 1 Jun 2018
Related topics AI Blockchain

From trade operations to post-trade compliance, what makes or breaks a middle office is the veracity, management and delivery of its data.

A middle office is only as successful as its data. From trade operations to post-trade compliance, performance reporting to position and cash reconciliation, corporate action verification to broker reconciliation, what makes or breaks a middle office is the veracity, management and delivery of its data.

It is no surprise that asset managers are turning to innovative technologies to help them improve data quality, analysis and delivery from the moment a trade is ticketed. Today, technologies like blockchain, artificial intelligence and machine learning are facilitating the aggregation and management of large volumes of external and internal data — including both historical and real-time data — received from back-office platforms for reporting to portfolio managers, finance, risk, compliance, clients, regulators and others. Across this process, these technologies are transforming the middle office.

Using digital technology to automate historically manual middle-office data processes used to be a competitive differentiator. That is no longer the case. Clients are no longer wowed by massive data analysis and real-time reporting. They expect it. Gone are the days when a weekly or monthly spreadsheet report of trades was sufficient. Today, firms that cannot produce transaction information in real-time are at a market disadvantage.

It’s not only clients who are demanding real-time, high-quality data. Regulatory bodies are as well — especially on the global front, where dozens of jurisdictions and agencies present complex compliance requirements. As a result, middle-office managers, their staff and their systems must be adept at repurposing data to be flexible enough to comply with disparate regulations without having to custom-build reporting capabilities.

The technologies driving innovation

If technology is critical, which ones are enhancing quality, management and delivery of data, and driving middle-office innovation? Certainly, blockchain has received a tremendous amount of attention lately. And with good reason: It adds triple-entry efficiency and transparency to ledgering and reporting by creating a detailed, replicable and cloud-based copy of each transaction. But blockchain does have its own set of caveats. Whenever granular data is migrated to the cloud, security, privacy and ownership concerns arise, as well as control issues. When can information be accessed? By whom? When should it be masked? These are complex questions that middle office management may or may not be prepared to answer, and for which many firms are turning to outside experts for assistance.

Middle-o­ffice managers, their staff and their systems must be adept at repurposing data.

Other digital technologies making the conversational rounds in today’s middle office are AI, machine learning, deep learning and advanced analytics. Each is a subset of another, but all share one commonality. They can remove inefficiencies from middle-office data processes by turning over error-prone human activities to increasingly intelligent automation. Whether AI is solving email or other counterparty communication problems, these technologies are being embraced across the asset management realm.

Yet among these technologies there are myths to be dispelled. One of them is that they provide off -the shelf quick fixes. In reality, they take time to implement, customize and learn an organization’s systems. While an AI algorithm can be developed and deployed in just a few weeks, it generally takes months — and hundreds of thousands of data points — to raise its accuracy to an acceptable level.

A key success determinant of AI and similar technologies is, ironically, a human one. Since AI algorithms are written by people, the quality of any algorithm is wholly dependent on the skill level of the person writing it. That raises a critically important — and often deeply vexing — issue for asset managers: finding, hiring and keeping talented IT and operations staff. In a labor market, where gifted tech professionals lean toward more exciting disruptors and fintech companies, it can be difficult for a traditional financial services firm to recruit and retain the talent needed to digitize its middle office.

Seeking help

Transforming a middle office is not for the faint of heart. The dynamic and changing nature of today’s emerging technologies presents numerous potential pitfalls and risks of failure on multiple fronts.

Technology providers — both global custodians and nontraditional, specialty managed service providers — have already invested funds and resources into emerging technologies and service offerings. After all, their business model demands it. They have traveled the inherent learning curve, identifying and hurdling the inevitable potholes in designing and implementing such technologies for the middle-office space. And they historically attract more specialized talent than traditional financial services providers.

This article was originally published in the June 2018 issue of Fund Operations. It’s reprinted with permission.

Summary

As today’s middle office continues to transform, many asset managers are turning to outside providers to automate both commoditized accounting and more complex functions such as regulatory reporting and specialist asset classes — all in an effort to satisfy clients’ and regulators’ seemingly insatiable appetite for ever-better, ever-faster data management, analysis and delivery.

About this article

By

Lesley Keefe

Ernst & Young LLP Wealth and Asset Management Executive Director and EY Americas Asset Management Advisory Leader

Transformation thought leader in asset management. Innovator of new approaches to operating model strategies and designs. Team builder. Mentor.

Related topics AI Blockchain