Todd Sloan, business development, SVP at Electra, says that the vendor is focused on helping Ops teams that “spend an excessive amount of time investigating exceptions,” and on related challenges.
(Todd Sloan, business development, senior vice president, Electra Information Systems, took time out of his schedule to give FTF News a progress report on Electra Information Systems. The provider of reconciliation and other post-trade solutions, Electra is the winner of the 2020 FTF News Technology Innovation award for “Best Reconciliation Solution” for the fifth consecutive year.)
Q: What impacts have the lockdown had on Electra’s client relationships and support?
A: The lockdown and ensuing remote work environments and general business uncertainty led firms to recognize the greater potential for operational risk caused by inefficient parts of their middle- and back-office operations.
We experienced increased interest in our SaaS solutions among both existing and new clients to enhance efficiencies across reconciliation, data aggregation and overall post-trade operations.
As for supporting our clients, we strengthened and thoroughly tested our company’s remote work infrastructure years ago in the wake of Superstorm Sandy, which enabled us to seamlessly switch to an all-remote workforce once stay-at-home orders began.
Although many firms experienced temporary slowdowns as they adjusted to remote work, business activity quickly returned to normal without disruption. One noticeable change is that our clients began working longer hours each day.
Q: Has the Electra Managed Services offering been getting more traction during the pandemic lockdown in 2020?
A: Yes. There is growing interest in Electra’s Managed Services offering for reconciliation and data aggregation, as many firms’ employees continue to work from home.
Firms are choosing Electra Managed Services to extend their own operations teams while leveraging our automated process to both eliminate immediate back-office stress and enable their operations to become more efficient over time.
Once the lockdown began, firms immediately focused on helping client-facing teams communicate with and address immediate and ongoing concerns of their clients.
This focus began to quickly shift to the middle- and back-offices and the important role they play to support these interactions while also mitigating risk and further losses.
Firms became concerned about the resilience of their post-trade operations in remote work environments in the face of increased back-office workloads and data volumes, and their ability to reduce the risk of multiple points of failure in an environment marked by unprecedented uncertainty.
Hence, firms experiencing growth or staff turnover were faced with two main choices: hire new staff, and train and support them remotely, or outsource some of the functions. They were also reluctant to hire new staff in remote environments where face-to-face contact is not as easy or efficient and makes it more difficult to learn from peers.
Based on our conversations with clients and others in the investment management industry, firms with operations teams of less than 10 people, or firms in the range of 40-to-60 total employees, appear to be the most strained right now. It is likely that asset management firms will face similar decisions about how they will allocate their operations resources in the future.
Q: Why is it important for Electra to urge investment managers to unite reconciliation operations and foster cross-team collaboration?
A: In hundreds of discussions with investment managers over the years, we’ve often discovered multiple reconciliation silos, minimal collaboration across teams, and limited visibility into the data needed to improve the situation.
Staff find themselves duplicating work already performed by their colleagues, leading to increased errors, lower productivity and unnecessary risks and costs. As transaction volumes increase, inefficiency makes it difficult to scale without having to add more staff.
Electra directly addresses these reconciliation and exception management issues by supporting all the reconciliation processes found across the middle- and back-office functions while also fostering collaboration across these areas.
Rather than viewing multiple reconciliation silos, management and operations staff have access to a single point of reference where the benefits of collaboration are obvious throughout the investigation’s workflow.
Q: What does Electra mean by the terms “root-cause analysis” and “intelligent integration?” What are the reconciliation benefits of these?
A: Investment managers’ operations teams spend an excessive amount of time investigating exceptions because they are viewed in silos across cash, transactions, and positions.
Often, multiple departments across the middle and back offices participate in the effort, leading to inefficiencies and high error rates, as well as increased transaction costs and operational risk. Much of the same work is repeated across different teams.
By intelligently integrating cash balances, transactions activities and/or positions onto one screen, operations teams can see, on that one screen, the root cause of a break regardless of where it occurred, as well as the break’s cascading impact on other exceptions it may cause or has caused. This eliminates redundant work across people, systems, and workflows.
Furthermore, firms can achieve greater cross-departmental collaboration automatically since Electra Reconciliation suggests possible reasons for a break by incorporating external data sources (such as failed trades, collateral held, pending trades, securities lending and corporate actions) which staff would normally have to access manually when researching an exception.
Q: How does Electra’s semantic-based fuzzy matching help reconciliation?
A: Fuzzy matching is crucial to reconciling transactions, and is often the only way to match assets that lack standard or reliable security identifiers such as over-the-counter (OTC) derivatives, loans, and commodities.
Firms need to able to increase the rate and speed of correct matches and decrease the rate of incorrect matches to process large volumes and scale to growth. But not all fuzzy matching algorithms are created equally; knowledge and understanding make all the difference.
Electra focuses on increasing auto-matching and decreasing false matches by using semantics that recognize the meaning of words to pair transactions and support subsequent reconciliation activities.
In contrast, solutions that use syntax-matching only examine characters and sentence structure, creating an increased risk of false matches.
Our semantic-based approach enables firms to prevent false matches that occur in other algorithms, and find more matches that they wouldn’t otherwise find.
For example, syntax-based matching would incorrectly decide that the custodian security identifier “Sam’s Club 3.375” is the same as the manager security identifier “Sam’s Club 3 ¾.”
However, a fuzzy matching tool that uses semantics interprets the identifier before trying to match it. That means it is able to understand that 3 ¾ is the same as 3.75, but not the same as 3.375, and therefore recognizes that this is not a match.
Q: What is Electra’s approach to artificial intelligence (A.I.) and how it is evolving?
A: While some progress has been made in the financial services industry, one cannot assume that A.I. and machine learning (ML) algorithms will fix every problem — especially complex problems investment managers face every day.
Instead, people must always play a key role in the A.I. equation to yield the most benefit. This is why Electra’s approach is evolving toward intelligence augmentation (IA).
Although the underlying technologies that fuel AI and IA appear identical, they are quite different: A.I. looks to build solutions without human involvement, while IA attempts to build solutions that uses the experience of humans and empower them to get better at their jobs.
Take failed trades, for example.
Through our experience thus far, we know there is a big difference between A.I. determining the reason for a failed trade, and IA detecting the likelihood of a trade failing based on a range of conditions and data such as collateral held, securities lending, or stale settlement instructions.
The approaches A.I. and IA take are fundamentally different. Would you rather find the root cause of fails that already happened, or reduce the number of fails and reconciliations? Both are equally important, but the latter is the ultimate goal.
Electra’s IA approach combines the latest A.I./ML technology, incorporating human experience and A.I. learning, with several decades of buy-side operations knowledge and experience in mapping and normalization to optimize the A.I. component that drives process improvements.
We established an AI Research Lab to explore industry use cases and pioneer models, statistical and ML tools, computational algorithms, and software to address the specific challenges that arise in buy-side markets.
Q: What can we look forward to in 2020-21 as far as new offerings and enhancements from Electra?
A: With the goal of empowering buy-side firms to surmount the complex challenges of efficiency, integrity and scalability amid difficult market conditions, Electra is focusing its initiatives for 2020 and into 2021 on driving lasting positive change in the areas of reconciliation and post-trade operations overall.
These initiatives include the following:
- Database application programming interface (API): Electra now provides secure access to reconciliation data by enabling integration with external client systems. Clients can connect their back-end systems to the Electra Reconciliation database, giving them the ability to use their own dashboards and other monitoring systems. In the future, we’ll be making the underlying API for Electra Reconciliation available to third parties including the possibility for white-labelling. This will allow providers of accounting platforms, collateral management systems and others to take advantage of our advanced reconciliation engine.
- Event Automation: New automated workflows that enable users to define event triggers relating to specific user-defined scenarios and take actions such as API calls, script calls or email notifications using robotic process automation (RPA) integration.
- Enhanced N-Way Reconciliation: Electra Reconciliation’s true N-way reconciliation will be enhanced to allow for non-uniform rules across different platforms and automatically act on specialized behavior requirements. N-way comparison will include aging, commenting, auditing, routing, and reporting of breaks found in the N-way reconciliation workspace. This workspace will leverage Electra’s patented intelligent integration capabilities to expedite the root-cause analysis between two reconciliation sources. When any two sources are highlighted, the intelligent integration functionality will be invoked to identify potential position, transaction or research records that may help to explain the origin of an exception.
- A.I. Research Lab: The goals of Electra’s A.I. Research Lab are to pioneer models, statistical and machine learning tools, computational algorithms, and software to solve omnipresent challenges in the buy-side community. The lab’s team, with the help of outside consultants, combines expertise in core areas such as ML, IA, optimization, data science, and algorithms with a deep understanding of financial markets and institutions to make fundamental advances and bring them to the community as market-ready tools.