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AiThority Interview Series with Stuart Brock, Director at Seal Software

Stuart Brock, Director at Seal Software

The need for systems that deliver extremely low latency, are highly scalable but are also simple to use has been the driving force in the decade-long move toward digitization.

Know My Company

What does Seal Software do?

Seal Software addresses a range of use cases, across bank type (retail, wealth management, investment) and across function (legal, regulatory, trading, procurement, institutional clients). After working with these clients for a number of years it is clear that their level of sophistication and knowledge of this area is increasing, and they are seeing contract analytics as a key technology to help them work towards the highest levels of compliance, risk management and contract visibility.

Can you give me some background on Seal Software.

The Financial Services (FS) industry has historically been in the vanguard of technology adoption. Second only to the military, financial services is the next industry to seek competitive advantage by both developing and implementing advances in computing and high technology. In the last 15 years, technology adoption has been under the umbrella of digital transformation.

Since the time that trading platforms became digital, the rest of the financial services industry has rapidly followed; the result of which is that manual processes are being replaced by automation in every operation and function. It is no surprise that financial services companies are at the forefront of Artificial Intelligence (AI) adoption and look to automate as many manual processes with Machine Learning and other AI models as quickly as possible.

Read More: AiThority Interview Series with Dr. Michael Green, Chief AI Officer at Blackwood Seven

What is your role at Seal?

I’m a director who helps lead Seal’s financial services programs. As a licensed attorney, I practiced law at a top national firm for a decade before moving in-house at Bank of America where I held various roles within the legal, compliance, and procurement organizations.

What have been the driving forces for industry innovation and what needs does Seal address?

The need for systems that deliver extremely low latency, are highly scalable but are also simple to use has been the driving force in the decade-long move toward digitization. These principles hold true for the majority of technology implemented in the financial services industry. Few other industries collectively grow as quickly.

The financial services industry growth has been achieved through the exploitation of split-second opportunities in trading conditions, through the scaling in terms of people, through rapid introduction of new products as well as driving a culture of digital transformation across all functions. The global financial services market is estimated to be north of $10 trillion.

What are the key factors to this innovation and what industries are most affected?

While digital transformation is high on the agenda of most banks and is a key ingredient for growth, there is also a recognition that these initiatives cannot be done at the expense of regulatory compliance, legality or even ethics. Except for the pharmaceutical industry, financial services institutions are arguably the most highly regulated. In fact, banks spend a mind-boggling $270 billion annually on compliance.

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What do you see as some of the key topics that need to be addressed and why?

Risk management and compliance are certainly key topics for the leadership teams of all financial services companies, and the regulators have sharp teeth. Fines for non-compliance and wrongdoing have spiraled over the 10 years since the financial crisis and have totaled more than $321 billion.

How does Seal see the importance of contracts within the financial services industry?

Given the criticality and legal status of contracts within the financial services sector, it is perhaps surprising that the adoption of technologies to truly understand the contract corpus has not been more significant. Contract lifecycle management systems have been around for many years and have done a relatively good job of corralling legal documents into some sort of centralized repository while putting some basic descriptive data (metadata) around them. But many contract lifecycle management systems have been undermined by serious limitations.

  • Firstly, the creation of metadata has largely been a manual process and has been more honored in the breach than in the observance.
  • Secondly, the systems have been limited to a process focused on the creation and warehousing of contracts, but the ability to derive insight out of the content itself has not been available.
  • Thirdly, the proliferation of cloud storage, use of file servers and distributed departmental decision-making has resulted in highly fragmented storage of contracts. For many organizations just knowing where their contracts are in the first place is a challenge.  The option to analyze the contracts is beyond most, except when forced to by a compelling event that is usually some regulatory requirement.

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What kind of volume are we looking at in terms of what you are addressing?

Contracts are the life-blood of any organization, whatever their size. Nothing of significance is bought or sold without a contract. Contracts can range from a single sheet of paper to the voluminous multi-hundred or even thousand-page variety. Their complexity can similarly range from the simple to the highly complex, often involving large teams of lawyers negotiating on both sides of the contract.

In the financial services sector, the sheer quantity of contracts across the business lines can be staggering and exist in every function, from procurement to trading, from retail banking to wealth management. Many Tier 1 and 2 banks have in excess of two or three million contracts. Those contracts represent opportunity, they represent obligations, and they represent risk. They contain semi-structured data that if harnessed correctly can surface obligations, potential exposures and help in the quest for better compliance.

Do you have a use case example of Seal Software in practice?
  • We have a number. For example, a global, multi-faceted top 20 bank has implemented Seal in a number of applications, across different business units. Perhaps the most effective pertains to the process for onboarding clients to new offerings. Let’s say you are an institutional provider like Fidelity for example and want to add a new offering — say, derivative trading — to your portfolio. That process has historically taken between 30 and 60 days to complete, mainly due to the checks and balances around performing a credit and risk assessment, a manual process involving specially trained risk officers.
  • In the old process, those risk officers manually review the application, and all the additional submissions, clarify key points in a back and forth process, and then make a go/no-go decision. As you can imagine, a 60-day process to approve new offerings is unlikely to be acceptable to either the bank’s customers or the institution itself. The net gain reported by the customer here is that Seal drove the time-to-decision (approval or rejection) down from a high of 60 days to an average of 2 days, improving customer service for important institutional investors, and accelerating time to revenue for the bank.

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What are some of Seal’s specific solutions or products?

Cross-industry research suggests that while many large organizations are still not using AI, the ones that do use it are seeing benefits. AI platforms often disappoint because most do not come with pre-built accelerators. Rather companies are required to build the technical and subject matter expertise to build the AI models for specific use cases. The need to help the client onboard AI technology is something Seal recognized several years ago, and a series of accelerators were released to speed deployment and improve the chances of a successful deployment. In Seal terminology, these are called Insight Accelerators to emphasize that they are not focused on just extraction, but also on delivering insight and answers from the start.

The Insight Accelerators are focused on specific use cases both within the financial services sector and cross-industry operations. Each of the Insight Accelerators contains pre-built analytics that identifies key clauses in contracts relating to broad topics and more specific subtopics, relevant to the use case.

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The Good, Bad, and Ugly about AI that you have heard or predict…

As I see it, 2019 will see AI at the crossroads, when companies are better able to skim the hype from the reality, and when AI can be applied for both the good and the bane of humanity.  It’s clear that AI has now gone mainstream and the benefits from using it are well known and vast, but people have also learned that any system needs teaching.

Data ownership will remain a massive issue and one that will just get worse, as we go into the smart contracts world, with data living on or in chains or immutable (or close to) data stores. Destruction events will become a requirement and any ledger will need to show how this can be done and be audited accordingly.

The good news is that the building blocks are in place for a new era in AI, when AI systems are capable of learning complex tasks with little human intervention. While dramatic claims about the future of AI ring alarms, I’m convinced the year ahead will also highlight our capability to innovate in substantially positive ways and the quality of change AI can bring to our lives — safe roads, clean oceans, and predictive healthcare to name a few. We are still, after all, the master of AI’s destiny.

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What role will Seal and AI play with the adoption of technology across the financial services industry?

The financial services industry, with its high level of regulation and voluminous contract counts across many lines of business, must continue to embrace technology to maintain regulatory compliance and economic efficiencies. The chosen technology must provide ease of use and tangible benefits. Seal combines deep subject matter expertise (employing many attorneys that practiced in the financial services space) with a cutting-edge and agile AI platform.

AI is a hot topic in the technology industry and Machine Learning is in the vanguard of practical application and tangible ROI. However, not all ML is created equal and Seal’s approach to multi-layered models is proven to be highly effective. The key point is that while identifying specific clauses and surfacing them has significant benefits it is by providing insight out of that data that takes it to another level.

Seal delivers answers to the burning topics of obligations, opportunities, risks, and so forth that are encapsulated in those key documents and contracts. That is why the largest and the mid-sized financial services firms are turning to Seal to empower their decision making.

Read More: TIBCO Continues Leadership Among Data Science and Machine Learning Platforms

Crystal Gazing

What AI enterprise solutions are you personally following?

Many, but most specifically the financial services industry. With its high level of regulation and voluminous contract counts across many lines of business, financial service providers must continue to embrace technology to maintain regulatory compliance and economic efficiencies. The chosen technology must provide ease of use and tangible benefits.

Do you have any insights you’d like to share on where the market is heading in the future?

AI is a hot topic in the technology industry and Machine Learning is in the vanguard of practical application and tangible ROI. Stunning breakthroughs will result from the use of Natural Language Generation (NLG) and Natural Language Understanding (NLU) to auto-teach AI learning systems. As the year progresses, we may learn about AI breakthroughs by computer scientists who are using NLG and NLU to auto-teach AI learning systems.

While unsupervised Machine Learning algorithms such as Generative Adversarial Networks (GANs) are already used to perform more simple tasks, computer scientists are now on the road to making progress that allows for “one-shot” learning with contextual data like contracts, speech and video. We’re likely to see a single example used, with NLU and NLG automatically generating new but valid items to learn from — and thus, auto-improve the models.

Read More: An AI-Based Robotic Machine Arrives to Combat Mosquito-Borne Diseases

Thank you, Stuart! That was fun and hope to see you back on AiThority soon.

Licensed attorney responsible for third party global contracts strategy, templates and risk assessment. Previous experience in enterprise compliance, in-house legal and litigation.

Seal Software

Seal Software is the leading provider of contract discovery and analytics. Seal enables companies around the world to manage their contract portfolio by understanding exactly where their contracts are and what is buried within them, maximizing revenue opportunities, mitigating risk, and reducing expenses.

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