Driving forward enterprise value and efficiencies with AI

There is no doubt that artificial intelligence (AI) has now become mainstream. The Collins Dictionary picked AI as the most notable word of 2023 because it “has accelerated at such a fast pace and become the dominant conversation”. ChatGPT4 certainly dominated headlines after it reached 100 million users in two months, making it the fastest-growing consumer internet app ever. AI now affects us all – whether as consumers or businesses – and is making an impact in every sector of the economy.

Traditional capital markets firms recognise the importance of using AI to improve how efficiently they run their businesses, as well as for innovating to add further value to their products and services. In this blog, we examine the different areas where Zodia Custody’s teams are using AI to improve the client experience, risk identification and drive forward enterprise efficiencies in digital asset custody.

Enhanced wallet security

Wallet security is at the heart of everything we do as digital asset custodians. Although blockchain analytics tools for analysing financial crime clustering and pattern analysis of public addresses have been around for almost a decade, Zodia Custody is taking this process to the next level by working with companies such as CUBE3.AI to implement an enhanced level of security and risk identification capabilities for our clients. Using pattern analysis for transaction and smart contract data, transaction-level or smart contract-level risk scores can be obtained, encompassing a number of risk factors such as smart contract exploits, token hijacking, rug pulls, phishing attacks, fake airdrops, front-running and so on.

Digital asset and Staking assessments

As a registered digital asset custodian, we place a very high degree of importance on only supporting well-vetted, credible digital assets, and ensuring financial crime risks related to staking models are identified, assessed and able to be mitigated. To enhance these processes, Zodia Custody is working with firms such as Metrika and Eunice to obtain data from whitepapers, as well as other on-chain and off-chain data sources. This helps us complete onboarding assessments more comprehensively for listing and supporting new digital assets, as well as in assessing new staking models.

Control testing and compliance

We are working on enhanced pattern analysis and tooling utilising Vanta to support us in developing control testing mechanisms and automatically associating pieces of evidence with controls for regulatory compliance initiatives including compliance with SOC 1 and SOC 2; complying with information security standards such as ISO 27001, and compliance with DORA for digital operational resilience.

DeFi risk assessments

Many digital asset clients want to engage in DeFi investing but this is an area where robust risk assessment is essential and complex. Deploying AI tools helps with vital tasks such as analysing the integrity of smart contracts and optimising liquidity conditions to ensure the best and safest outcomes for our institutional clients.

Operational efficiencies

Our team are using various AI tools to increase overall efficiency in how we run our day-to-day business operations, as well as developing our product suite to tailor services more effectively.  Sentiment analysis helps us to understand more quickly how clients are reacting to our products and to assess where we should be providing them with additional information. Summarisation tools also assist analysts in picking up queries – and AI tools can even suggest solutions to questions, freeing up more capacity across the team. Our legal team is using AI contract lifecycle management tools such as Evisort to streamline workflows, signing processes, draft clauses; all the while improving the user experience and saving time as the business scales.

Future possibilities for AI in the enterprise

Other areas where we could use AI to improve our workflows and speed up client services in future include incident triaging and using AI agents for swift incident response and resolution, as well as improving the onboarding experience by supporting swifter identity verification and KYC processes.

While some AI tools are admittedly not yet time savers and all of them require investments in training and learning, such tools are gradually freeing up the role of junior team members to carry out more value-added tasks rather than performing administrative work. Over time they are changing the future of work and will shift how we will train new employees joining the company.

AI – The evolution of portfolio management?

As large language models evolve and improve, digital assets and AI will converge more closely, opening up opportunities for greater personalisation of products and services. Custodians will have the ability to add value for clients by interrogating data sets and learning from them. Experiential investing will start to transform transactions into multi-dimensional investment opportunities.

What next?

In future capital markets, where we are likely to see a wide variety of tokenised asset types, demand for data processing aided by AI will increase. The ability to do machine learning based on on-chain data will be in high demand. Portfolio management will evolve to be driven by AI insights, unlocking the door to new business models and fresh opportunities for digital asset custodians and clients alike.

AI looks unlikely to stop dominating the business conversation anytime soon.