Risk Management Can Only Get Better
The Role of Emerging Technologies
In a recent blog post we discussed how ransomware is impacting businesses and what can be done to fight back and make cyberattackers’ lives miserable. Let’s now talk a bit about risk management in general.
Risk management is a complex thing — be it financial, legal, operational, regulatory or reputational, you name it — and current practices involve plenty of friction. For starters, workflows bring together multiple parties with their own legacy processes and systems, and typically involve data coming from a number of sources, with reconciliation often including manual processes that are not only costly and time-consuming, but they also slow down critical processes and are prone to error.
So, how to get better at dealing with risk? We recently held a webinar in partnership with Digital Asset and The Demex Group to talk about a very specific use case that is climate risk, and how that affects certain businesses, as well as how these businesses can leverage emerging technologies to better manage risks caused by weather.
Being Predictive and Proactive rather than Reactive
One thing we highlighted at the above mentioned webinar was that regardless the type of risk, arming organizations with the ability to be predictive and proactive, so they can decrease the severity of an event — e.g. a cybersecurity risk, natural disaster or system failure — before it happens or prevent the event from ever happening, will not only save them money, but also reduce the stress caused by this type of threats, and help them avoid compliance violations as well as damage to their reputation. With reactive risk management, you are always at least one step behind the threat.
For example, as discussed in my previous post about ransomware, by implementing a blockchain-based distributed file system, you can proactively protect your business-critical data, minimize the risk of a cyberattack, and save yourself from devastating consequences.
Interplay of AI, Distributed Ledgers and Smart Contracts
Emerging technologies can be applied to address a wide range of risk management related pain points. As discussed on the climate risk webinar, distributed ledgers can provide the needed trust layer by establishing an immutable, single source of truth, while smart contracts are used to formalize and automate the relationship between stakeholders involved in the risk management process. The aggregated data also serves as the basis for AI algorithms to more accurately and efficiently identify financial, operational, regulatory, and external risk factors.
An interesting aspect of distributed ledger technology (DLT) overall, is that while activities enabled by it — such as the transfer of digital assets — may be subject to laws and regulations, DLT itself can be leveraged for a number of legal and regulatory compliance use cases. For example, DLT can help improve current reporting and enforcement processes, by making them more transparent and efficient.
A very specific use case where AI and DLT capabilities go nicely together is the fight against doctored documents and images, as well as deep fake videos. Insurance companies have been using data analytics for fighting digital fraud, but as the sophistication of fake data and media technologies grows, fraud detection and prevention tools also need to improve.
Imagine having a file — whether that is a document or other type of media such as image or video — fingerprinted to a distributed ledger, with validation occurring in real time, determining whether that file is authentic or has been tampered with. Based on all that information, organizations can devise an action plan.
Whatever the risk factor is, we are definitely not in a bad place where AI is providing the brains, distributed ledgers are establishing the trust, and smart contracts are formalizing the relationships and automating processes.