In the last instalment of our article series on machine learning we touched on the human elements and the AI interventions of the system we utilise to make our business efficient. The logical discussion point from that perspective is the risk-based approach we employ in our product functions.
The benefits of machine learning (ML) using a risk-based approach mean we can process many transactions quickly and on a wide-scale in a way that is largely automated, and this allows for a form of real-time document processing to take place, which in many ways speeds up the verification and approval process beyond human capabilities as it allows users our system to receive near-instant feedback as their documents are processed.
While our system parameters which define what an acceptable document is are sufficiently broad enough to deal with enterprise-scale volumes, they are also stringent enough to catch the things that should not go through. In the context of our risk-based analysis using ML “doubt” really just means “don’t.” And we adhere to that principal closely to maintain a standard of quality within our system.
In the validation phase, if the user provides us with an unacceptable document we can then reject the content quickly in a manner we call “fail-fast” which keeps the processing pipeline fluid, allowing a user to be informed that they must send us a new document while they are engaged in the process. We can keep users more satisfied in this manner as the document turn-around time is quick and the feedback instantaneous. And so to fail-fast when there is doubt is fundamental to our approach when using ML in our business.
While machine learning powers the volume and scale of the risk-based approach, it is the interplay between both the AI elements and our human users that determine the efficacy of the process. Since the ML side of the operation can match the engagement of the users in real-time it keeps the document queue numbers as low as possible as the majority of users complete the verification steps on their first session. If we were to rely only on a human back-office for these functions we would not be able to match the speed and accuracy we presently enjoy, and that is the power of this amazing technology.
#intergreatme #remotekyc #kyc # digitaltransformation #onboarding #knowyourcustomer #regtech #fica #rica
In our previous article we explored machine learning as a branch of artificial intelligence. In this article we will now look at how Intergreatme has deployed this kind of technology in our business and consider how it enables our products in light of the domestic regulatory environment.
Intergreatme has a responsibility for the security and upkeep of our platform around the clock. To accomplish this Integreatme has automated our document processing in a way that provides scalability to process large transaction volumes by embracing machine learning.
The machine-learning document processing occurs after we have collected key pieces of information. This is then coupled with information from what we call ‘golden source’ databases, like the Department of Home Affairs HANIS application programming interface (API).
When a transaction begins, we queue data which allows us to monitor the user journey from start to finish. This is done in order to identify transactions which require assistance, at which point they can automatically be directed to our human verification operations team to provide the necessary support which can be directed either to the user, or to our customers via our innovative Customer Insight Platform (CIP). At every step of the verification process, documents are inspected in real-time, resulting in near instant validation, verification, or feedback as the user uploads their supporting documentation.
The back office verification team also inspects transactions, ensuring that we flag transactions that are potentially fraudulent. What this means is that when our machine learning system cannot make a good decision, it refers it to a human being in order to make a final determination. This ensures maximum efficiency and compliance, and that our systems operate in the most balanced way possible.
While the significant advancements in artificial intelligence in the first 2 decades of the 21st century have laid the groundwork for much of the future tech that is on the horizon and that we benefit from right now, A.I. ethics, and ethical A.I. choice-making in the context of systems that interact with human beings remains a lasting and perpetual concern. Ethics in artificial intelligence is in fact such a concern that many futurists often refer to a soon to be reached kind of technological singularity which is yet to occur — a hypothetical point in time in which humanity’s technological growth exceeds the confines of its original design and becomes an uncontrollable and irreversible entity of its own cognition, resulting in unforeseeable changes to human civilization.
As exciting and as rather startling as that may sound, the present day FinTech and RegTech industries of the modern economy are closely allied in being on the frontier of some of the trends that are driving this kind of technology forward, but they are also ensuring that ethics and humanity stay an intrinsic part of the A.I. equation.
Machine learning is a branch of A.I. premised on the concept that a system, by conducting its own data analysis, which then in turn automates analytical model building can learn from data inputs. It can then identify patterns in that data, and then use algorithms to make decisions with a minimum amount of human intervention.
It sounds quite spectacular, but as we all know, the real world has a great amount of nuance to it, which machines are not very good at accounting for. When machines make decision based on probabilities, they are not really experiencing reality but operating out of a set of parameters, if their environment changes and evolves to behave in an unexpected way the AI certainly can and will fail to adapt to this or comprehensively deal with such a change. And the complexity of A.I. means that it can be really hard to determine why or if a machine made a mistake, and that mistake can have serious consequences for human beings.
In an adapting and changing world, it is logical then to consider whether locking a system to remain affixed to a set of rigid parameters that cannot change is preferable, or otherwise alternatively rather to consider granting that A.I. the ability to evolve somewhat, and this indeed is what machine learning is and does. When it can evolve it effectively enables A.I. the ability to autonomously deal with changes in its operating environment and expand its parameters to absorb and internalise those kinds of operating changes. And this is where consequence management becomes a big issue.
The decisions made by machine learning systems have real world outcomes: it can influence investment profits and losses, express biases in risk preferences, influence hiring decisions that can have ramifications that vastly exceed just the make-up of who a company employs, determine who is granted a loan or gets access to a medicine and who does not, and even lead to automotive collisions simply due to circumstances beyond the understanding of an A.I. system. This type of technology raises an abundance of ethical and moral questions which are complex and not easy to answer. But one thing is for certain, and that is that this is the future, and it is driving change in our modern economies, and it is happening right now.
When RegTech companies for instance take a risk-based approach in executing their product functions, this is a very good example of how tech companies make use of machine learning to make these types of processes quicker and easier for consumers. By engaging this form of probability analysis and then reducing the risk on a vast scale, it can have positive benefits for consumers, making the application process for many kinds of services and products more accessible and even democratised. Given the concerns that exist in allowing A.I. to evolve and adapt, it is perhaps the RegTech industry that has found the most eloquent answer to the moral and ethical dilemmas that seem to exist in artificial intelligence systems.
RegTech companies do actually have a model to emulate, they have successfully automated, but they have still kept their humans. So when anomalies do occur and are expected, the human elements still remain to pick-up on what the A.I. systems cannot. It is fair to say in the broad conception of RegTech and machine learning, some adjudication is by all means still required to enable an efficient and practical business workflow to exist. And it is at this juncture that perhaps, RegTech has the answer to the broader A.I. problem. Keep the humanity where it is necessary, to make the decisions that should be made by a human.
Of course the complexities of A.I. systems are not getting any easier or smaller, 20 years from now the world will have changed at a dizzying pace, but if we are going to face a future of increasing automation and greater surveillance, and the worries of some kind of singularity occurring, then keeping the human decision making element will remain a vital piece of that equation.
#intergreatme #remotekyc #kyc # digitaltransformation #onboarding #knowyourcustomer #regtech
Intergreatme is looking to hire two new developers to complement our existing team.
Essential skills are Flutter, and Angular. You will be working predominantly in Flutter (targeting iOS, Android, and Web) but might need to pull in some weight with our Angular projects.
Most of your work will be focused on the development of new technologies, products and services within the Intergreatme App.
A portion of your time will also be devoted to working on our Remote KYC solution.
We're looking for an individual with experience in Java (DropWizard is a plus), and a keen interest or experience with Go.
The candidate should have experience with unit testing, with CI/CD experience being a plus.
We make use of Docker, so experience with container technologies is necessary.
We make use of CockroachDB, so experience with Postresql is required.
Your work will involve building up an upgraded backend for our products and services under the guidance of our Solution Architect and Chief Information Officer.
Send your CV to [email protected]
In a year beset with far-reaching international disruption, and the market uncertainty the pandemic has caused, the one thing that has remained consistent throughout is the essential need for trust to be maintained between consumers and businesses. In the RegTech space COVID-19 has served as the progenitor for great innovation, and as driver of change and migration to digital platforms due to the need to ensure compliance and ease of use for the end user.
The types of change which have occurred in many organisations as a result of the COVID-19 pandemic have permanently altered their operating conditions. Whether it has been in the medical and legal areas, or the accelerated adoption of ID verification technology in government departments, online marketplaces or banking. Rapid digital transformation programs over the last 3 quarters have been essential to many businesses hoping to maintain operations throughout hard lockdowns in order to ensure trading stability as we move through this pandemic.
The speed of execution in implementing these programs has expressed the clear urgency to protect large numbers of consumers, and this has all needed to conform to the existing regulations like that of POPIA and the Electronic Communications and Transactions Act.
The pace of digital transformation and changes in consumer behaviour have accelerated trends favouring the uptake of ID verification across online marketplaces and the financial services sector far more than any other time in history, and in many instances these trends have resulted in business operations which have been subject to the regulatory pressures of compliance requirements while deploying and building new systems rapidly and at scale.
Maintaining a clean user-interface and eliminating cumbersome verification and sign-up processes requires delft planning and talent, maintaining a sense of trust and security is critical while instilling a great account opening experience. It is where these two elements meet that one encounters the power of user satisfaction. Make these processes too tedious or cumbersome, and consumers will lose interest quickly, and there will be a resultant low rate of adoption. In avoiding complexity, if you make these elements too weak, you will run likewise the gauntlet of falling short on compliance matters.
The end user experience must be seamless, or you run the risk of alienating your customers, who are the ones you essentially do need to impress.
The account opening process, from start to finish will make or break any future relationship between your customer and your brand. And that was the lesson many businesses came to learn this year.
Where there is a crisis there is also an opportunity, and while there is no certainty of what other future threats may await us in the medium or long-term, never has there been a more pressing case for businesses to prepare for the digital long-haul and not get left behind. Fortune favours the prepared.
#intergreatme #remotekyc #kyc #digitaltransformation #onboarding #knowyourcustomer #regtech
Intergreatme is a South African RegTech company which specialises in online identity management and verification, with a class-leading mobile application, web apps and a proprietary online business interface we aspire to provide innovative and cutting-edge solutions for the security and verification needs of 21st century consumers and businesses.
Through the deployment of our fast, secure and scalable platforms we place data fidelity and security at the heart of our systems, in fact the engine of our business is driven by the reassurance and fundamental trust that in everything we do and every decision we make is made in total compliance with the regulatory and legislative environment.
Our headline products are built on a foundation of invention, and have been custom built to perform to rigorous specifications.
Remote KYC (Know Your Customer) has been at the forefront of eFICA and eRICA, allowing South African enterprise to take a fully remote risk-based approach to their regulatory obligations.
Intergreatme for Business simplifies identity management with our proprietary mobile app. Enabling real-time identity verification, the creation of business forms with deep integration and the secure sharing of biographic identity information on demand, all done through remarkable innovation to deliver a secure and regulatory complaint solution which allows the end-consumer to completely control their identity while empowering businesses take a bold step into the future.
Great user experiences rely on intuitive interfaces and logical and thoughtful design aesthetics, and that is why we place as much emphasis on these elements of the user and business experience as we do on our security.
At Intergreatme we place the end-user and business consumers at the very heart of everything we do.
We specialise in making the technical and complex elements of RegTech systems simple and easy to use, to deliver world-class solutions and cutting-edge innovations which give our clients the reassurance of total regulatory compliance.
#intergreatme #remotekyc #kyc #digitaltransformation #onboarding #knowyourcustomer #regtech