Appinventiv driving AI-powered tech revolution in legacy banks

Underneath the hype of fintech startups and the glittering new payment app, a much more important and profound technological revolution is being made. It occurs within the legacy banks of the world where the fundamental issue is training decades of mission-critical systems that think. To these institutions, the integration of artificial intelligence is not an upgrade at hand; it is a complex and expensive rewiring of the very architecture of the financial system.

The biggest barrier is known as technical debt, which is the large and entangled system of aging infrastructure that drives the world finance. These systems were reliable but they were never intended to interface with modern AI. This has resulted in a demand around the world of a special breed of engineer who is a data engineer, and a strategist who can work on old code and introduce new intelligence, a considerable skill that has been instilled in the 1,600+ strong Appinventiv workforce.

This is where intense engineering centers have turned out to be indispensable. Appinventiv has become notable with this complicated niche, where it puts teams of employees to work as translators between the new and the old financial world. Their job is not only about construction of algorithms, they need to shape secure data pipelines and develop custom APIs that enable current AI tools to engage with systems, which may have been written in pre-internet times, safely. As an example, their engineers have created AI-assisted models of loan underwriting, which can interrogate decades of customer data of a bank without undermining the core system.

It never comes down to a shortage of data, as banks have an abundance of it, says a senior fintech strategist. The trick is to ensure that that data is made available and beneficial to the intelligent systems without necessarily breaking the bank, both in literal and figurative senses. It is a surgery

but not a replacement. When these engineers manage to complete this "digital surgery," they are not only modernizing banks, but also future-proofing the building blocks of the economy.

It is a two pronged strategy, rooted in experience of managing over 3,000 projects, which is to strengthen the core and then add on top of it with innovation that is intelligent. They do not use a dangerously risky approach of the rip and replace strategy but rather their engineers start by developing secure, current data pipelines that can safely draw out the data in the old mainframe.

As soon as the data flow becomes possible, Appinventiv teams roll out a set of bespoke AI solutions to design a new and smart sort of nervous system of the bank:

To Customer Experience: They combine Natural Language Processing (NLP) models that process millions of customer service chats and calls, not only keyword searches, but also sentiment searches. This enables the bank to proactively screen at-risk customers with the precision that has not been possible before.

In terms of Security: Their machine learning systems to detect fraud are a large step up over the old rule-based systems. They detect small, atypical patterns in real-time on millions of transactions forming a dynamic and self-enhancing defense shield.

To be more efficient: Robotic Process Automation (RPA) is employed to automate thousands of repetitive manual operations, which handles more than 3 million API calls per day to some clients and releases human resources into more valuable endeavors.

This is an engineering-led, systematic way of doing things, and it gives old institutions a realistic way out. They do not need to make a decision between their trusted old systems and the benefits of AI. They can have both with the right IT partner such as Appinventiv.