Harnessing Real-time Decision Making on your Mainframe Platform

Enhance your transactions with superior performance, more efficient, and less costly to manage by integrating instant verdicts into your mainframe systems.

The center of a real-time business is the capacity to formulate instantaneous determinations – to determine which recommendation to give, whether to approve a claim, or allow a loan appeal the instant the client inquires. There’s a significant value proposition for real-time determinations and a set of established technology, including machine learning, business rules, AI, and determination automation systems. But have you ever examined disseminating your real-time determinations to your mainframe? And, if no, why not?

The value proposition of real-time determinations

Why yield real-time determinations? What’s the yield for committing to real-time? Four aspects consistently arise – better customer service, revenue expansion through cross-sell and up-sell, risk management, and expense reduction.

Better customer service

Your clientele desires instantaneous responses to frequently complex inquiries – queries where a high-quality response necessitates data analysis and compliance with rules and regulations. If you can address these inquiries and formulate these determinations instantly, you can facilitate smooth proceedings without requiring manual interference or forcing them to contact the call center, and they will perceive that you supplied better service.

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Revenue expansion

Immediate offers are accepted more readily. For example, an instantaneous offer of a car loan is much more possible to be received than one formulated after several hours. If you can determine that a potential client is a reliable risk and make them the offer instantly, you can nearly double your acceptance rates – from 15 to 20% to 35 to 40%! This signifies more profitable revenue for you. In addition, it illustrates that you’re enthralling the best clientele in each risk tier, not the ones remaining when everyone else has had an attempt at them.

Improved Risk Management

Managing risk utilizing predictive analytics and machine learning put into action instantly evaluates your risk transaction by transaction. Real-time risk decisions advance you ahead from after-the-fact portfolio analysis and place you on the offensive – acquiring the right risks at the right price.

Reduced expenses

Ultimately, real-time determinations lead to straight-through processing and hands-free transactions. This signifies reduced manual labor and thus less expense per transaction.

Elements of real-time determinations

Instant verdict services combine business rules, machine learning, and AI to execute a model of your decision-making that conforms to your business requirements.

Business Rules

The guidelines, regulations, guiderails, and restrictions that ensure your determinations are legitimate and appropriate are managed utilizing business rules management systems or determination platforms. This is crucial to supply the flexibility and responsiveness you require for rapidly evolving decisions, as well as the transparency you require for regulators and auditors.


Machine learning and other varieties of advanced predictive analytics ensure that risk is managed, fraud is diminished, and opportunity is maximized as part of your determinations. This use of ML to optimize determinations about core operational transactions is central to how ML provides value.


Generative AI and LLMs can considerably enhance your customers’ interactions with your real-time determinations. While they can’t be trusted to MAKE business determinations, they can help ascertain which determinations are appropriate, make it easier for customers to provide the necessary data, and then explain the results in natural language.

Decision models

Ensuring all these elements fit together necessitates a visual blueprint, a decision model. Defined by your business experts and based on industry-standard notation, decision models unify everything.

See also: Why the Mainframe is the Opposite of Legacy Tech

Why use the mainframe?

When organizations contemplate real-time decisions and implementing these technologies, they frequently ponder running everything in the cloud or on local containers. They seldom reflect on running this tech stack on their mainframe. Why should they? Well, real-time determination systems require all the common capabilities mainframes furnish for transactional systems, like availability, reliability, and security. Furthermore, mainframes frequently contain the first touch and most, if not all, of the data. In addition, they are high-performance and increasingly designed to accelerate this kind of processing.

First touch

Your mainframe is almost undoubtedly the first system that manages a transaction. This signifies that if it also formulates these real-time determinations, there’s no latency between transaction and determination. Anytime you have to wait for data to be moved off the mainframe before you use it, you introduce delay – you’re wasting time you could have used to respond to your customers.

Fresh data

The data on your mainframe is fresh. It’s not stale because it hasn’t been copied somewhere else yet. It might seem easier to access the cleaned-up and migrated data, but it’s just stale. This fresh data can be used in a hybrid transactional-analytic processing (HTAP) model, too. With HTAP, your real-time determination can run its machine learning and AI models directly on “in-flight” transactional data as it is stored. No more “after the fact” analytics.

Sponsored: Mainframe Data Is Critical for Cloud Analytics Success—But Getting  to It Isn’t Easy [Read Now]Sponsored: Mainframe Data Is Critical for Cloud Analytics Success—But Getting  to It Isn’t Easy [Read Now]

High Performance

Mainframes are high-performance beasts. Real-time determinations can become intricate, with numerous rules and multiple ML models to be executed. Your mainframe possesses the capacity you need to make these determinations occur swiftly. In addition, your mainframe team is almost certainly already delivering on millisecond service-level agreements.

ML and AI accelerators

Modern mainframes have machine learning and AI acceleration built into their chips! Seriously, hardware acceleration for advanced ML is a thing these days. Scoring transactions in the cloud can take up to 100 milliseconds. With modern hardware acceleration, executing a scoring transaction on a mainframe can be accomplished within just a few milliseconds. As you enhance your real-time determinations with more ML and AI models, this advantage is only going to grow.

But whattabout…

Three complaints seem to crop up every time customers think about mainframes for real-time determinations – cost, service level agreements, and rigidity.


The biggest complaint about running real-time determinations on the mainframe is that mainframes are expensive. Well, yes, each mainframe is expensive to acquire, but this doesn’t mean mainframes are expensive on a “per transaction” basis. If you have a lot of transactions already and you know you must process them all, then the scalability of the cloud isn’t buying you much – but the cost effectiveness of a mainframe is.

Service level agreements

People don’t want to run anything on their mainframe that might slow core transaction processes. For instance, they don’t want to do analytic model training or reporting. This is why all the analytic work is moved off the mainframe, so it doesn’t slow the transactions. Well, that’s fine, but that doesn’t mean you can’t execute developed analytic and machine learning models on the mainframe – you can just build them somewhere else at your leisure. Executing these models won’t break your service level agreements, not with the power and accelerators of a modern mainframe.

Too rigid and hard to change

If your mainframe is rigid and hard to change, if you can’t readily deploy new business rules to it or update it regularly with new machine learning models, then your IT team just hasn’t got the memo yet! Many mainframe teams have integrated the same CI/CD pipelines, business rules management systems, MLOps, and agile best practices as their cloud colleagues. A rigid and hard-to-change mainframe is just a choice – and not a very smart one.

Don’t waste that first touch

Make that first customer touch the best it can be by pushing real-time determinations onto your mainframe. Your mainframe is a vital platform for handling your core transactions. Make those transactions more profitable, more effective, and cheaper to handle by adding real-time determinations to your mainframe systems.

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