Our Vision of Core Banking

We dared ourselves to imagine a world, where core banking is modern and is served by an ecosystem of microservices with a KISS (keep it sweet and simple) philosophy.

Features

Overview

Companies who choose us

We built a part of this future with
PE as a pricing engine.

PE can be

a single-purpose engine, or
an enterprise-wide multi-core-supporting pricing engine that banks have been dreaming about for decades.

PE explicitly is not

an analytical accounting/posting/booking engine
a workflow engine to manage authorization
and booking instruction
foreign exchange currency conversion
engine

Business Overview

PE supports the rapid development of products. Changing a formula is parameterization, and so is adding new accumulations of data - e.g. cumulative turnover over a period. There is no development necessary, let alone regression testing of the whole monolithic core banking system.

If your bank is struggling with:
- difficulties with implementing the creative product innovations that business needs to improve their numbers,
- getting a core banking system replacement out the door,
- scaling up a microservice architecture core banking system to support the complex products of a universal bank,
- moving away from legacy hardware or software platforms towards a cloud native environment, without a surprising cloud bill at the end of the day,
we are here to help.
‍
PE is a pricing engine built with an enterprise mindset that is:

Short Time to market

Flexible

New pricing rules can be created, tested and
applied in production rapidly. Changes to source systems will be necessary only if new source data is needed to complete the price calculations. Price changes are decoupled from the rest of the application architecture, massively reducing the complexity of regression testing.

No development

No development is necessary in PE in case of changes to or creation of new rules, or even the addition of new fields in the incoming data feeds.
If business (or the regulator) thinks of "just a simple new field" that they want to use in the pricing formula, this means only parameterization in our solution no matter what they think up. This is because we have no predefined, rigid structures.

No dependency

No dependency enforced or even expected on pricing parameters or data structures that makes integrating to existing data structures as simple as possible.
Our data representation is very open and flexible on purpose. We faced situations where it was difficult to match the bank's vocabulary to the wording and notions that exist in vendor products. We have no predetermined phrases for e.g. accounts/contracts/passive products/retail accounts/sme accounts/micro accounts. Similarly, we do not have predetermined phrases for customers/parties/retail or corporate/large corp/etc. These trivial things have proven to lead to serious challenges.

Pricing simulation

Perhaps the most exciting and forward-looking aspect of our solution is the possibility of simulation. We store all the information used for pricing and the pricing formulas themselves retrospectively, enabling what-if analysis going back in time. Or going into a simulated future using various made-up scenarios. An analyst can use all this information to come up with better pricing strategies, and an AI can be used to suggest better strategies optimizing for pre-set conditions (e.g. max profit, min churn, etc).

Cloud Native

Highly available

PE has no downtime due to:
-operating system or
-other infrastructure upgrades,
-new product launches,
-rule creation/modification,
-addition of a new formula, or
-a new field to PE.

Scalable

From a few thousand accounts
up to tens of millions of accounts.
Our pricing engine is scalable even during the day leading to lower operating costs. This is due to the technologies and development patterns we used in our solution.

Event driven

Apache Kafka is our preferred
integration technology.
Our solution supports sync or async decoupled integration via Kafka streams or REST APIs.

Infrastructure

We offer PE as an on-prem solution, as a SaaS, or both.
Built on top of cloud-provider supported managed services supporting multiple cloud providers, leading to minimal infra operations overhead and lower TCO.
We also support on-prem installations or even cloud-on-prem hybrid solutions.

Fast

Enabling the calculation of end-of-period closing prices of millions of accounts in 10-20 minutes.
‍Our typical response times are around 10ms regardless of the amount of data (e.g. number of accounts) or transactions per second. If you need more performance, you can scale up the underlying infrastructure.

Functional Overview

PE has an API that can be called to return a price for
simulation or booking

Prices are calculated using an extensible open expression
language with support for:

Multiplication/Division

Addition/Subtraction

Minimum/maximum calculation

The engine works with data made available to it

using data from the pricing API call

via streaming relevant business events to it

accumulating/building abstractions from business events usingthe same expression language

Pricing calculation logic can be set up on the GUI by non-programmers.

Roadmap

Arrangement Master
Product 360

Contact us today

We're here to help, whether you have a clear project plan and need the necessary resources to make it market-ready, or if you would like to consult with our experts to bring your project to life.

Our services