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Razvan Codis

Principal Advisor at Codis Consulting

Sydney , Australia

I design the governed decisioning layer that sits above the platforms — the architecture that turns model outputs, business rules, regulatory constraints, and competing priorities into one explainable outcome, in real time, across channels.

Whether it's approving a loan, routing a service case, or choosing what to show a customer, the architecture is structurally identical. What changes is the domain, not the pattern.

I've designed and delivered this layer across tier-1 banks, insurers, and government — spanning credit risk, operations, and customer engagement. Most recently, I built Emirates NBD's real-time interaction management programme from scratch: 42 live use cases, eight channels, governed production capability with measurable commercial impact.

Author of a peer-reviewed thesis on decision management in banking (2,000+ downloads). Formerly CBA, NAB, Westpac, Suncorp, and Pega.

razvan101@gmail.com

Available For: Advising, Consulting, Speaking
Travels From: Sydney, Australia
Speaking Topics: Real-Time Interaction Management, Next Best Action Decisioning, AI Operationalisation in Banking

Razvan Codis Points
Academic 30
Author 7
Influencer 0
Speaker 0
Entrepreneur 0
Total 37

Points based upon Thinkers360 patent-pending algorithm.

Thought Leader Profile

Portfolio Mix

Company Information

Company Type: Company
Business Unit: Advisory
Theatre: Asia Pacific / Middle East
Minimum Project Size: N/A
Average Hourly Rate: $200-$300
Number of Employees: N/A
Company Founded Date: 2010

Areas of Expertise

Agentic AI 30.03
AI 30.08
AI Ethics
AI Governance 30.06
Analytics 31.51
Architecture
Customer Experience 30.38
Customer Loyalty
Digital Transformation 30.04
Finance 30.13
FinTech
Future of Work 30.02
Generative AI
IT Strategy
Marketing
Predictive Analytics 30.43
Risk Management 30.03
Transformation

Industry Experience

Financial Services & Banking

Publications & Experience

1 Masters Degree
Decision Management for Next Best Action in Retail Banking
University of Technology Sydney
December 31, 1969
Peer-reviewed research thesis examining NBA decisioning frameworks in retail banking. Explores arbitration logic, proposition prioritisation, and the operationalisation of AI/ML models in real-time customer engagement. Published via UTS OPUS. 1,700+ downloads.

See publication

Tags: Analytics, Customer Experience, Predictive Analytics

2 Miscellaneouss
From Database to Intelligence: The Evolution of Marketing Decision Systems
LinkedIn
December 31, 1969
Traces the evolution of marketing decision systems from database marketing to AI-powered real-time decisioning, and what it means for how organisations engage customers today.

See publication

Tags: AI Ethics, Analytics, Customer Experience

Stop Building MarTech Backwards: Why Strategy Must Drive Technology, Not Follow It
LinkedIn
December 31, 1969
Most organisations deploy MarTech as an IT infrastructure project then wonder why adoption is low. Strategy has to come first — technology amplifies direction, it doesn't create it.

See publication

Tags: Digital Transformation, IT Strategy, Marketing

4 Posts
Andrew Ng’s AI Engineering Skills Map: What Enterprise Leaders Should Notice
LinkedIn
August 29, 2026
Andrew Ng’s AI Engineering Skills Map identifies four increasingly important capabilities: building and deploying AI applications, software-engineering fundamentals, working effectively with coding agents, and shaping what gets built. This article examines how AI is shifting value from code production toward problem definition, architecture, evaluation, product judgement and accountable enterprise deployment.

See publication

Tags: Agentic AI, AI, Future of Work

Why Banks Can't Just "Deploy and Pray" with Next Best Action Models?
LinkedIn
August 26, 2026
Enterprise Next Best Action models require disciplined validation before they reach customers. This article connects statistical cross-validation with the staged delivery environments used by banks, explaining how development, UAT, performance testing and controlled pilots test whether models generalise under real operating conditions. It also examines the role of the Coefficient of Concordance in measuring a model’s ability to distinguish likely positive outcomes from negative ones.

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Tags: AI, Predictive Analytics, Risk Management

The Babylonian Data Problem: What Ancient Prices Teach Us About Sparse Data
LinkedIn
August 05, 2026
Alice Slotsky’s analysis of 430 commodity-price records from ancient Babylon reveals a problem that remains highly relevant today: how to model sparse, irregular data containing missing variables and sudden structural breaks. This article connects ancient economic records with contemporary applications in banking, insurance, central banking and emerging markets, examining where classical regression struggles and modern machine-learning methods can add value.

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Tags: AI, Analytics, Predictive Analytics

What Babylon's Barley Teaches a Modern Bank
LinkedIn
June 11, 2026
A reanalysis of Alice Slotsky's 2,400-year-old Babylonian commodity-price data with a modern Gaussian process — and what it says about calibrated uncertainty and the governance layer that sits above model scores in banking.

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Tags: AI Governance, Finance, Predictive Analytics

1 Presentation
Your Models Are Fine. Your Arbitration Layer Isn't.
LinkedIn
April 08, 2026
Most banks have invested millions in models and data.
Neither is the problem.
The problem is what happens between a model producing a score and a customer seeing an action.

See publication

Tags: AI, Analytics, Digital Transformation

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