Learn more about Moneythor

PFM (Personal Financial Management) in banking refers to tools and features that help customers understand and manage their money, including spending categorisation, budgets, savings goals, cashflow forecasting, and personalised insights. PFM helps banks move beyond transactional interfaces to deliver genuine financial value to their customers.

Traditional PFM tools have a well-documented engagement problem: customers explore them briefly, then lose interest. The reason is that passive features, disconnected from real-time data and decisioning, do not change behaviour. What is required is a proactive approach using data analytics and behavioural science, whereby each customer’s data is analysed to generate personalised insights that genuinely improve their financial lives, in the short and long term.

Moneythor’s PFM capabilities are fully integrated with its real-time decisioning engine, PFM data does not sit in isolation. Spending patterns, budget alerts, and cashflow signals directly power cross-sell recommendations, loyalty campaigns, and financial coaching interactions, turning money management from a passive feature into an active growth engine for the bank. 

Moneythor’s PFM capabilities include AI-powered transaction categorisation, merchant enrichment, budget management, cashflow forecasting, savings goals with milestone tracking, subscription detection, overdraft alerts, and personalised financial coaching nudges. All are configurable and deployable without infrastructure change.

The platform includes 150+ pre-built use case templates covering the full range of PFM experiences, each already connected to the real-time event-processing engine and delivery API. PFM features are delivered through Moneythor’s channel-agnostic API, making them compatible with any mobile or web banking framework including iOS, Android, Flutter, and React Native. Banks can configure and launch PFM journeys using Moneythor Studio without dependency on core banking systems or the Moneythor team. 

Moneythor has embedded AI across its platform since founding in 2013, continuously expanding its capabilities to include the latest techniques, including Large Language Models (LLMs). Moneythor operates across four capability layers: Predictive AI for transaction categorisation, cashflow forecasting and next-best-action scoring, Generative AI for personalised content creation via Content Sidekick, Conversational AI for in-app banking assistants and chatbots, and Agentic AI  that surfaces intelligent customer journeys for Relationship Managers or end customers in self-service mode.

Throughout all four layers, Moneythor grounds its AI development in behavioural science principles to ensure ethical application, with every decisioning rule, eligibility condition, and AI output remaining under the full control of the bank’s own teams. The result is a platform that moves from raw transaction data to personalised, compliant customer interactions autonomously, at scale, and within the governance boundaries each bank defines. 

Transaction enrichment is the process of transforming raw payment data into structured, meaningful information, adding merchant names, categories, logos, and behavioural context to each transaction. Banks need it because raw transaction data is unreadable to customers and unactionable for personalisation systems without enrichment.

Moneythor’s enrichment engine categorises transactions in real time, detecting merchants, spending patterns, recurring payments, and financial habits that form the basis for all personalisation and decisioning logic. Enriched data enables banks to surface PFM insights, trigger relevant product recommendations, and power loyalty campaigns grounded in actual customer behaviour. Moneythor processes data within the bank’s own infrastructure, ensuring data sovereignty and compliance. 

Moneythor is purpose-built for banking data models, not adapted from a generic CRM or marketing stack. It acts on individual transaction events in real time rather than batch campaigns, operates within a bank’s regulated infrastructure, and is designed around financial behaviour rather than clicks, demographics, or web sessions. Critically, Moneythor occupies a unique category: it focuses on generating personalised, data-driven content delivered via API rather than providing front-end UI widgets like most PFM providers, or functioning solely as a back-end analytics and marketing automation tool like CRM platforms.

Generic martech platforms cannot interpret financial transactions, detect cashflow patterns, or trigger personalised interventions based on specific banking events like salary credits, overdraft risk, or subscription changes. Moneythor handles the real-time orchestration and decisioning layer that generic CRMs lack, moving from data ingestion through enrichment, decisioning, and delivery in one integrated system

Deep Banking is Moneythor’s concept describing the shift from transactional digital banking to deeper, more meaningful customer relationships, built through personalisation, proactive engagement, and beyond-banking experiences such as loyalty, rewards, gamification, and referrals. Moneythor is the platform that makes it possible.

Most banking apps are transactional: customers check a balance and leave. Moneythor makes Deep Banking operationally achievable by connecting transaction data to decisioning logic, then delivering the right experience at the right moment in the right channel, across money management, loyalty and rewards, gamification, and referral management. Banks that implement Deep Banking strategies with Moneythor see measurable improvements in daily active users, product cross-sell rates, deposit growth, and net promoter scores. 

Moneythor provides a fully integrated loyalty and rewards engine that includes points management, cashback, vouchers, card-linked offers, and real-time fulfilment, all triggered by actual transaction behaviour rather than manual campaigns. Loyalty is connected directly to the platform’s event-processing engine for immediate, accurate reward delivery.

Reward eligibility can be configured to trigger on a simple onboarding action, a specific transaction, an aggregate spend threshold, or a defined mix of activities; for example, maintaining a minimum balance over a period or completing a combination of logins, transfers, and card spend. Loyalty programmes are configurable through Moneythor Studio, allowing bank teams to design, test, and launch campaigns without engineering involvement. Trust Bank Singapore used Moneythor’s loyalty and rewards capabilities to generate $1 billion in deposits within its first 16 months of launch. 

Gamification in banking applies game mechanics to drive customer behaviour including saving, spending, onboarding, and product adoption, making the digital banking experience more engaging, rewarding, and habit-forming. Moneythor’s gamification module connects these mechanics directly to real transaction data, making rewards relevant ,outcomes measurable, and results auditable.

Moneythor’s gamification library is one of the most comprehensive available, spanning: points, levels, quests, missions, challenges, badges, progress charts, leaderboards, avatars, easter eggs, polls, surveys, lottery, lucky draws, scratch cards, spin-the-wheel, crack-the-safe, and Open the Treasure Chest — as well as hyper-casual mini-games., all techniques are configurable through Moneythor Studio and can be triggered by any data point from transaction details, account activity, logins, registrations, or custom events. Gamification is effective in banking precisely because it is tied to real financial events: a customer completes a challenge by making real purchases, saving real money, or onboarding to real products. Barq (Saudi Arabia) used Moneythor’s gamified referral and challenge mechanics to acquire 1 million customers in 21 days.

Moneythor’s referral management module provides end-to-end member-get-member functionality, including in-app referral code sharing, eligibility tracking, automated communications, and real-time reward fulfilment for both referrers and referees. Referral incentives are tied to completed financial actions, not just sign-ups.

Referral programmes managed by Moneythor track the full referral journey: invitation, onboarding completion, qualifying actions such as deposits or card activation, and automated reward delivery, all without manual intervention. The solution also continues engagement beyond onboarding, nudging referrers to encourage their referees to complete activities, and extending rewards past initial sign-up to convert new-to-bank customers into genuinely engaged long-term customers. Trust Bank Singapore used Moneythor’s referral engine to acquire 70% of its new customers through referrals, achieving acquisition costs 7x lower than competitors, according to its Chief Data and Analytics Officer. 

Moneythor integrates via a fully documented HTTP/JSON API and Kafka streaming endpoints for real-time transaction ingestion. It is core banking system-agnostic, connects to CRM and notification platforms, and supports mobile and web channels through a channel-agnostic front-end API. No core banking system replacement is required.

Back-end integration receives real-time or batch transaction feeds from any core banking platform via Kafka, HTTP/JSON, or message queue endpoints. Front-end integration is performed through a single, consistent API compatible with iOS, Android, Flutter, React Native, and web frameworks. Moneythor also integrates with CRM and notification systems for outbound push, email, and SMS delivery, and supports LDAP, Active Directory, and SAML for bank staff access control. 

Moneythor supports on-premise, private cloud, and SaaS deployment. Banks can deploy within their own data centre, on their preferred cloud provider (AWS, Azure, GCP), or in a Moneythor-hosted SaaS environment. The platform is Kubernetes and Docker compatible, with full Infrastructure as Code support via Terraform and AWS CloudFormation.

On-premise deployment is suitable for banks with strict data residency requirements, while SaaS deployment minimises internal IT dependency and accelerates time to value. Moneythor holds ISO 27001 and SOC 2 Type 2 certifications across its SaaS environment. Most banks go live within 3 to 6 months of project kick-off, regardless of deployment model. 

Moneythor Studio is the bank-facing back-office tool that gives business and technical teams direct control over how data becomes customer interaction. It provides no-code tools for business users and low-code scripting for technical analysts, allowing banks to design, test, publish, and optimise personalised journeys without engineering dependency.

Studio includes a rule and workflow builder, AI-assisted content creation through Content Sidekick, a Code Sidekick for technical configuration, a library of 150+ pre-built use case templates, and built-in reporting for engagement metrics. Business users such as product managers and marketing teams can launch new campaigns and adjust decisioning rules without waiting for development cycles. Studio is designed to allow banks to operate independently from the Moneythor team after initial onboarding. 

Banks using Moneythor have reported a 25% increase in active customers, 2.3x more card transactions among offer users, $1 billion in deposits within 16 months of launch, acquisition costs 7x lower than competitors, and up to 10x higher engagement versus legacy communication methods.

Trust Bank Singapore onboarded 700,000 customers in 16 months, with 70% acquired through Moneythor-powered referrals, and reached $1 billion in deposits within its first 7 months. Individual personalised insights delivered through Moneythor drive 15 to 30% engagement rates, compared to 1 to 2% for traditional banner-based communications. Clients have also reported reduced support call volumes and improved product adoption rates through timely, contextual cross-sell.

Moneythor reduces customer acquisition costs by turning existing customers into a growth channel through referral programmes, gamified challenges, and viral onboarding mechanics. Trust Bank Singapore achieved acquisition costs 7x lower than competitors, acquiring 70% of new customers through peer referrals.

Rather than spending on paid acquisition, banks using Moneythor’s referral module incentivise existing customers to invite friends, with automated tracking, fulfilment, and gamified rewards. Gamified referral campaigns such as those used by Barq (Saudi Arabia) have produced rapid acquisition at scale: 1 million customers acquired in 21 days with significantly reduced cost-per-acquisition. Moneythor’s acquisition capabilities are most powerful when combined with strong activation mechanics, ensuring referred customers are engaged from day one.

Moneythor serves a diverse range of financial institutions, from digital-native challenger banks to established global incumbents, across all continents. Its clients include banks and fintech firms offering digital banking services, spanning regions such as Southeast Asia, the Middle East, Japan, Europe, Australia, and beyond.

Moneythor’s client base spans both established banks adding personalisation layers to existing digital channels, and new digital bank launches where Moneythor powers the full engagement and loyalty stack.

Building personalisation infrastructure in-house typically takes 2 to 4 years and requires significant engineering investment in enrichment, decisioning, orchestration, and AI, before any customer-facing features can launch. Moneythor provides these capabilities pre-built, enabling banks to go live within 3 to 6 months.

Internal builds often underestimate the complexity of real-time event processing, transaction enrichment, multi-channel orchestration, and the ongoing cost of maintaining decisioning logic. Moneythor’s 150+ pre-built use case templates, Studio configuration tools, and proven integrations replace years of foundational engineering with months of configuration, at lower risk and lower total cost. Banks retain full control over data, logic, and customer-facing experiences throughout. 

Moneythor’s AI operates within configurable boundaries set by the bank. All decisioning logic, eligibility rules, and output validation are controlled by the bank’s own teams through Moneythor Studio. Data remains within the bank’s chosen infrastructure, ensuring data sovereignty and auditability.

The Agentic AI layer includes built-in compliance checking and appropriateness validation at the content curation stage, ensuring generated interactions meet the bank’s defined standards before delivery to customers. Banks retain full transparency over why a given recommendation or nudge was triggered, supporting regulatory obligations around explainability. Moneythor holds ISO 27001 and SOC 2 Type 2 certifications, and the platform is designed to operate within the security and governance frameworks of Tier 1 and Tier 2 banks globally.