Financial Technology Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Finance Managers, Financial Controllers and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 7 Nov 2026 Course code SD-FT-028

Before you join: Participants should understand core finance processes such as accounts payable, accounts receivable, general ledger, budgeting, cash management, or financial reporting.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Finance functions are under pressure to close faster, forecast more accurately, control risk, and improve service without adding manual workload. Financial technology changes how transactions are processed, reconciliations are completed, credit decisions are supported, and reporting data is governed. The opportunity is not simply to buy new systems; it is to select, control, and implement technology that improves measurable finance outcomes while meeting security, regulatory, and audit requirements.

This course examines the technologies reshaping finance operations and financial services: cloud finance platforms, APIs, robotic process automation, data analytics, artificial intelligence, digital payments, distributed ledgers, and regulatory technology. Participants assess use cases against business value, data quality, operating risk, implementation effort, and control requirements. They learn to translate finance problems into technology requirements, evaluate vendors, define target processes, and establish governance for automated and data-driven decisions.

Teaching combines short instructor briefings with bank, corporate treasury, shared-services, and public-finance cases. Participants work through process maps, technology option assessments, control scenarios, vendor-selection criteria, and implementation decisions. They leave with a Financial Technology Adoption Pack containing a use-case prioritisation model, process assessment, requirements checklist, risk register, and 90-day application plan. The course is available as a five-day classroom programme in more than 50 cities or as live online instructor-led training. Participants who complete the course receive a certificate of completion.

The programme suits finance professionals who contribute to technology-enabled change and need enough technical fluency to work effectively with IT, data, risk, procurement, and external providers. It is particularly relevant where finance teams are replacing spreadsheets, modernising enterprise resource planning systems, introducing automated controls, or assessing digital financial-service propositions.

What you will be able to do

  • Assess financial technology use cases using value, feasibility, risk and control criteria
  • Map finance processes and identify automation opportunities using process-mapping techniques
  • Specify finance technology requirements through user stories, acceptance criteria and control needs
  • Evaluate cloud, API, automation and analytics solutions against defined selection criteria
  • Design data governance controls for finance data quality, lineage, access and retention
  • Apply NIST Cybersecurity Framework 2.0 principles to finance technology risk scenarios
  • Prepare a technology implementation roadmap with governance, milestones, dependencies and benefits measures
  • Produce a prioritised financial technology adoption plan for a finance function

Benefits of attending

For you

  • Build confidence evaluating finance technology proposals and vendor claims
  • Gain practical language for working with IT, data, security and procurement teams
  • Create defensible business cases for automation and finance-system investment
  • Recognise control failures in automated workflows before they become audit issues
  • Strengthen readiness for finance transformation and digital finance leadership roles

For your organisation

  • Prioritise technology investments against quantified finance-process pain points
  • Reduce manual reconciliation, rekeying and exception-handling effort
  • Improve control design for automated transactions and financial data
  • Make vendor selection more consistent through documented requirements and evaluation criteria
  • Deliver finance technology changes with clearer ownership, benefits measures and risk controls

Course modules

10 modules over 5 days

Participants can explain how financial technology changes finance processes, service models, controls, and decision rights.

  • Financial technology categories: platforms, automation, analytics, payments, and distributed ledgers
  • Finance operating model links among people, process, data, technology, governance
  • Value drivers: cost reduction, speed, accuracy, insight, and customer service
  • Technology maturity assessment across transaction processing, reporting, planning, and control
  • Shared-services, treasury, banking, and public-finance technology use cases
  • Build, buy, configure, and outsource decisions for finance capabilities

Participants can map finance workflows and select suitable candidates for digitisation and automation.

  • SIPOC mapping for procure-to-pay, order-to-cash, and record-to-report processes
  • Process mining concepts using event logs, timestamps, variants, and bottlenecks
  • Automation candidate scoring by volume, rules, exceptions, and control sensitivity
  • Robotic process automation for repetitive data entry and reconciliation tasks
  • Workflow orchestration, business rules engines, and human approval queues
  • Exception management design using thresholds, routing rules, and evidence retention
  • Segregation-of-duties controls within automated finance process flows

Participants can assess cloud finance platforms and define integration requirements for finance systems.

  • Cloud service models: SaaS, PaaS, IaaS, and shared responsibility
  • ERP modernisation drivers, configuration limits, and finance-control implications
  • API fundamentals: endpoints, authentication, payloads, rate limits, and error handling
  • ISO 20022 messages for payments, cash reporting, and bank connectivity
  • Integration patterns: point-to-point, middleware, event-driven, and batch interfaces
  • Master data alignment across customers, suppliers, accounts, and legal entities
  • Service-level agreements covering availability, support, recovery, and data ownership

Participants can define finance data requirements and assess analytics outputs for decision use.

  • Finance data architecture: source systems, warehouses, marts, and reporting layers
  • Data quality dimensions: completeness, accuracy, timeliness, consistency, and validity
  • Data lineage tracing from source transaction to management report
  • Chart-of-accounts design supporting statutory, management, and analytical reporting
  • Descriptive, diagnostic, predictive, and prescriptive analytics for finance decisions
  • Variance analysis using drivers, bridges, trends, and materiality thresholds
  • Dashboard design with KPIs, drill-down paths, owners, and refresh frequencies

Participants can evaluate artificial intelligence applications while defining appropriate human oversight and controls.

  • Machine-learning use cases for forecasting, fraud detection, and credit assessment
  • Generative AI uses for narrative reporting, policy queries, and document review
  • Training, validation, and test data distinctions for model development
  • Model performance measures: precision, recall, false positives, and calibration
  • Human-in-the-loop approval points for material financial decisions
  • Explainability requirements for automated credit, fraud, and compliance decisions
  • Prompt controls, confidential-data handling, and output verification procedures

Participants can assess payment and treasury technologies against settlement, liquidity, fraud, and customer requirements.

  • Payment rails: cards, ACH, wire transfers, instant payments, and wallets
  • Payment lifecycle from initiation through authorisation, clearing, settlement, and reconciliation
  • Treasury management systems for cash positioning, forecasting, and bank connectivity
  • Virtual accounts and payment factories for centralised cash operations
  • Fraud controls using payee verification, velocity rules, and transaction monitoring
  • Open banking APIs supporting account access, payment initiation, and consent
  • Digital identity methods: multifactor authentication, biometrics, and device recognition

Participants can distinguish credible distributed-ledger use cases from unsuitable or poorly controlled applications.

  • Distributed ledger architecture: nodes, consensus, immutability, and permissioning
  • Public, private, and consortium networks compared through governance requirements
  • Smart contracts for conditional settlement, escrow, and trade-finance workflows
  • Tokenisation of assets, liabilities, collateral, and ownership records
  • Digital asset custody, private-key management, and transaction authorisation
  • Accounting and valuation questions for digital asset holdings
  • Use-case screening against scalability, privacy, legal, and control constraints

Participants can identify technology risks and specify security, privacy, and resilience controls for finance solutions.

  • NIST Cybersecurity Framework 2.0 functions applied to finance technology risks
  • Identity and access management using least privilege and role-based access
  • Encryption controls for financial data at rest and in transit
  • PCI DSS v4.0 requirements for payment-card data environments
  • Third-party risk assessment covering providers, subcontractors, concentration, and exit
  • Business continuity planning with recovery objectives and fallback procedures
  • Incident response evidence, notification routes, and finance stakeholder responsibilities

Participants can establish governance and control arrangements for technology-enabled finance activities.

  • COBIT 2019 governance objectives for finance technology decision-making
  • Three-lines model roles across finance, technology, risk, and internal audit
  • Automated control design: preventive, detective, corrective, and compensating controls
  • Audit trails linking transactions, approvals, system changes, and reporting outputs
  • Regulatory technology for screening, monitoring, reporting, and compliance evidence
  • Model risk governance covering ownership, validation, monitoring, and retirement
  • Technology policies defining acceptable use, data handling, and accountability

Participants can prepare a prioritised implementation plan for a finance technology initiative.

  • Business case structure: problem, options, costs, benefits, risks, and assumptions
  • Requirements elicitation through stakeholder interviews, user stories, and process evidence
  • Vendor evaluation matrices using weighted criteria and demonstration scenarios
  • Total cost of ownership covering licences, integration, support, and change
  • Implementation roadmap sequencing pilots, dependencies, controls, and adoption activities
  • Benefits realisation measures for cycle time, error rates, cost, and compliance
  • Ninety-day application plan with owners, milestones, decisions, and review dates

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Financial technology use-case prioritisation matrix
  2. Finance process automation assessment template
  3. Technology requirements and vendor evaluation checklist
  4. Financial data governance model
  5. Finance technology risk and controls register
  6. 90-day financial technology adoption plan

Who should attend

  • Finance Managers — need to improve finance processes while retaining control and auditability
  • Financial Controllers — need to assess automation, reporting data and control implications
  • Finance Transformation Managers — need structured methods for selecting and implementing technology
  • Treasury Professionals — need to evaluate payment, liquidity and banking technology
  • Risk and Compliance Managers — need to govern emerging technology risks within finance activities
  • Business Analysts — need to translate finance requirements into workable technology specifications

Skills and tools covered

Finance process automationTechnology requirements definitionFinancial data governanceDigital payments assessmentCybersecurity risk controlImplementation roadmap planning

Tools and standards

ISO 20022, NIST Cybersecurity Framework 2.0, PCI DSS v4.0, COBIT 2019

How the course runs

Training methodology

The instructor uses short briefings to establish concepts, standards, and decision methods before applying them to realistic finance cases. Participants analyse payment failures, automation candidates, cloud-system proposals, data-quality issues, and cyber-control scenarios in small groups. Simulations test trade-offs between speed, cost, control, and customer experience. Facilitated discussion links each method to participants’ own finance processes. Individual application planning converts course outputs into a practical 90-day technology adoption agenda.

Requirements and prerequisites

Participants should understand core finance processes such as accounts payable, accounts receivable, general ledger, budgeting, cash management, or financial reporting. Experience using an enterprise resource planning system, finance software, or spreadsheets for analysis is helpful. The course assumes confidence discussing finance controls, business requirements, and process improvement with colleagues. Programming, database administration, data science, cybersecurity certification, or prior experience implementing financial technology is not required. Participants do not need to be IT specialists, although they should be prepared to assess technology decisions from a finance and control perspective.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

You should understand common finance processes, financial reporting, budgeting, treasury, or transaction processing. You do not need programming skills, cybersecurity certification, or previous financial technology implementation experience.

Bring examples of finance processes, recurring reporting problems, manual tasks, or proposed technology changes from your workplace. A laptop is useful for live online delivery and may support course materials in classroom sessions.

It suits finance managers, controllers, transformation staff, treasury professionals, business analysts, and risk professionals involved in finance change. It is designed for people who must make or influence technology decisions rather than build software.

This course focuses on evaluating and governing the technology used across finance processes, rather than teaching a single software product. It also covers automation, payments, AI, cybersecurity, data governance, vendor selection, and implementation planning.

You can use the templates to assess a manual process, define requirements for a proposed system, compare suppliers, or review controls around automated finance activity. The final application plan identifies actions that can begin within 90 days.

The course contains ten modules taught in sequence, covering roughly 30 contact hours within five training days from 08:30 to 16:30. Time is allocated between instructor briefings, case analysis, group work, simulations, and application planning.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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