Tax Consultant
Banking Technology
in Purwokerto

Core banking migration is one of the highest-risk projects a bank can undertake. Key challenges include: data migration for millions of accounts and historical transactions, maintaining zero system downtime during cutover, ensuring continuity of OJK and BI regulatory reporting, training thousands of tellers and customer service officers on new systems, and parallel running of legacy and new systems during transition. Typical projects take 2-4 years with budgets of IDR 100 billion to 1 trillion.

POJK 12/2019 on Banking IT Implementation requires banks to have: an IT master plan aligned with business strategy, IT risk management framework, primary and disaster recovery data centers with minimum 100km separation, information security management system, electronic data preservation for 10 years, business continuity plans tested semi-annually, and comprehensive IT compliance reports submitted to OJK.

Indonesia's open banking framework (SNAP - Standar Nasional Open API Pembayaran) mandates standardized APIs for payment initiation, account information, and other banking services. Banks must expose APIs with OAuth 2.0 security, standard data formats, and agreed service levels. The ecosystem enables fintech companies to build services on top of banking infrastructure while maintaining data security and customer consent requirements.

Indonesian banks face increasing threats including: DDoS attacks targeting digital banking channels, ransomware targeting critical infrastructure, phishing campaigns targeting customers, insider threats from employees or vendors, and API-based attacks exploiting open banking interfaces. The Indonesia Financial Services Authority (OJK) requires banks to maintain Security Operations Centers (SOC) and participate in sector-wide threat intelligence sharing.

Cloud adoption in Indonesian banking follows OJK's cloud computing regulation (POJK 11/2022) which permits public and hybrid cloud for non-core systems while requiring stricter governance for core systems. Banks typically start with cloud deployment for digital channels and analytics, then migrate core systems as cloud-native cores mature. Major Indonesian banks are adopting hybrid models with critical systems in private cloud and digital platforms on public cloud infrastructure.

AI applications in banking span: credit scoring and underwriting using alternative data, fraud detection through transaction pattern analysis, customer service via intelligent chatbots, personalized product recommendations based on spending patterns, anti-money laundering (AML) transaction monitoring with reduced false positives, and predictive analytics for customer churn prevention and cross-selling opportunities.