Global FinTech Hackcelerator

Customer behaviour, credit risk, and fraud patterns are constantly evolving. Traditional retraining approaches can be costly, slow to respond, and may erode valuable insights of its foundational understanding of long-term credit risk? At the same time, credit and fraud risks are often modelled separately despite sharing many underlying signals. How can we create a risk intelligence architecture that continuously learns from changing conditions, integrates credit and fraud insights, and maintains robust governance, transparency, and trust?

Over the next two decades, an estimated US$84 trillion will be transferred to the next generation of wealth holders. This cohort has grown up with consumer grade apps, mobile first services, and highly personalised digital experiences, and is more willing than previous generations to switch providers when expectations are not met. Private banks must evolve to meet changing client expectations while preserving the trust, discretion, and personalised service that define wealth management. How might we reimagine the end to end private banking experience, from discovery and onboarding to engagement, servicing, and relationship continuity, to better serve the next generation of high net worth clients while preserving the trust and human connection that underpin wealth management?

Many SMEs remain underinsured because they lack the knowledge, tools, and expertise to understand their business risks and insurance needs. As risks evolve and businesses grow, SMEs often struggle to assess their exposure, identify coverage gaps, and take actions that improve their resilience and insurability. How might we leverage AI to help SMEs better understand their risks, bridge protection gaps, access the right insurance solutions and value-added services throughout their business journey?