An examination of the key dynamics in data aggregation for wealth in the context of open finance.
An independent evaluation and description of the ranking given to Broadridge in Chartis’ RiskTech100® 2021 report, with a focus on its fixed-income solution.
This, the inaugural STORM50 ranking and analysis, focuses on the computational infrastructure and algorithmic efficiency of the vast array of technology tools used across the financial services industry. In this report we explore specific aspects and…
This report contains Chartis’ updated view of the market and vendor landscape for governance, risk and compliance (GRC) solutions. Contains 8 RiskTech Quadrants.
This collaborative report from Chartis and iMeta discusses the risk and technology perspectives of client onboarding in wholesale banking, setting out the challenges and best practices for financial institutions.
In this supplement to Chartis' RiskTech100® report, profiles and interviews with some of the category winners' key representatives offer an insight into their performance and plans.
This short report is the second of our quarterly updates in which we review our research agenda and extend it by one quarter.
A 2021 update to our enterprise fraud research. Contains one RiskTech Quadrant.
The latest iteration of Chartis Research’s market-leading RiskTech100® report. Contains a ranking of the top 100 players in risk technology, more than 80 category winners, and an overview of some of Chartis' key research themes.
An analysis of Fenergo and its KYC software solution.
This report updates our previous KYC/AML quadrant reports. It examines financial institutions’ (FIs’) evolving technology requirements for Know Your Customer (KYC)/anti-money laundering (AML) processes and systems.
Financial firms neglect the hardware for AI tools at their peril. But even as chips and system architectures evolve, trade-offs remain. When it comes to hardware, firms need to know what to balance with what, to avoid being lumbered with fragmented IT…
This report updates our view of the market for CRQ solutions, highlighting the major trends and developments, and assessing the vendor landscape.
In this report we consider insurers’ evolving technology requirements for compliance with IFRS 17 and its US counterpart LDTI. As part of our analysis we also examine the core principles of LDTI, and the main areas in which it differs from IFRS 17…
In this latest Chartis Briefing, we consider the growing importance of CRQ technology, and the part it can play in financial institutions’ cyber risk management strategies.
The first quarterly rolling update of Chartis' research agenda - now includes Q1 2021.
Technology Solutions for Credit Risk 2.0: Credit Risk Analytics, 2020; Market Update and CVA/CLO Solutions Vendor Landscape
This report builds on the themes discussed in Technology Solutions for Credit Risk 2.0, 2018, published in May 2018. In that report we identified an emerging credit risk environment – which we call Credit Risk 2.0 – in which the banking book and default…
Failing to incorporate renewable energy sources effectively into power networks can create serious issues around energy pricing and forecasting. Some neural networks can mitigate renewables’ intermittency, but require the right expertise and data.
This supplement to the main RiskTech100 ranking report highlights the achievements and innovations of many of the featured vendors, giving readers a glimpse into what makes them successful.
This report – a collaborative publication from Chartis and ClusterSeven – examines a crucial period of activity for MRM users and sellers. It considers what MRM now means in a post-IFRS 9/CECL world, and how FIs can develop effective MRM solutions in…
A summary of Chartis' planned subscription reports and targeted topic areas for 2020, with a summary of the 'pillars' that will underpin our research.
Welcome to Big Bets, a briefing from Chartis Research in which we explore the five big themes we believe will shape the RiskTech marketplace in 2020.
Regulating AI is a challenge that must and will be faced. Central to effective regulation will be a robust, accurate taxonomy of the multiplicity of available AI techniques.