CAF
RCI
Centre for Analytical Finance
About CAF
The Centre for Analytical Finance (CAF) was established in the year 2004, with a mandate to produce high quality research, create research database, organise conferences and workshops, and train next generation of researchers in the area of finance. Through its Conferences, Workshops and Researcher’s Training programme, the Centre has created a forum for academicians, regulators and industry professionals, to discuss the latest issues and research. Centres association with the distinguished scholars of global repute and top industry practitioners makes it one of the premier research centres in South-east Asia.
Mission
- Undertake research projects that will aid and inform: Financial markets, Financial institutions, Financial instruments and Financial regulations
- Focus on issues in finance, including access to financial markets for small and micro entrepreneurs
- Disseminate research-based knowledge through conferences, workshops and lectures among all CAF constituencies: Academics, Practitioners, Regulators and policy-makers
- Create data-sets to help and benefit academicians as well as practitioners
- Consolidate our position as the premier research centre in the Asia-Pacific region
- Achieve global standing in the foreseeable future
Research
Our research focus includes real-time issues from financial markets, instruments, institutions, and regulations. We undertake projects which have policy implications, gather primary and secondary data, test our hypothesis by employing cutting-edge econometric techniques and come out with actionable recommendations. We form partnerships/associations and undertake collaborative research activities with finance think tanks and research centers of global standing.
Research Associate Programme
Training the next generation of researchers is an important CAF activity. Each year, CAF recruits two or three bright and motivated recent graduates in Finance, Statistics, Mathematics, Economics, Engineering, and Business as Researchers.
The center focuses on doing academic research with an industry application rigor. We design business tools using sophisticated models based on our ongoing research. These tools are actively used by lending institutions, credit bureaus and regulatory bodies whom we associate with as knowledge partners.
The tool uses state of the art machine learning algorithms to give a risk score associated with each new loan applicant. This tool uses information from the customer application, economic indicators local to the demographic factors and loan repayment partners of existing customers.
The tool has been designed based on the paper titled " Fintech for the Poor: Financial Intermediation Without Discrimination".
The tool uses state of art machine leaning algorithm to predict the stickiness of a customer to the banking correspondent network after a failed transaction. The tool helps the banking correspondent agents to take corrective measures to retain customers who are likely to drop out.
The tool has been designed based on the paper titled " Fintech for The Poor: Do Technological Failures Deter Financial Inclusion?".
The tool uses cluster models along with basic statistical predictors to identify volatility in banking correspondents’ transaction pattern. The tool helps the aggregator to monitor major deviation in agents’ transaction patterns.
The tool has been designed based on the paper titled " Fintech for The Poor: Do Technological Failures Deter Financial Inclusion?".
