Nana Abban and Martin Hinshelwood discuss the issues of the CIO and how we can use Evidence-based Management to solve them. Find out about the new Agility Index measures and Scrum.org's implementation of Evidence-based Management, Agility Path, in a worlewind 20 minute presentation.
Digital disruption, fourth industrial revolution, internet of things, smart contracts, big data, customer journey, fintech, smart city - all of them are parts of new reality, where biorithms exists. The king is attention, and everyone will keep their fight on it.
This document discusses effective management reporting systems for banks to measure value creation. It proposes using a value measuring methodology (VMM) with three components: a value structure identifying key areas that create value for customers, society, operations etc.; a cost structure; and a risk structure. Key performance indicators (KPIs) should be linked to key risk indicators (KRIs) to integrate risk and performance management. Appendices provide examples of mapping KRIs against potential impacts; sources of risk and performance; the risk-performance cycle; and how KPIs relate to risk appetite and tolerance. The document advocates a holistic approach linking financial, operational and risk metrics to truly reflect how value is created and destroyed.
This document discusses a new perspective on data management called Just in Time analytics. It focuses on harvesting both structured and unstructured data from various sources to answer typical questions, identify anomalies, and support business processes and decision making. The key aspects involve data harvesting, treating data as a service, establishing a data market and using data science. The goal is to provide a situation room and reports to enable operational excellence through hypothesis validation and proactive anomaly detection.
Nana Abban and Martin Hinshelwood discuss the issues of the CIO and how we can use Evidence-based Management to solve them. Find out about the new Agility Index measures and Scrum.org's implementation of Evidence-based Management, Agility Path, in a worlewind 20 minute presentation.
Digital disruption, fourth industrial revolution, internet of things, smart contracts, big data, customer journey, fintech, smart city - all of them are parts of new reality, where biorithms exists. The king is attention, and everyone will keep their fight on it.
This document discusses effective management reporting systems for banks to measure value creation. It proposes using a value measuring methodology (VMM) with three components: a value structure identifying key areas that create value for customers, society, operations etc.; a cost structure; and a risk structure. Key performance indicators (KPIs) should be linked to key risk indicators (KRIs) to integrate risk and performance management. Appendices provide examples of mapping KRIs against potential impacts; sources of risk and performance; the risk-performance cycle; and how KPIs relate to risk appetite and tolerance. The document advocates a holistic approach linking financial, operational and risk metrics to truly reflect how value is created and destroyed.
This document discusses a new perspective on data management called Just in Time analytics. It focuses on harvesting both structured and unstructured data from various sources to answer typical questions, identify anomalies, and support business processes and decision making. The key aspects involve data harvesting, treating data as a service, establishing a data market and using data science. The goal is to provide a situation room and reports to enable operational excellence through hypothesis validation and proactive anomaly detection.
Capital according to Basel - Business ArchitectureAlexei Blagirev
Define Key principles on business architecture framework for Basel II / III implementation within Financial Institutions in Russia. Describes basic principles and key aspects on difference between Basel approaches.
Defining the framework to open API for banking based on transactional banking approach for future integration on digital services outside of banks system
Bank Insight - from Data to Insight new framework for Banking Analytics.
Материалы, которые были использованы на выступлениях
OSP BigData Forum, Breakpointforum, ACH ИТ в Финансовом Секторе
Here are the key points about projection segmentation in Vertica:
- Projection segmentation splits large projections into multiple segments and distributes those segments across database nodes for improved parallelism and high availability.
- The segmentation process randomly distributes rows of data across all available nodes using a hash function. This random distribution helps optimize query performance.
- Segmentation allows Vertica to parallelize queries by enabling each node to work independently on its portion of the data.
- It also provides high availability because if a node fails, its data segments are available on other nodes, avoiding data loss.
- During recovery, the replacement node can retrieve missing segments from the live segments on other nodes.
- Administrators can control
Introduction to Vertica (Architecture & More)LivePerson
LivePersonDev is happy to host this meetup with Zvika Gutkin, an Oracle and Vertica expert DBA in LivePerson, and specialist in BI and Big Data.
At LivePerson, we handle enormous amounts of data. We use Vertica to analyse this data in real time.
In this lecture Zvika will cover the following:
1. Present the architecture of Vertica
2. Compare row store to column store
3. Explain how Vertica achieve Fast query time
4. Show few use cases .
5. Explains what does Liveperson do with Vertica? Why we chose Vertica?
6. Talk about why we Love Vertica and Why we hate it .
7. Is Vertica SQL DB or NoSQL? Is vertica Consistent or Eventually consistent?
8. How Vertica differ from other SQL and noSQL technologies?
Capital according to Basel - Business ArchitectureAlexei Blagirev
Define Key principles on business architecture framework for Basel II / III implementation within Financial Institutions in Russia. Describes basic principles and key aspects on difference between Basel approaches.
Defining the framework to open API for banking based on transactional banking approach for future integration on digital services outside of banks system
Bank Insight - from Data to Insight new framework for Banking Analytics.
Материалы, которые были использованы на выступлениях
OSP BigData Forum, Breakpointforum, ACH ИТ в Финансовом Секторе
Here are the key points about projection segmentation in Vertica:
- Projection segmentation splits large projections into multiple segments and distributes those segments across database nodes for improved parallelism and high availability.
- The segmentation process randomly distributes rows of data across all available nodes using a hash function. This random distribution helps optimize query performance.
- Segmentation allows Vertica to parallelize queries by enabling each node to work independently on its portion of the data.
- It also provides high availability because if a node fails, its data segments are available on other nodes, avoiding data loss.
- During recovery, the replacement node can retrieve missing segments from the live segments on other nodes.
- Administrators can control
Introduction to Vertica (Architecture & More)LivePerson
LivePersonDev is happy to host this meetup with Zvika Gutkin, an Oracle and Vertica expert DBA in LivePerson, and specialist in BI and Big Data.
At LivePerson, we handle enormous amounts of data. We use Vertica to analyse this data in real time.
In this lecture Zvika will cover the following:
1. Present the architecture of Vertica
2. Compare row store to column store
3. Explain how Vertica achieve Fast query time
4. Show few use cases .
5. Explains what does Liveperson do with Vertica? Why we chose Vertica?
6. Talk about why we Love Vertica and Why we hate it .
7. Is Vertica SQL DB or NoSQL? Is vertica Consistent or Eventually consistent?
8. How Vertica differ from other SQL and noSQL technologies?
1. В жизни всегда
есть место открытию
openbank.ru
AGILE FINANCE
Переход к гибким
сервисам
OUT OF THE FINANCE BOX
2. ЭТО VUCA МИР !
VUCA
VOLATILITY - ВОЛАТИЛЬНОСТЬ
UNCERTAINITY- НЕОПРЕДЕЛЕННОСТЬ
COMPLEXITY - СЛОЖНОСТЬ
AMBIGUITY - НЕТОЧНОСТЬ
3. ТРИ КЛЮЧЕВЫЕ ПРОБЛЕМЫ
3 KEY PROBLEMS
reporting
Данные
#1 Data
Используем только 10% из тех
данных, которые собираем
Regular Use only 10% of what we
have
Факторы
#2 Factors
Решения не принимаем
на основании фактов
Decision taken not by facts
Решения
#3 Decisions
Упускаем, от чего
именно зависит
прибыль организации
Miss key variances that
drives company PnL
4. #1 КАКИЕ ДАННЫЕ МОЖЕМ ИСПОЛЬЗОВАТЬ?
WHAT DATA CAN WE USE?
HOT DATA
COOL DATA
COLD DATA
Сейчас
NOW
Ранее
Earlier
Давно
Long ago
Взгляд на отчетность
Report view
Ценность
Value
Актуальность
предоставляемой
информации
Data applicability
5. #2 ФАКТОРЫ И ОТЧЕТНОСТЬ
FACTORS И ОТЧЕТНОСТЬ
Настоящий бизнес
Real Business
Как мы его обычно видим
How do we see
Отчетность
Reporting
«Черный Ящик»
Black box
8. AGILE FINANCE CONCEPT
Сервис
• Устойчивы к
изменениям
• Нацелены только
на создание
стоимости
Быстрота
• Управление
событиями и
аномалиями в
моменте
• Гибкая и
динамическая
аналитика
Гибкость
•Доступность [web,
мобильные и тд]
•Интеграция со
сложными
инструментами
анализа
9.
10. AGILE FINANCE
Понять и
прочувствовать
боль и проблему
Сформулировать
Point of View, о
гипотезе как
можно помочь в
решении
проблемы
Разобрать
самые
интересные и
необычные
идеи
Data Scout Finance Product Owner
12. FINANCE BUSINESS PARTNER
Это катализатор и синхронизатор бизнес
стратегии
Ясное понимание ключевых драйверов затрат и
потенциальных точек роста направлений бизнеса
Повышение скорости принятия решений и
достижение синергии с бизнес подразделениями
Повышение качества и точности управленческой
отчетности
Повышение качества решений и становление
неотъемлемой частью бизнес направления
.