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Open and fast Data - Survey 2019 - Ext


Regaining Control in an era of Fast & Open Data
Banking culture is traditionally anchored around trust and (operational + financial) control - for all the right reasons. Regulatory pressure and technology transformation are challenging the old ways. How can this closed and necessarily 'slow' environment deal with the dual challenges of high-volume, high-velocity data and the radical transparency mandated across banking and capital markets regulations, including Open Banking, PSD2, MiFID and SFTR ? 

The research will focus on insights that document the nature and impact of these two converging trends, and banks'  organisational and technological response. Responses are confidential and results will only be shared in aggregate form. 
1. Urgency drivers  - which statement best reflects your organisation's readiness for each of the following regulatory drivers ?
Space Cell Minimal compliance - we have done enough to meet regulatory requirementsMaximizing opportunities - part of transformational change programsWill be fully compliant in 6-12 monthsNot relevant to our business
Open Banking regulation (UK)
Open Payments regulation PSD2
Open Account Access regulation PSD2
Industry-wide transparency - regulatory reporting MiFID2
Client-facing transparency - Best Execution MiFID2
Transparency and customer protection across multiple regulations
2. What are the most significant benefits to your organization of using a platform which is ready for Open Banking, PSD2, and other transparency and access-driven compliance projects? Choose up to 3 drivers.
3. Which transparency-driven open banking use cases have the highest value? How ready is your firm to deliver these?
Space Cell Value/importance (low to high)Maturity/readiness to deliver (low to high)
Multi-bank account aggregation
Cash Management
Payment Initiation
Payment Status
Payment Account Information
Customer analytics
Product information
Product opening
Fraud and risk reduction
Credit Scoring
4. How often do data quality exceptions occur? How often does automated processing break down - requiring manual exception management for the following list of data exceptions?
Space Cell Multiple times per dayAt least 1x every weekAt least 1x every monthAlmost never
Missing or late data (eg NAV or pricing data)
Incomplete data (eg transaction without account ID or security identifier)
Inconsistent data – time series (new data point outside usual value range)
Inconsistent data – internal (data does not match between internal systems)
Inconsistent data – external (data does not match with counterparties, eg broker)
Data not in machine-readable format (emails, natural language, analogue sensor data)
Data in incompatible formats (intra-system and between counterparts)
Data needs to be manufactured, calculated, or derived before it can be used (eg for risk analysis)
Context: some high value or highly-sensitive exceptions can be automated but are subject to human oversight for reasons to do with compliance, risk management or customer impact
5. Who will benefit most from increased transparency and access to payment and account information?
6. In your estimate, what percentage of new business growth will be driven by your ability to monetize fast and open data? How soon?
Space Cell There is no obvious path to monetization of fast and open dataMonetization of data will contribute between 2-5% of new businessMonetization of data will contribute between 5-10% of new businessMonetization of data will contribute between 10-20% of new businessMonetization of data will contribute between 20-40% of new businessMonetization of data will contribute to more than 40% of new business
Current status
In 12 months time
In 24 months time
In 36 months time
7. What is the importance of each of these obstacles to investment in data control solutions?
Not Important at all
Very Important
No credible technology solutions
Lack of business case
Lack of customer interest
Regulatory compliance burden
Integration with existing technology
Too expensive
Lack of internal skills/knowledge
Organisational culture or bias
8. Which benefits are most likely to drive your firm's investment in improved data quality and control? Choose importance on scale of 1 to 10, 10 being the most important.
  *This question is required.
Space Cell Likely trigger to drive investment in data control solutions?
Reduce data management costs
Improve quality of customer service
Improve quality of business decision making
Improve scalability/robustness of workflows
Improve compliance with regulation
Enable digital transformation of customer engagement
Free up business operations resources
Free up IT operations resources
9. How do you categorize your organization's maturity level when it comes to IT investment in open banking and transparency-driven transformation projects?
10. As you invest  in future tech capabilities, what are the biggest drivers for improving data management? Score 1-10 with 10 being the most important. *This question is required.
Space Cell How relevant is this tech trend?
Ubiquitous, value-for-money Cloud infrastructure
RPA automation
AI (machine learning)
Data reconciliation
Streaming Data
Manufactured/Derived Data
Unstructured data (NLP, sentiment analysis)
Distributed ledger/Blockchain/DLT
Increased data control and oversight
11. As you prepare for future business  challenges, how do you measure the importance of the following drivers for improved data control? Score 1-10 with 10 being the most relevant business driver.
  *This question is required.
Space Cell How relevant is this Business Driver?
Cost and Margin Pressure
Customer experience management (milennials/un(der)served customers)
Digitisation of legacy client/intermediary channels
Complying with regulatory/transparency requirements
Readiness for alternative sourcing/operating models