Introduction to quantexa CDI syneo platform

Quantexa

Big data service provider , Use entity resolution , Relationship analysis and artificial intelligence technology help customers process data and prevent financial crimes .

Enterprise Overview

• 2016 Founded in , The current scale 500 people
• The service feature is scene decision-making intelligence CDI(contextual decision intelligence)
• The landing scene is mainly the anti money laundering and anti financial fraud monitoring of financial institutions , Data management , Risk control
• Problem solved : Regulatory compliance , Improve warning accuracy , cost reduction , Improve the competitiveness of the industry
• The main customers are banks , insurance , Payment agency , Operator, (CSP) And government agencies , Known customers have HSBC , Standard Chartered Bank , Dansk bank ( The Danish ), New York & Mellon bank , OFX( Australian payment agency )

time axis

2016

• 2016-03
  • Founded, 15 people(6 financial crime experts). Work for anti financial crimes for HSBC, services: AML, people traffic, solve the data problems
• 2016-09
  • SWIFT Innotribe Chanllenge Winner

2017

• 2017-03 3.3m in Series A investment
• 2017-10 Microsoft Accelerator Programme Winner
• 2017-? Synechron became a customer

2018

• 2018-04 Featured in Financial Times
• 2018-04 Named in Tech Nation Future 50
• 2018-04 HSBC became a customer
• 2018-07 Open US office in NY and Boston
• 2018-08 30m in Series B investment
• 2018-09 100 employees
• 2018-? Danske Bank a successful pilot

2019

• 2019-02 Featured in The Times
• 2019-02 Host QuanCon
• 2019-03 Appeared on CNN(TV)
• 2019-05 Named "Cool Vendor" by Gartner
• 2019-07 Appeared on Sky(TV)
• 2019-09 200 employees

2020

• 2020-07 64.7m in Series C funding. The round was led by Evolution Equity Partners,
• 2020-09 Engagement with BNY Mellon

2021

• 2021-07 153m in Series D funding from Warburg Pincus and a growing group of blue-chip investors
• 2021-09 BNY Mellon has completed a strategic investment in Quantexa.
• 2021-10 Quantexa 2 release - easier deployment, simplify navigation, introducing contextual search for unstructured data

2022

• 2022-04 Quantexa 2.1 release, introducing Geospatial Search

# Services and solutions

Quantexa Enable customers to make better decisions from data , According to its website , It is divided into two directions: monitoring and investigation , It may be the description of two different emphases of the same product .

Scene monitoring contextual monitoring

Combine internal data and external data to build a relationship network , Reduce false positives , Improve speed and accuracy , And identify previously undetected risks

• Enhance detection rates with advanced models that leverage network-based context to reduce false positives and generate more accurate alerts.
• Generate more meaningful alerts with context for investigators, leading to faster, trusted decisions.
• Find new, previously unknown risk from external sources to optimize future alert generation.

survey investigations

Respond quickly to alerts and information requests with visualization , Create individual portraits and real-time correlation and behavior maps for each customer and counterparty , Faster identification of financial crime and fraud risks .

• Automate manual work, and free up experts to focus on real risk.
• Create a true single view of each customer or counterparty, and a real-time network of relevant connections and behaviors.
• Go deeper and wider in your data to identify financial crime and fraud risks and typologies, faster.

Details of services involved

Anti money laundering KYC & AML

KYC and AML It is a financial regulatory requirement in most countries

• Transaction monitoring Transaction Monitoring, Alert the account of abnormal transactions
• Key monitoring list Watch List
• Identity verification Identity Verification, Keep the customer's identity and institutional information , Ensure the accuracy and effectiveness of the actual beneficiary information
• Case management Case Management
• behavior analysis Behavioral Analytics
• risk assessment Risk Assessment, Whether the transaction involves sensitive countries or regions
• Does the client include people who hold important public positions PEP Screening, Be sanctioned or involve any negative news / Media information
• Suspicious behavior report SARs (suspicious activity report)
• Investigation management Investigation Management
• Compliance report Compliance Reporting

Fraud detection Fraud Detection

• Custom fraud parameters Custom Fraud Parameters
• pattern recognition , banking / The insurance industry Pattern Recognition: for Banking, for Insurance Industry
• Investigation record Investigator Notes
• Check fraud monitoring Check Fraud Monitoring
• Internal fraud monitoring Internal Fraud Monitoring
• Authority security management Access Security Management
• Transaction review for e-commerce and digital currency Transaction Approval: for eCommerce, for Crypto

Data management Master Data Management

• Relation mapping Relationship Mapping
• Data masking Data Masking
• Process management Process Management
• visualization Visualization
• Match and merge Match & Merge
• Hierarchical management Hierarchy Management
• Data source integration Data Source Integrations
• Many fields / Multiple models Multi-Domain
• Data governance Data Governance
• Metadata management Metadata Management

Product introduction

The carrier of the above services and solutions is Quantexa Syneo platform . At present (2022.04) The latest version is 2.1

Product details

Quantexa Using big data and AI technology , Discover potential customer contact and behavior , To solve financial crimes 、 Demand for customer insight and data analysis

Fast data import Rapid data ingestion

• Scalable , High performance data subscription ( Import ), No need for complicated ETL; Automatically judge the existing data and structure , To configure , cleaning , Parsing and Standardization ; Open the box , With default entity definition and attribute settings , Pre trained models

• Acceptable , Unstructured and semi-structured input data ; Validate data fields when importing , Identify the problem ; Provide UI Enable users to operate and solve problems

• Quantexa It provides many analysis models for its customers , Currently available models include capital market anti money laundering ( Including foreign exchange 、 Stocks and precious metals ), Financial intelligence agency score , Reduce false positives , Trade anti money laundering , The customer gave a score of , Securities anti money laundering detection , Trade finance fraud , Credit card application fraud, etc

• Quantexa It also provides customized modeling and skill training services .

• Use Quantexa Fusion to model complex source data and ingest it fast with no-code, scalable, high performance data preparation and ingestion – and no complex ETL.

• Automatically infer, configure, cleanse, parse and standardize potential linking attributes from existing data schema.

• Get started quickly with out of the box, state-of-the-art AI-tuned models. Define entities and their attributes.

Entity parsing Entity Resolution

• Quantexa The entity analysis work connects internal and external data to get better accuracy , Even for data without unique keywords, it can get better results ; Define and create by , Business , Address and other data assets are output to batch and pipeline processing

• End users can drill down into an entity , See how and why different data records are matched to the same entity . Users can dynamically adjust the parsing matching logic .

• Connect internal and external data sources with unprecedented accuracy, even from poor quality data without unique match keys.

• Create data assets for people, businesses, addresses and more, and expose them through batch and real-time data pipelines.

Relationship map Network Generation

Use diagrams to show the real relationship between entities , These connections include supply chains , partners , Legal hierarchy , Social relations, etc ; Based on the dynamic entity, it can be parsed into different scenes , And generate different associations ; Mining users , Institutions , Association between address and transaction

• Use to generate graphs that link entities into relevant, real world networks representing supply chains, associates, legal hierarchies, social connections and more.
• Build on dynamic entity resolution to generate different networks for different use cases.
• Reveal the context of how people, organizations, places, and transactions relate to each other.

relation ( scene ) analysis Contextual analytics

• Use Quantexa Assess( May be Syneo An internal data asset management module , There is no separate introduction from the outside ) Create and maintain data relational models ; For machine learning and AI Service entity atlas analysis tool .

• Customers can import external detection models or use their own favorite analysis environment , Such as KNIME, R or Python. Modeling methods promote transparency and interpretability , And it can be run in batch or in real time .

• Use Quantexa Assess to empower data scientists to build and maintain their own contextual models with ease.

• Productively engineer features for machine learning and AI with native support for entity graphs and networks to build robust features for machine learning and AI.

Quantexa Supported machine learning algorithms and applicable scenarios

Visualization and exploration Visualization and exploration

• Investigators can search various customer and transaction data obtained by the platform

• The interface supports thousands of users to operate at the same time , Make fast and accurate cooperative decisions . The interface supports visual exploration and analysis , Create a label , Highlight the data of interest ; At the same time provide API To third-party systems such as CRM Etc

• Data privacy compliance : Quantexa Ability to restrict access to customer data , To allow its customers to comply with local data privacy requirements . When investigators interact with entities and maps , They can only view the data according to the user's permissions .

• Support thousands of users with faster, more accurate, collaborative decisioning using Quantexa’s UI to search, visualize and explore context; investigate and thematically analyze; and review analytically created flags within their context, highlighting points of interest.

• Or, use Quantexa’s APIs for external application platforms including CRM and case management.

Workflow

Data import and management

Scene analysis and investigation

Product technology stack

Language

• Scala
  Quantexa Syneo Main development language of
• Python
  Common languages used by data workers , For machine learning and data processing
• R
  Common languages used by data workers , Function rich , Commonly used in scientific computing , Statistics and data analysis , Make a picture

Storage

• PostgreSQL
  Small and medium-sized relational data storage
• Oracle
  Large and medium-sized relational data storage , Business software
• Hadoop/Hive
  Large scale distributed storage and processing , It is used for computing tasks with low timeliness requirements , It is speculated that this product is mainly used to give Spark Streaming Provide storage
• Elastic
  Data retrieval engine , Support distributed cluster
• Apache Spark, Spark Streaming
  Data processing engine , Support fault-tolerant high-throughput real-time streaming data processing , Can run in Hadoop or Google Cloud, Kubernetes above , Use memory computing , Faster
• Apache Kafka
  Message queue , Streaming data pipes , Used in Spark Receive and temporarily store data before

Containers

• Redhat Openshift (Kubernetes)

Third party service

• Google Cloud Storage
• Google Cloud SQL
• AWS
• Azure
• Salesforce

Interface display

Only the analysis part of the interface can be searched temporarily

These two versions are 2.1 New geographic location analysis function in

Market driven

Regulatory needs Regulatory requirements

for financial firms’ ability to detect money laundering continue to mount. The price of failure is hefty fines (banks worldwide have paid several billion dollars in fines for AML lapses since 2010), embarrassing headlines, and potential liability for the firm’s chief AML officer in the form of personal fines and even jail time.

Innovation needs Innovation

in financial services is creating an ever-growing attack surface. Faster payments and the increasing electronification of payment flows create utility for businesses, but criminals benefit from these innovations as well.

Customer expectations Customers’ expectations

for a smooth and easy experience put pressure on firms to reduce lag time and friction across the customer life cycle. These expectations start at the onboarding process and extend throughout the customer journey.

Historical technology upgrading pressure Legacy technology

that produces high volumes of alerts, false positives, and often false negatives compounds the challenges that banks face. Banks often have to throw bodies at the problem to keep up with alert volume. This is not only expensive but often problematic in terms of finding skilled analysts to fill these positions.

Public opinion pressure Social pressure

from citizens who feel that banks, as trusted custodians, have an ethical obligation to detect and intercede in money laundering, human trafficking, and fraud incidents

market trends Trends

Criminal attack technology against banks is constantly upgrading Escalating criminal attacks on banks use advanced technology.

Organized crime rings, rogue nations, and terrorists are all leveraging automation and artificial intelligence in their attacks on the financial ecosystem. These sophisticated attacks, combined with the growing volume of electronic payments, make it ifficult for FIs to keep pace with the rising tide of alerts.

Regulators want financial institutions to upgrade their technology to help them better improve their intelligence capabilities Regulators are encouraging FIs to use more sophisticated detection techniques.

Especially in the AML arena, concern over regulatory response to the use of advanced analytics has been an inhibitor to adoption. The new openness among regulators is encouraging FIs to invest in technology that can help them extract intelligence from their customer data.

Banks want to improve operational efficiency Banks are looking for operational efficiencies.

While many FIs initially turned to outsourcing first- and secondlevel alert triage to less expensive offshore locations, the benefits of these strategies were short-lived, as alert volumes continue to multiply. Many banks are now focused on tackling the source of the issue—dirty source data and high levels of false-positive alerts.

The adoption of new technologies creates competitive advantages for banks and other financial enterprises Adoption of next-generation financial crime technology is creating competitive differentiation.

Firms that use advanced technologies to vet customers’ identities and transactions differentiate themselves from their competitors, as they provide more responsive and streamlined customer interactions, improve their operational efficiency, and meet regulatory requirements.

Reference resources

1. Official site https://www.quantexa.com/
2. 2019-08-05 Jamie Hutton, chief technology officer at Quantexa, about building a culture of compliance within the banking industry.
   https://www.youtube.com/watch?v=X5vaAGfytA8
3. 2020-03-02 Ian Lees is the Head of Research and Development at Quantexa, he gave an introduction to Quantexa (our hosts) at the start of this months Scala in the City, Lightbend Edition
   https://www.youtube.com/watch?v=f5A1R_JCvqA
4. 2020-07 Quantexa Raises $64.7M to Drive Growth in Big Data and Analytics Ecosystem
   https://www.datanami.com/this-just-in/quantexa-raises-64-7m-to-drive-growth-in-big-data-and-analytics-ecosystem/
5. 2021-03-09 Jennifer Calvery, Head of Financial Crime HSBC. How HSBC Uses Technology To Combat Crime. See how HSBC is using technology to manage its data effectively and improve financial crime detection to tackle horrific crimes, from terrorist financing and human trafficking.
   https://www.youtube.com/watch?v=JmnI2K6OVNg
6. Follows a successful 12-month engagement with BNY Mellon using Quantexa's platform and includes an expanded relationship focused on data fabric innovation at the bank
   https://www.prnewswire.com/news-releases/bny-mellon-invests-in-quantexa-technology-301388579.html
7. OFX with Quantexa: OFX is an Australian foreign exchange and payments company https://cloud.google.com/customers/ofx-quantexa
8. Case of using Quantexa https://thefinancialcrimenews.com/why-illegal-trafficking-in-organs-is-growing-fastbut-few-are-talking-about-itby-steve-farrer/
9. Dun & Bradstreet partner with Quantexa https://www.dnb.com/solutions/partner/quantexa-partners-detail.html
10. Positive, PR service provider for Quantexa https://www.positivemarketing.com/case-studies/quantexa/