June 1, 2016 (Austin, TX) Crime Tech Solutions, LLC, a leading provider of analytics and investigation software for law enforcement and commercial markets, today announced that it has acquired Cleveland, TN based Case Closed Software in a cash transaction. The terms of the deal were not released, but according to Crime Tech Solutions’ founder and president Douglas Wood, the acquisition brings together two dynamic and fast-growing software companies with an unparalleled complement of technologies.
“For Crime Tech Solutions, the opportunity to add Case Closed Software into the fold was too good to pass up” said Mr. Wood. “We think that the technology offered by Case Closed helps to further differentiate us in the market as the price performance leader for this type of investigative solution.”
Crime Tech Solutions, based in the city of Leander, TX, delivers advanced analytics and investigation software to commercial investigators and law enforcement agencies across the globe. Their solution suite includes criminal intelligence software, sophisticated crime analytics with geospatial mapping, and powerful link analysis and visualization software. The company says that the addition of Case Closed Software expands those offerings even further.
Case Closed Software develops and markets investigative case management software specifically designed for law enforcement agencies. The suite is built around four primary software products including best-in-class investigative case management software, property and evidence tracking, a gang database tool, and an integrated link analysis and data visualization tool. The company also plans to release the solution as Case Closed Cloud for cloud-based access.
“Case Closed couldn’t be happier than to be joining Crime Tech Solutions,” said Keith Weigand, the company’s founder. “The blending of our technologies creates a suite that will add tremendous value to our mutual customers, and will be hard for others to duplicate.”
According to both Mr. Weigand and Mr. Wood, the name Case Closed will continue on as the product brand, given its widespread popularity and loyal customer base. Crime Tech Solutions is expected to retain all Case Closed employees, with Mr. Weigand joining as the company’s chief technical officer.
Crime Tech Solutions says it expects continued growth via ongoing software sales and strategic acquisitions.
About Crime Tech Solutions
(NOTE: Crime Tech Solutions is an Austin, TX based provider of crime and fraud analytics software for commercial and law enforcement groups. Our offerings include sophisticated Case Closed™ investigative case management and major case management, GangBuster™ gang intelligence software, powerful link analysis software, evidence management, mobile applications for law enforcement, comprehensive crime analytics with mapping and predictive policing, and 28 CFR Part 23 compliant criminal intelligence database management systems.)
Category Archives: Link Analysis
China building big data platform for pre-crime
Re-posted by Crime Tech Solutions – Your Source for Investigation Software
It’s “precrime” meets “thoughtcrime.” China is using its substantial surveillance apparatus as the basis for a “unified information environment” that will allow authorities to profile individual citizens based upon their online behaviors, financial transactions, where they go, and who they see. The authorities are watching for deviations from the norm that might indicate someone is involved in suspicious activity. And they’re doing it with a hand from technology pioneered in the US.
As Defense One’s Patrick Tucker reports, the Chinese government is leveraging “predictive policing” capabilities that have been used by US law enforcement, and it has funded research into machine learning and other artificial intelligence technologies to identify human faces in surveillance video. The Chinese government has also used this technology to create a “Situation-Aware Public Security Evaluation (SAPE) platform” that predicts “security events” based on surveillance data, which includes anything from actual terrorist attacks to large gatherings of people.
The Chinese government has plenty of data to feed into such systems. China invested heavily in building its surveillance capabilities in major cities over the past five years, with spending on “domestic security and stability” surpassing China’s defense budget—and turning the country into the biggest market for security technology. And in December, China’s government gained a new tool in surveillance: anti-terrorism laws giving the government even more surveillance powers and requiring any technology companies doing business in China to provide assistance in that surveillance.
The law states that companies “shall provide technical interfaces, decryption and other technical support and assistance to public security and state security agencies when they are following the law to avert and investigate terrorist activities”—in other words, the sort of “golden key” that FBI Director James Comey has lobbied for in the US. For obvious reasons, the Chinese government is particularly interested in the outcome of the current legal confrontation between the FBI and Apple over the iPhone used by Syed Farook.
Bloomberg reports that China is harnessing all that data in an effort to perform behavioral prediction at an individual level—tasking the state-owned defense contractor China Electronics Technology Group to develop software that can sift through the online activities, financial transactions, work data, and other behavioral data of citizens to predict which will perform “terrorist” acts. The system could watch for unexpected transfers of money, calls overseas by individuals with no relatives outside the country, and other trigger events that might indicate they were plotting an illegal action. China’s definition of “terrorism” is more expansive than that of many countries.
At a news conference in December, China Electronics Technology Group Chief Engineer Wu Manqing told reporters, “We don’t call it a big data platform, but a united information environment… It’s very crucial to examine the cause after an act of terror, but what is more important is to predict the upcoming activities.”
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(NOTE: Crime Tech Solutions is an Austin, TX based provider of crime and fraud analytics software for commercial and law enforcement groups. We proudly support the Association of Certified Fraud Examiners (ACFE), International Association of Chiefs of Police (IACP), Association of Law Enforcement Intelligence Units (LEIU) and International Association of Crime Analysts (IACA). Our offerings include sophisticated link analysis software, comprehensive crime analytics with mapping and predictive policing, and criminal intelligence database management systems.)
Link Analysis and Crime – An examination.
Posted by Tyler Wood, Operations Manager at Crime Tech Solutions
The topic of fraud is widely discussed, and the focus of thousands upon thousands of articles. Television shows such as Crime, Inc and American Greed have become popular due, in part, to our fascination with the topic of fraud.
The organizations that are affected by fraud are also fascinated… but for entirely different reasons. Some estimates suggest that the US economy loses 11 trillion dollars each year due to one form of fraud or another. It’s little wonder, therefore, that the companies most frequently defrauded have been heavily investing in anti-fraud technologies at an increasing rate over the past decade or more.
The biggest problem with fraud, of course, is that it is always evolving in a very Darwinian fashion. Like a living, breathing entity, fraud schemes change over time in order to survive. As the targets of fraud schemes put new policies, procedures and/or systems to deter the activities, the schemes modify and find new ways to survive.
So, since the nature of criminal activity is such that they constantly change, how do investigators find a fool proof methodology to ensure they are 100% safe from them? The answer, of course, is that they can’t. They never will; at least not until we live in a world such as the one depicted in the 2002 film Minority Report, starring Tom Cruise. In that movie, criminals are arrested prior to committing a crime based upon the predictions of psychics called ‘Precogs’. Corporations and individual targets of fraud can only wish.
Nope, there are no Precogs running around locking up would-be practitioners of fraud that would protect banks, insurance companies, Medicaid and Medicare programs, victims of Ponzi schemes, victims of identity theft, and countless others. Instead, organizations rely upon skilled knowledge workers using purpose-built crime and fraud analytics technology that can detect anomalies in patterns, suspicious transactions, hotspot mapping, networks of fraudsters, and other sophisticated data analytics tools.
Crime and fraud analytics
Any discussion of analytics and investigation software must touch upon the topic of ‘big data’. No longer just a buzz word, big data literally fuels the insights gathered by organizations in every area of business. Naturally, then, organizations who have been traditionally targeted by fraudsters have increasingly invested in crime technology such as investigation software and analytics in order to exploit the phenomenon.
Of course, big data in and by itself does nothing. It just sits there. Nobody has ever yelled “Help! We’ve been defrauded! Call the big data!” Big data is only useful when it can be transformed into ‘smart data’. In other words, understanding the big picture of costly fraudulent activities is not akin to understanding the specifics of ‘who’ is defrauding you, and ‘how’ they are doing it.
Those questions can best be answered through the powerful data mining and link analysis software tools offered by Austin, TX based Crime Tech Solutions in partnership with Sterling, VA based Visallo. Effective link analysis complements big data analytics platforms, helping to expose previously undetected fraud, and the entities (people or organizations) committing it.
Link Analysis – Transforming big data into smart data
By definition, link analysis is a data analysis technique that examines relationships among people, places, and things. As a visual tool, link analysis provides users a powerful method to quickly understand and ‘see’ what is happening. Because of this, it is widely used by financial institutions such as banks and insurance companies to uncover criminal networks, improve fraud investigations, detect insider fraud, and expose money laundering schemes. Similarly, government agencies use link analysis to investigate fraud, enhance screening processes, uncover terrorist networks and investigate criminal activities.
At Crime Tech Solutions, we liken the question of how to detect and deter fraud to ‘How do you eat an elephant?’ The answer, of course, is one bite at a time. If big data is the elephant, comprehensive link analysis software is part of the one ‘bite’ at a time. Or should we say ‘byte’.
(NOTE: Crime Tech Solutions is an Austin, TX based provider of investigation software and analytics for commercial and law enforcement groups. We proudly support the Association of Certified Fraud Examiners (ACFE), International Association of Chiefs of Police (IACP), Association of Law Enforcement Intelligence Units (LEIU) and International Association of Crime Analysts (IACA). Our offerings include sophisticated link analysis software, an industry-leading investigation case management solution, and criminal intelligence database management systems.)
What is Crime Analysis?
Posted by Tyler Wood Crime Tech Solutions, your source for investigation software.
The information provided on this page comes primarily from Boba, R. (2008: Pages 3 through 6) Crime Analysis with Crime Mapping. For a full discussion of the crime analysis discipline, refer to the book which can be obtained through www.sagepub.com.
Over the past 20 years, many scholars have developed definitions of crime analysis. Although definitions of crime analysis differ in specifics, they share several common components: all agree that crime analysis supports the mission of the police agency, utilizes systematic methods and information, and provides information to a range of audiences. Thus, the following definition of crime analysis is used as the foundation of this initiative:
Crime analysis is the systematic study of crime and disorder problems as well as other police–related issues—including sociodemographic, spatial, and temporal factors—to assist the police in criminal apprehension, crime and disorder reduction, crime prevention, and evaluation.
Clarification of each aspect of this definition helps to demonstrate the various elements of crime analysis. Generally, to study means to inquire into, investigate, examine closely, and/or scrutinize information. Crime analysis, then, is the focused and systematic examination of crime and disorder problems as well as other police-related issues. Crime analysis is not haphazard or anecdotal; rather, it involves the application of social science data collection procedures, analytical methods, and statistical techniques.
More specifically, crime analysis employs both qualitative and quantitative data and methods. Crime analysts use qualitative data and methods when they examine non-numerical data for the purpose of discovering underlying meanings and patterns of relationships. The qualitative methods specific to crime analysis include field research (such as observing characteristics of locations) and content analysis (such as examining police report narratives). Crime analysts use quantitative data and methods when they conduct statistical analysis of numerical or categorical data. Although much of the work in crime analysis is quantitative, crime analysts use simple statistical methods, such as frequencies, percentages, means, and rates. Typical crime analysis tools include link analysis and crime mapping software.
The central focus of crime analysis is the study of crime (e.g., rape, robbery, and burglary); disorder problems (e.g., noise complaints, burglar alarms, and suspicious activity); and information related to the nature of incidents, offenders, and victims or targets of crime (targets refer to inanimate objects, such as buildings or property). Crime analysts also study other police-related operational issues, such as staffing needs and areas of police service. Even though this discipline is called crime analysis, it actually includes much more than just the examination of crime incidents.
Although many different characteristics of crime and disorder are relevant in crime analysis, the three most important kinds of information that crime analysts use are sociodemographic, spatial, and temporal. Sociodemographic information consists of the personal characteristics of individuals and groups, such as sex, race, income, age, and education. On an individual level, crime analysts use sociodemographic information to search for and identify crime suspects. On a broader level, they use such information to determine the characteristics of groups and how they relate to crime. For example, analysts may use sociodemographic information to answer the question, “Is there a white, male suspect, 30 to 35 years of age, with brown hair and brown eyes, to link to a particular robbery?” or “Can demographic characteristics explain why the people in one group are victimized more often than people in another group in a particular area?”
The spatial nature of crime and other police-related issues is central to understanding the nature of a problem. In recent years, improvements in computer technology and the availability of electronic data have facilitated a larger role for spatial analysis in crime analysis. Visual displays of crime locations (maps) and their relationship to other events and geographic features are essential to understanding the nature of crime and disorder. Recent developments in criminological theory have encouraged crime analysts to focus on geographic patterns of crime, by examining situations in which victims and offenders come together in time and space.
Finally, the temporal nature of crime, disorder, and other police-related issues is a major component of crime analysis. Crime analysts conduct several levels of temporal analysis, including (a) examination of long-term patterns in crime trends over several years, the seasonal nature of crime, and patterns by month; (b) examination of mid-length patterns, such as patterns by day of week and time of day; and (c) examination of short-term patterns, such as patterns by day of the week, time of day, or time between incidents within a particular crime series.
The final part of the crime analysis definition—”to assist the police in criminal apprehension, crime and disorder reduction, crime prevention, and evaluation” generally summarizes the purpose and goals of crime analysis. The primary purpose of crime analysis is to support (i.e., “assist”) the operations of a police department. Without police, crime analysis would not exist as it is defined here.
The first goal of crime analysis is to assist in criminal apprehension, given that this is a fundamental goal of the police. For instance, a detective may be investigating a robbery incident in which the perpetrator used a particular modus operandi (i.e., method of the crime). A crime analyst might assist the detective by searching a database of previous robberies for similar cases.
Another fundamental police goal is to prevent crime through methods other than apprehension. Thus, the second goal of crime analysis is to help identify and analyze crime and disorder problems as well as to develop crime prevention responses for those problems. For example, members of a police department may wish to conduct a residential burglary prevention campaign and would like to target their resources in areas with the largest residential burglary problem. A crime analyst can assist by conducting an analysis of residential burglary to examine how, when, and where the burglaries occurred along with which items were stolen. The analyst can then use this information to develop crime prevention suggestions, (such as closing and locking garage doors) for specific areas.
Many of the problems that police deal with or are asked to solve are not criminal in nature; rather, they are related to quality of life and disorder. Some examples include false burglar alarms, loud noise complaints, traffic control, and neighbor disputes. The third goal of crime analysis stems from the police objective to reduce crime and disorder. Crime analysts can assist police with these efforts by researching and analyzing problems such as suspicious activity, noise complaints, code violations, and trespass warnings. This research can provide officers with information they can use to address these issues before they become more serious criminal problems.
The final goal of crime analysis is to help with the evaluation of police efforts by determining the level of success of programs and initiatives implemented to control and prevent crime and disorder and measuring how effectively police organizations are run. In recent years, local police agencies have become increasingly interested in determining the effectiveness of their crime control and prevention programs and initiatives. For example, an evaluation might be conducted to determine the effectiveness of a two-month burglary surveillance or of a crime prevention program that has sought to implement crime prevention through environmental design (CPTED) principles within several apartment communities. Crime analysts also assist police departments in evaluating internal organizational procedures, such as resource allocation (i.e., how officers are assigned to patrol areas), realignment of geographic boundaries, the forecasting of staffing needs, and the development of performance measures. Police agencies keep such procedures under constant scrutiny in order to ensure that the agencies are running effectively.
In summary, the primary objective of crime analysis is to assist the police in reducing and preventing crime and disorder. Present cutting edge policing strategies, such as hotspots policing, problem-oriented policing, disorder policing, intelligence-led policing, and CompStat management strategies, are centered on directing crime prevention and crime reduction responses based on crime analysis results. Although crime analysis is recognized today as important by both the policing and the academic communities, it is a young discipline and is still being developed. Consequently, it is necessary to provide new and experienced crime analysts with training and assistance that improves their skills and provides them examples of best practices from around the country and the world. http://crimetechsolutions.com
Uncovering Fraud means Uncovering Non-Obvious Relationships
Posted by Tyler Wood, Operations Manager at Crime Tech Solutions
Although no fraud prevention measures are ever 100% foolproof, significant progress can be achieved by looking beyond the individual data points to the relationships between them. This is the science of link analysis.
Looking at data relationships isn’t straightforward and doesn’t necessarily mean gathering new or more data. The key to battling financial crimes it is to look at the existing data in a new way – namely, in a way that makes underlying connections and patterns using powerful but proven tools such as the Sentinel Visualizer software offered by Crime Tech Solutions.
Unlike most other ways of looking at data, link analysis charts are designed to exploit relationships in data. That means they can uncover patterns difficult to detect using traditional representations such as tables.
Now, we all know that there are various types of fraud – first-party, insurance, and e-commerce fraud, for instance. What they all have in common is the layers of dishonesty to hide the crime. In each of these types of fraud, link analysis from Crime Tech Solutions offers a significant opportunity to augment existing methods of fraud detection, making evasion substantially more difficult.
Let’s take a look at first-party fraud. This type of fraud involves criminals who apply for loans or credit cards but who have no intention of ever paying the money back. It’s a serious problem for banks, who lose tens of billions of dollars every year to this form of fraud. It’s hard to detect and the fraudsters are good at impersonating good customers until the moment they do their ‘Bust-Out,’ i.e. cleaning out all their accounts and disappearing.
Another factor is the nature of the relationships between the participants in the fraud ring. While these characteristics make these schemes very damaging, it also renders them especially vulnerable to link analysis methods of fraud detection.
That’s because a first-party fraud ring involves a group of people sharing a subset of legitimate contact information and bogus information, and then combining them to create a number of synthetic identities. With these fake identities, fraudsters open new accounts for new forms of loans.
The fraudsters’ accounts are used in a normal manner with regular purchases and timely payments so that the banks gain confidence and slowly increase credit over time. Then, one day… Poof! The credit cards are maxed out and everyone has disappeared. The fraudsters are long gone and ready to hit the next bank down the road.
Gartner Group believes in a layered model for fraud prevention that starts with simple discrete methods but progresses to more elaborate types of analysis. The final layer, Layer 5, is called “Entity Link Analysis” and is designed to leverage connections in data in order to detect organized fraud.
In other words, Gartner believes that running appropriate entity link analysis queries can help organizations identify probable fraud rings during or even before the fraud occurs.
What is Link / Social Network Analysis?
Posted by Crime Tech Solutions
Computer-based link analysis is a set of techniques for exploring associations among large numbers of objects of different types. These methods have proven crucial in assisting human investigators in comprehending complex webs of evidence and drawing conclusions that are not apparent from any single piece of information. These methods are equally useful for creating variables that can be combined with structured data sources to improve automated decision-making processes. Typically, linkage data is modeled as a graph, with nodes representing entities of interest and links representing relationships or transactions. Links and nodes may have attributes specific to the domain. For example, link attributes might indicate the certainty or strength of a relationship, the dollar value of a transaction, or the probability of an infection.
Some linkage data, such as telephone call detail records, may be simple but voluminous, with uniform node and link types and a great deal of regularity. Other data, such as law enforcement data, may be extremely rich and varied, though sparse, with elements possessing many attributes and confidence values that may change over time.
Various techniques are appropriate for distinct problems. For example, heuristic, localized methods might be appropriate for matching known patterns to a network of financial transactions in a criminal investigation. Efficient global search strategies, on the other hand, might be best for finding centrality or severability in a telephone network.
Link analysis can be broken down into two components—link generation, and utilization of the resulting linkage graph.
Link Generation
Link generation is the process of computing the links, link attributes and node attributes. There are several different ways to define links. The different approaches yield very different linkage graphs. A key aspect in defining a link analysis is deciding which representation to use.
Explicit Links
A link may be created between the nodes corresponding to each pair of entities in a transaction. For example, with a call detail record, a link is created between the originating telephone number and the destination telephone number. This is referred to as an explicit link.
Aggregate Links
A single link may be created from multiple transactions. For example, a single link could represent all telephone calls between two parties, and a link attribute might be the number of calls represented. Thus, several explicit links may be collapsed into a single aggregate link.
Inferred Relationships
Links may also be created between pairs of nodes based on inferred strengths of relationships between them. These are sometimes referred to as soft links, association links, or co-occurrence links. Classes of algorithms for these computations include association rules, Bayesian belief networks and context vectors. For example, a link may be created between any pair of nodes whose context vectors lie within a certain radius of one another. Typically, one attribute of such a link is the strength of the relationship it represents. Time is a key feature that offers an opportunity to uncover linkages that might be missed by more typical data analysis approaches. For example, suppose a temporal analysis of wire transfer records indicates that a transfer from account A to person X at one bank is temporally proximate to a transfer from account B to person Y at another bank. This yields an inferred link between accounts A and B. If other aspects of the accounts or transactions are also suspicious, they may be flagged for additional scrutiny for possible money laundering activity.
A specific instance of inferred relationships is identifying two nodes that may actually correspond to the same physical entity, such as a person or an account. Link analysis includes mechanisms for collapsing these to a single node. Typically, the analyst creates rules or selects parameters specifying in which instances to merge nodes in this fashion.
Utilization
Once a linkage graph, including the link and node attributes, has been defined, it can be browsed, searched or used to create variables as inputs to a decision system.
Visualization
In visualizing linking graphs, each node is represented as an icon, and each link is represented as a line or an arrow between two nodes. The node and link attributes may be displayed next to the items or accessed via mouse actions. Different icon types represent different entity types. Similarly, link attributes determine the link representation (line strength, line color, arrowhead, etc.).
Standard graphs include spoke and wheel, peacock, group, hierarchy and mesh. An analytic component of the visualization is the automatic positioning of the nodes on the screen, i.e., the projection of the graph onto a plane. Different algorithms position the nodes based on the strength of the links between nodes or to agglomerate the nodes into groups of the same kind. Once displayed, the user typically has the ability to move nodes, modify node and link attributes, zoom in, collapse, highlight, hide or delete portions of the graph.
Variable Creation
Link analysis can append new fields to existing records or create entirely new data sets for subsequent modeling stages in a decision system. For example, a new variable for a customer might be the total number of email addresses and credit card numbers linked to that customer.
Search
Link analysis query mechanisms include retrieving nodes and links matching specified criteria, such as node and link attributes, as well as search by example to find more nodes that are similar to the specified example node.
A more complex task is similarity search, also called clustering. Here, the objective is to find groups of similar nodes. These may actually be multiple instances of the same physical entity, such as a single individual using multiple accounts in a similar fashion.
Network Analysis
Network analysis is the search for parts of the linkage graph that play particular roles. It is used to build more robust communication networks and to combat organized crime. This exploration revolves around questions such as:
- Which nodes are key or central to the network?
- Which links can be severed or strengthened to most effectively impede or enhance the operation of the network?
- Can the existence of undetected links or nodes be inferred from the known data?
- Are there similarities in the structure of subparts of the network that can indicate an underlying relationship (e.g., modus operandi)?
- What are the relevant sub-networks within a much larger network?
- What data model and level of aggregation best reveal certain types of links and sub-networks?
- What types of structured groups of entities occur in the data set?
Applications
Link analysis tools such as those provided by Crime Tech Solutions are increasingly used in law enforcement investigations, detecting terrorist threats, fraud detection, detecting money laundering, telecommunications network analysis, classifying web pages, analyzing transportation routes, pharmaceuticals research, epidemiology, detecting nuclear proliferation and a host of other specialized applications. For example, in the case of money laundering, the entities might include people, bank accounts and businesses, and the transactions might include wire transfers, checks and cash deposits. Exploring relationships among these different objects helps expose networks of activity, both legal and illegal.
What the heck do Crime Analysts do?
Posted by Crime Tech Solutions – Your source for analytics in the fight against crime and fraud.
NOTE: This great article is property of International Association of Crime Analysts and is posted in it’s original format HERE…
What do Crime Analysts Do?
One: Finding Series, Patterns, Trends, and Hot Spots as They Happen
Crime analysts review all police reports every day with the goal of identifying patterns as they emerge. If a burglar starts targeting drugs stores in your jurisdiction, a crime analyst will let you know on the second incident. If domestic violence becomes a recurring problem in one family, an analyst will catch it. If your city, town, or county faces any emerging problem—youth disorder on a particular street, street robbery hot spots, new trends in fraud and forgery, a pattern of items being stolen from cars—your analyst can identify it and alert you about it as soon as possible.
Analyses of these trends, patterns, and hot spots provide you with the who, what, when, where, how, and why of emerging crime in your community. You can use this information to develop effective tactics and strategies, interceding as soon as possible, preventing victimization, and reducing crime.
Two: Researching and Analyzing Long-Term Problems
Crime analysis isn’t just about immediate patterns and series:analysts also look at the long-term problems that every police department faces. From a park that has been a drug-dealing hot spot for 20 years to a street that has a high number of car accidents to ongoing issues with crime and disorder at budget motels, a crime analyst can take it apart, explore its dimensions, and help the police department come up with long-term solutions.
Three: Providing Information on Demand
How often have you been frustrated getting the information you need from your records management or CAD system? Crime analysts know how to extract data from records systems, ask questions of it, and turn it into useful information. They know how to get data from other sources, and how to work with it. They know how to create charts, maps, graphs, tables, and other visual products.
Whether you need a list of all the incidents of youth violence over five years, or a chart showing trends in OUI arrests, or some statistics on motor vehicle citations, or a map showing an upcoming parade route, or an estimate of how many officers you’ll need in five years if current population trends continue, a trained crime analyst can put it together quickly and clearly.
Four: Developing and Linking Local Intelligence
Since September 11, 2001, we hear a lot about the need for intelligence. But what is it? And what does it have to do with local police departments?
Intelligence describes special information about criminals and criminal organizations: their goals, their activities, their chains of command, how money and goods flow through them, what they’re planning, and so on. Analyzing intelligence data on national and international problems is generally the responsibility of national and international agencies, but local police departments and local analysts play an important role.
First, as information synthesizers, crime analysts often know when local information or intelligence fits with state, national, or international intelligence. If the FBI issues a bulletin stating that terrorists are using forged passports from Belgium, your analyst will know to pay special attention when one of your reports mentions a Belgian passport. If a state agency issues a report on motorcycle gangs, your analyst can integrate that with your own police reports. In the post-September 11 world, you’re bombarded with information from multiple agencies at multiple levels; with a crime analyst, you have someone who can sift through this information and extract what’s relevant to your agency.
Second, your crime analyst can apply criminal intelligence analysis tactics to your local problems. Do you need a link chart showing the relationships between members of a local street gang? Or a carefully-crafted timeline for a court presentation? An analyst is trained in such techniques.
Five: Making Your Department Look Good
A crime analyst makes you and your agency look good to the public and to local government officials. You’re fully informed about a crime pattern before the press calls about it. The analyses, statistics, and charts on your web site and in printed publications convey that you are on top of crime and disorder. And when someone wants some information—whether a town selectman looking for statistics on juvenile liquor parties or a reporter looking for the top accident hot spots—you can provide it completely and quickly.
Crime analysts can also enhance the things you already do. Their desktop publishing skills can breathe new life into your reports, newsletters, and alerts; their graphing and charting skills can spice up your community presentations and budget requests; and their overall analysis and communications skills means that you always have someone on hand to explain crime and disorder—whether in meetings, interviews, or formal presentations—to the members of the community you serve.
IBM Crime Analytics: Missing the mark? CTS Hits the bullseye!
Posted by Crime Tech Solutions – Your source for analytics in the fight against crime and fraud.
September 7, 2015. IBM announced this week a major update to its IBM i2 Safer Planet intelligence portfolio that includes a major overhaul of the widely used Analyst’s Notebook product. The product, which has become increasingly abandoned by its user base over the past five years, is now being positioned as ‘slicker‘ than previous versions.
IBM suggests that the new version scales from one to 1,000 users and can ingest petabytes of information to visualize. (A single petabyte roughly translates to 20,000,000 four-drawer filing cabinets completely filled with text).
That’s a lot of data. Seems to me that analysts are already inundated with data… now they need more?
This all begs the question: “Where is IBM headed with this product?”
The evidence seems to point to the fact that IBM wants this suite of products to compete head-to-head with money-raising machine and media darling Palantir Technologies. If I’m IBM, that makes sense. Palantir has been eating Big Blue’s lunch for a few years now, particularly at the lucrative US Federal market level. Worse yet, for IBM i2, is the recent news of a new competitor with even more powerful technology.
If I’m a crime or fraud analyst, however, I have to view this as IBM moving further and further away from my reality.
The reality? Nobody has ever yelled “Help! I’ve been robbed. Call the petabytes of ‘slick’ data!” No, this tiring ‘big data’ discussion is not really part of the day to day work for the vast majority of analysts. Smart people using appropriate data with intuitive and flexible crime technology solutions… that’s the reality for most of us.
So, as IBM moves their market-leading tool higher and higher into the stratosphere, where does the industry turn for more practical desktop solutions with realistic pricing? For more and more customers around the world, the answer is a crime and fraud link analytics tool from Crime Tech Solutions.
No, it won’t ingest 20,000,000 four-drawer filing cabinets of data, and it’s more ‘efficient‘ than ‘slick‘. Still, the product has been around for decades as a strong competitor to Analysts Notebook, and is well-supported by a network of strategic partners around the world. Importantly, it is the only American made and supported alternative. Period. It’s also, seemingly, the last man standing in the market for efficient and cost-effective tools that can be used by real people doing their real jobs.
Is "Minority Report" pure fiction?
Posted by Douglas Wood.
Journalist Raj Shekhar had an interesting article in the Times of India this week.
It’s like PreCrime, only four decades early. The “predictive policing” system seen in the Tom Cruise blockbuster Minority Report is now taking shape in Delhi. But instead of the three slime-immersed psychic “Precogs” that system relied on, Delhi Police’s crime prediction will be based on cold, hard data.
Once Enterprise Information Integration Solution or ‘EI2S’—a system that puts petabytes of information from more than a dozen crime databases at police staff’s fingertips—is ready, Delhi Police will be able to implement its ‘Crime Forecast’ plan to predict when and where criminals will strike.
The technology is not as fanciful as it seems at first and is already being tried out in many important cities, including New York, Los Angeles, London and Berlin. Officers associated with the plan say the software will analyze police data for patterns, compare it with other data from jails, courts and other crime-fighting agencies, and alert police to the likely threats. Data will be available not only on the suspects but also their likely victims.
A global tender has been floated for the project and Delhi Police is in talks with various firms for the technology.
According to the article, the system can help pre-empt many situations. For example, a violent clash between two gangs. It can identify individuals who are likely to join gangs or take to crime in an area based on the analyses of their behaviour and network. It can also curb domestic violence by identifying a pattern and predicting the next attack, the article said.
It all boils down to spotting patterns in mountains of data using tremendous computing power. A police document about the plan states that investigators should be able to perform crime series identification, crime trend identification, hot spot analysis and general analysis of criminal profiles. Link analysis will help spot common indicators of a crime by establishing associations and non obvious relationships between entities.
Using neighbourhood analysis, police will be able to understand crime events and the circumstances behind them in a small area as all the crime activity in a neighbourhood will be available for analysis. Criminal cases will be classified into multiple categories to understand what types of crime an area is prone to and the measures needed to curb them. Classification will be done through profiles of victims, suspects, localities and the modus operandi.
Another technique, called proximity analysis, will provide information about criminals, victims, witnesses and other people who are or were within a certain distance of the crime scene. By analyzing demographic and social trends, investigators will be able to understand the changes that have taken place in an area and their impact on criminality.
Network analysis will also be a part of this project to identify the important characteristics and functions of individuals within and outside a network, the network’s strengths and weaknesses and its financial and communication data.
While the system could help fight crime and rid Delhi of its ‘crime capital’ tag, it is bound to raise concerns over privacy and abuse as no predictive system can be foolproof.
The Name Game Fraud
Posted by Douglas Wood, Editor. Alright everybody, let’s play a game. The name game!
“Shirley, Shirley bo Birley. Bonana fanna fo Firley. Fee fy mo Mirley. Shirley!” No, not THAT name game. (Admit it… you used to love singing the “Chuck” version, though.)
The name game I’m referring to is slightly more sinister, and relates to the criminal intent to deceive others for gain by slightly misrepresenting attributes in order to circumvent fraud detection techniques. Pretty much anywhere money, goods, or services are dispensed, folks play the name game.
Utilities, Insurance, Medicaid, retail, FEMA. You name it.
Several years ago, I helped a large online insurance provider determine the extent to which they were offering insurance policies to corporations and individuals with whom they specifically did not want to do business. Here’s what the insurer knew:
- They had standard application questions designed to both determine the insurance quote AND to ensure that they were not doing business with undesirables. These questions included things such as full name, address, telephone number, date of birth, etc… but also questions related to the insured property. “Do you live within a mile of a fire station?”, Does your home have smoke detectors?”, and “Is your house made of matchsticks?”
- On top of the questions, the insurer had a list of entities with whom the knew they did not want to do business for one reason or another. Perhaps Charlie Cheat had some previously questionable claims… he would have been on their list.
In order to circumvent the fraud prevention techniques, of course, the unscrupulous types figured out how to mislead the insurer just enough so that the policy was approved. Once approved, the car would immediately be stolen. The house would immediately burn down, etc.
The most common way by which the fraudsters misled the insurers was a combination of The Name Game and modifying answers until the screening system was fooled. Through a combination of investigative case management and link analysis software, I went back and looked at several months of historical data and found some amazing techniques used by the criminals. Specifically, I found one customer who made 19 separate online applications – each time changing just one attribute or answer slightly – until the policy was issued. Within a week of the policy issue, a claim was made. You can use your imagination to determine if it was a legitimate claim. 😀
This customer, Charlie Cheat (obviously not his real name), first used his real name, address, telephone number, and date of birth… and answered all of the screening questions honestly. Because he did not meet the criteria AND appeared on an internal watch list for having suspicious previous claims, his application was automatically denied. Then he had his wife, Cheri Cheat, complete the application in hopes that the system would see a different name and approve the policy. Thirdly, he modified his name to Charlie Cheat, Chuck E. Cheat, and so on. Still no go. His address went from 123 Fifth Street to 123-A 5th Street. You get the picture.
Then he began to modify answers to the screening questions. All of a sudden, he DID live within a mile of a fire station… and his house was NOT made of matchsticks… and was NOT located next door to a fireworks factory. After almost two dozen attempts, he was finally issued the policy under a slightly revised name, a tweak in his address, and some less-than-truthful answers on the screening page. By investing in powerful investigative case management software with link analysis and fuzzy matching this insurer was able to dramatically decrease the number of policies issued to known fraudsters or otherwise ineligible entities.
Every time a new policy is applied for, the system analyzes the data against previous responses and internal watch lists in real time. In other words, Charlie and Cheri just found it a lot more difficult to rip this insurer off. These same situations occur in other arenas, costing us millions annually in increased taxes and prices. So, what happened to the Cheats after singing the name game?
Let’s just say that after receiving a letter from the insurer, Charlie and Cheri started singing a different tune altogether.